diff --git a/.gitignore b/.gitignore index c1b85b62..7a847adc 100644 --- a/.gitignore +++ b/.gitignore @@ -1,47 +1,30 @@ -# IntelliJ project files -.idea -*.iml -out -gen - -### Vim template -[._]*.s[a-w][a-z] -[._]s[a-w][a-z] -*.un~ -Session.vim -.netrwhist -*~ - -### IPythonNotebook template -# Temporary data -.ipynb_checkpoints/ - -### Python template # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] *$py.class # C extensions -*.so +# *.so # Distribution / packaging .Python -env/ build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ -#lib/ -#lib64/ +# lib/ +lib64/ parts/ sdist/ var/ +wheels/ +share/python-wheels/ *.egg-info/ .installed.cfg *.egg +MANIFEST # PyInstaller # Usually these files are written by a python script from a template @@ -56,40 +39,105 @@ pip-delete-this-directory.txt # Unit test / coverage reports htmlcov/ .tox/ +.nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml -*,cover +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ # Translations *.mo *.pot # Django stuff: -*.log +# *.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy # Sphinx documentation docs/_build/ # PyBuilder +.pybuilder/ target/ -*.ipynb -*.params -*.json -.vscode/ +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json -lib/pycocotools/_mask.c -lib/nms/cpu_nms.c +# Pyre type checker +.pyre/ -output/* -models/* -log/* -data/* -external/ +# pytype static type analyzer +.pytype/ -draws/ -plot/ +# Cython debug symbols +cython_debug/ +*.pth +*.pt +extracted_frames/ +predicted_frames/ \ No newline at end of file diff --git a/README.md b/README.md index 40b7720e..2ff1c717 100644 --- a/README.md +++ b/README.md @@ -243,9 +243,7 @@ python visualization/plot_coco.py \ Many other dense prediction tasks, such as segmentation, face alignment and object detection, etc. have been benefited by HRNet. More information can be found at [High-Resolution Networks](https://github.com/HRNet). ### Other implementation -[mmpose](https://github.com/open-mmlab/mmpose)
-[ModelScope (中文）](https://modelscope.cn/models/damo/cv_hrnetv2w32_body-2d-keypoints_image/summary)
-[timm](https://huggingface.co/docs/timm/main/en/models/hrnet) +[mmpose](https://github.com/open-mmlab/mmpose) ### Citation diff --git a/data/ak_P2/annot/test.json b/data/ak_P2/annot/test.json new file mode 100644 index 00000000..0899ea69 --- /dev/null +++ b/data/ak_P2/annot/test.json @@ -0,0 +1,225062 @@ +[ + { + "image":"ABCSJZQJ\/ABCSJZQJ_f000023.jpg", + "animal":"Bird", + "animal_parent_class":"Bird", + "animal_class":"Bird", + "animal_subclass":"Bird", + "joints_vis":[ + 1, + 0, + 1, + 1, + 0, + 1, + 1, + 1, + 0, + 1, + 0, + 1, + 0, + 1, + 1, + 1, + 1, + 1, + 0, + 1, + 1, + 1, + 1 + ], + "joints":[ + [ + 351.7407963937, + 73.9684447785 + ], + [ + -1.0, + -1.0 + ], + [ + 364.0052592036, + 78.2486851989 + ], + [ + 407.7933884298, + 54.7355371901 + ], + [ + -1.0, + -1.0 + ], + [ + 372.0052592036, + 83.5078888052 + ], + [ + 416.7986476334, + 88.5078888053 + ], + [ + 340.9947407964, + 144.2066115701 + ], + [ + -1.0, + -1.0 + ], + [ + 354.0420736289, + 179.6882043575 + ], + [ + -1.0, + 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--git a/description-pak b/description-pak new file mode 100644 index 00000000..1c8e4235 --- /dev/null +++ b/description-pak @@ -0,0 +1 @@ +Package created with checkinstall 1.6.3 diff --git a/doc-pak/LICENSE b/doc-pak/LICENSE new file mode 100644 index 00000000..e692e188 --- /dev/null +++ b/doc-pak/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2019 Leo Xiao + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/doc-pak/README.md b/doc-pak/README.md new file mode 100644 index 00000000..2ff1c717 --- /dev/null +++ b/doc-pak/README.md @@ -0,0 +1,274 @@ +# Deep High-Resolution Representation Learning for Human Pose Estimation (CVPR 2019) +## News +- [2021/04/12] Welcome to check out our recent work on bottom-up pose estimation (CVPR 2021) [HRNet-DEKR](https://github.com/HRNet/DEKR)! +- [2020/07/05] [A very nice blog](https://towardsdatascience.com/overview-of-human-pose-estimation-neural-networks-hrnet-higherhrnet-architectures-and-faq-1954b2f8b249) from Towards Data Science introducing HRNet and HigherHRNet for human pose estimation. +- [2020/03/13] A longer version is accepted by TPAMI: [Deep High-Resolution Representation Learning for Visual Recognition](https://arxiv.org/pdf/1908.07919.pdf). It includes more HRNet applications, and the codes are available: [semantic segmentation](https://github.com/HRNet/HRNet-Semantic-Segmentation), [objection detection](https://github.com/HRNet/HRNet-Object-Detection), [facial landmark detection](https://github.com/HRNet/HRNet-Facial-Landmark-Detection), and [image classification](https://github.com/HRNet/HRNet-Image-Classification). +- [2020/02/01] We have added demo code for HRNet. Thanks [Alex Simes](https://github.com/alex9311). +- Visualization code for showing the pose estimation results. Thanks Depu! +- [2019/08/27] HigherHRNet is now on [ArXiv](https://arxiv.org/abs/1908.10357), which is a bottom-up approach for human pose estimation powerd by HRNet. We will also release code and models at [Higher-HRNet-Human-Pose-Estimation](https://github.com/HRNet/Higher-HRNet-Human-Pose-Estimation), stay tuned! +- Our new work [High-Resolution Representations for Labeling Pixels and Regions](https://arxiv.org/abs/1904.04514) is available at [HRNet](https://github.com/HRNet). Our HRNet has been applied to a wide range of vision tasks, such as [image classification](https://github.com/HRNet/HRNet-Image-Classification), [objection detection](https://github.com/HRNet/HRNet-Object-Detection), [semantic segmentation](https://github.com/HRNet/HRNet-Semantic-Segmentation) and [facial landmark](https://github.com/HRNet/HRNet-Facial-Landmark-Detection). + +## Introduction +This is an official pytorch implementation of [*Deep High-Resolution Representation Learning for Human Pose Estimation*](https://arxiv.org/abs/1902.09212). +In this work, we are interested in the human pose estimation problem with a focus on learning reliable high-resolution representations. Most existing methods **recover high-resolution representations from low-resolution representations** produced by a high-to-low resolution network. Instead, our proposed network **maintains high-resolution representations** through the whole process. +We start from a high-resolution subnetwork as the first stage, gradually add high-to-low resolution subnetworks one by one to form more stages, and connect the mutli-resolution subnetworks **in parallel**. We conduct **repeated multi-scale fusions** such that each of the high-to-low resolution representations receives information from other parallel representations over and over, leading to rich high-resolution representations. As a result, the predicted keypoint heatmap is potentially more accurate and spatially more precise. We empirically demonstrate the effectiveness of our network through the superior pose estimation results over two benchmark datasets: the COCO keypoint detection dataset and the MPII Human Pose dataset.
+ +![Illustrating the architecture of the proposed HRNet](/figures/hrnet.png) +## Main Results +### Results on MPII val +| Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mean | Mean@0.1 | +|--------------------|------|----------|-------|-------|------|------|-------|------|----------| +| pose_resnet_50 | 96.4 | 95.3 | 89.0 | 83.2 | 88.4 | 84.0 | 79.6 | 88.5 | 34.0 | +| pose_resnet_101 | 96.9 | 95.9 | 89.5 | 84.4 | 88.4 | 84.5 | 80.7 | 89.1 | 34.0 | +| pose_resnet_152 | 97.0 | 95.9 | 90.0 | 85.0 | 89.2 | 85.3 | 81.3 | 89.6 | 35.0 | +| **pose_hrnet_w32** | 97.1 | 95.9 | 90.3 | 86.4 | 89.1 | 87.1 | 83.3 | 90.3 | 37.7 | + +### Note: +- Flip test is used. +- Input size is 256x256 +- pose_resnet_[50,101,152] is our previous work of [*Simple Baselines for Human Pose Estimation and Tracking*](http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html) + +### Results on COCO val2017 with detector having human AP of 56.4 on COCO val2017 dataset +| Arch | Input size | #Params | GFLOPs | AP | Ap .5 | AP .75 | AP (M) | AP (L) | AR | AR .5 | AR .75 | AR (M) | AR (L) | +|--------------------|------------|---------|--------|-------|-------|--------|--------|--------|-------|-------|--------|--------|--------| +| pose_resnet_50 | 256x192 | 34.0M | 8.9 | 0.704 | 0.886 | 0.783 | 0.671 | 0.772 | 0.763 | 0.929 | 0.834 | 0.721 | 0.824 | +| pose_resnet_50 | 384x288 | 34.0M | 20.0 | 0.722 | 0.893 | 0.789 | 0.681 | 0.797 | 0.776 | 0.932 | 0.838 | 0.728 | 0.846 | +| pose_resnet_101 | 256x192 | 53.0M | 12.4 | 0.714 | 0.893 | 0.793 | 0.681 | 0.781 | 0.771 | 0.934 | 0.840 | 0.730 | 0.832 | +| pose_resnet_101 | 384x288 | 53.0M | 27.9 | 0.736 | 0.896 | 0.803 | 0.699 | 0.811 | 0.791 | 0.936 | 0.851 | 0.745 | 0.858 | +| pose_resnet_152 | 256x192 | 68.6M | 15.7 | 0.720 | 0.893 | 0.798 | 0.687 | 0.789 | 0.778 | 0.934 | 0.846 | 0.736 | 0.839 | +| pose_resnet_152 | 384x288 | 68.6M | 35.3 | 0.743 | 0.896 | 0.811 | 0.705 | 0.816 | 0.797 | 0.937 | 0.858 | 0.751 | 0.863 | +| **pose_hrnet_w32** | 256x192 | 28.5M | 7.1 | 0.744 | 0.905 | 0.819 | 0.708 | 0.810 | 0.798 | 0.942 | 0.865 | 0.757 | 0.858 | +| **pose_hrnet_w32** | 384x288 | 28.5M | 16.0 | 0.758 | 0.906 | 0.825 | 0.720 | 0.827 | 0.809 | 0.943 | 0.869 | 0.767 | 0.871 | +| **pose_hrnet_w48** | 256x192 | 63.6M | 14.6 | 0.751 | 0.906 | 0.822 | 0.715 | 0.818 | 0.804 | 0.943 | 0.867 | 0.762 | 0.864 | +| **pose_hrnet_w48** | 384x288 | 63.6M | 32.9 | 0.763 | 0.908 | 0.829 | 0.723 | 0.834 | 0.812 | 0.942 | 0.871 | 0.767 | 0.876 | + +### Note: +- Flip test is used. +- Person detector has person AP of 56.4 on COCO val2017 dataset. +- pose_resnet_[50,101,152] is our previous work of [*Simple Baselines for Human Pose Estimation and Tracking*](http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html). +- GFLOPs is for convolution and linear layers only. + + +### Results on COCO test-dev2017 with detector having human AP of 60.9 on COCO test-dev2017 dataset +| Arch | Input size | #Params | GFLOPs | AP | Ap .5 | AP .75 | AP (M) | AP (L) | AR | AR .5 | AR .75 | AR (M) | AR (L) | +|--------------------|------------|---------|--------|-------|-------|--------|--------|--------|-------|-------|--------|--------|--------| +| pose_resnet_152 | 384x288 | 68.6M | 35.3 | 0.737 | 0.919 | 0.828 | 0.713 | 0.800 | 0.790 | 0.952 | 0.856 | 0.748 | 0.849 | +| **pose_hrnet_w48** | 384x288 | 63.6M | 32.9 | 0.755 | 0.925 | 0.833 | 0.719 | 0.815 | 0.805 | 0.957 | 0.874 | 0.763 | 0.863 | +| **pose_hrnet_w48\*** | 384x288 | 63.6M | 32.9 | 0.770 | 0.927 | 0.845 | 0.734 | 0.831 | 0.820 | 0.960 | 0.886 | 0.778 | 0.877 | + +### Note: +- Flip test is used. +- Person detector has person AP of 60.9 on COCO test-dev2017 dataset. +- pose_resnet_152 is our previous work of [*Simple Baselines for Human Pose Estimation and Tracking*](http://openaccess.thecvf.com/content_ECCV_2018/html/Bin_Xiao_Simple_Baselines_for_ECCV_2018_paper.html). +- GFLOPs is for convolution and linear layers only. +- pose_hrnet_w48\* means using additional data from [AI challenger](https://challenger.ai/dataset/keypoint) for training. + +## Environment +The code is developed using python 3.6 on Ubuntu 16.04. NVIDIA GPUs are needed. The code is developed and tested using 4 NVIDIA P100 GPU cards. Other platforms or GPU cards are not fully tested. + +## Quick start +### Installation +1. Install pytorch >= v1.0.0 following [official instruction](https://pytorch.org/). + **Note that if you use pytorch's version < v1.0.0, you should following the instruction at to disable cudnn's implementations of BatchNorm layer. We encourage you to use higher pytorch's version(>=v1.0.0)** +2. Clone this repo, and we'll call the directory that you cloned as ${POSE_ROOT}. +3. Install dependencies: + ``` + pip install -r requirements.txt + ``` +4. Make libs: + ``` + cd ${POSE_ROOT}/lib + make + ``` +5. Install [COCOAPI](https://github.com/cocodataset/cocoapi): + ``` + # COCOAPI=/path/to/clone/cocoapi + git clone https://github.com/cocodataset/cocoapi.git $COCOAPI + cd $COCOAPI/PythonAPI + # Install into global site-packages + make install + # Alternatively, if you do not have permissions or prefer + # not to install the COCO API into global site-packages + python3 setup.py install --user + ``` + Note that instructions like # COCOAPI=/path/to/install/cocoapi indicate that you should pick a path where you'd like to have the software cloned and then set an environment variable (COCOAPI in this case) accordingly. +4. Init output(training model output directory) and log(tensorboard log directory) directory: + + ``` + mkdir output + mkdir log + ``` + + Your directory tree should look like this: + + ``` + ${POSE_ROOT} + ├── data + ├── experiments + ├── lib + ├── log + ├── models + ├── output + ├── tools + ├── README.md + └── requirements.txt + ``` + +6. Download pretrained models from our model zoo([GoogleDrive](https://drive.google.com/drive/folders/1hOTihvbyIxsm5ygDpbUuJ7O_tzv4oXjC?usp=sharing) or [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blW231MH2krnmLq5kkQ)) + ``` + ${POSE_ROOT} + `-- models + `-- pytorch + |-- imagenet + | |-- hrnet_w32-36af842e.pth + | |-- hrnet_w48-8ef0771d.pth + | |-- resnet50-19c8e357.pth + | |-- resnet101-5d3b4d8f.pth + | `-- resnet152-b121ed2d.pth + |-- pose_coco + | |-- pose_hrnet_w32_256x192.pth + | |-- pose_hrnet_w32_384x288.pth + | |-- pose_hrnet_w48_256x192.pth + | |-- pose_hrnet_w48_384x288.pth + | |-- pose_resnet_101_256x192.pth + | |-- pose_resnet_101_384x288.pth + | |-- pose_resnet_152_256x192.pth + | |-- pose_resnet_152_384x288.pth + | |-- pose_resnet_50_256x192.pth + | `-- pose_resnet_50_384x288.pth + `-- pose_mpii + |-- pose_hrnet_w32_256x256.pth + |-- pose_hrnet_w48_256x256.pth + |-- pose_resnet_101_256x256.pth + |-- pose_resnet_152_256x256.pth + `-- pose_resnet_50_256x256.pth + + ``` + +### Data preparation +**For MPII data**, please download from [MPII Human Pose Dataset](http://human-pose.mpi-inf.mpg.de/). The original annotation files are in matlab format. We have converted them into json format, you also need to download them from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blW00SqrairNetmeVu4) or [GoogleDrive](https://drive.google.com/drive/folders/1En_VqmStnsXMdldXA6qpqEyDQulnmS3a?usp=sharing). +Extract them under {POSE_ROOT}/data, and make them look like this: +``` +${POSE_ROOT} +|-- data +`-- |-- mpii + `-- |-- annot + | |-- gt_valid.mat + | |-- test.json + | |-- train.json + | |-- trainval.json + | `-- valid.json + `-- images + |-- 000001163.jpg + |-- 000003072.jpg +``` + +**For COCO data**, please download from [COCO download](http://cocodataset.org/#download), 2017 Train/Val is needed for COCO keypoints training and validation. We also provide person detection result of COCO val2017 and test-dev2017 to reproduce our multi-person pose estimation results. Please download from [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blWzzDXoz5BeFl8sWM-) or [GoogleDrive](https://drive.google.com/drive/folders/1fRUDNUDxe9fjqcRZ2bnF_TKMlO0nB_dk?usp=sharing). +Download and extract them under {POSE_ROOT}/data, and make them look like this: +``` +${POSE_ROOT} +|-- data +`-- |-- coco + `-- |-- annotations + | |-- person_keypoints_train2017.json + | `-- person_keypoints_val2017.json + |-- person_detection_results + | |-- COCO_val2017_detections_AP_H_56_person.json + | |-- COCO_test-dev2017_detections_AP_H_609_person.json + `-- images + |-- train2017 + | |-- 000000000009.jpg + | |-- 000000000025.jpg + | |-- 000000000030.jpg + | |-- ... + `-- val2017 + |-- 000000000139.jpg + |-- 000000000285.jpg + |-- 000000000632.jpg + |-- ... +``` + +### Training and Testing + +#### Testing on MPII dataset using model zoo's models([GoogleDrive](https://drive.google.com/drive/folders/1hOTihvbyIxsm5ygDpbUuJ7O_tzv4oXjC?usp=sharing) or [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blW231MH2krnmLq5kkQ)) + + +``` +python tools/test.py \ + --cfg experiments/mpii/hrnet/w32_256x256_adam_lr1e-3.yaml \ + TEST.MODEL_FILE models/pytorch/pose_mpii/pose_hrnet_w32_256x256.pth +``` + +#### Training on MPII dataset + +``` +python tools/train.py \ + --cfg experiments/mpii/hrnet/w32_256x256_adam_lr1e-3.yaml +``` + +#### Testing on COCO val2017 dataset using model zoo's models([GoogleDrive](https://drive.google.com/drive/folders/1hOTihvbyIxsm5ygDpbUuJ7O_tzv4oXjC?usp=sharing) or [OneDrive](https://1drv.ms/f/s!AhIXJn_J-blW231MH2krnmLq5kkQ)) + + +``` +python tools/test.py \ + --cfg experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml \ + TEST.MODEL_FILE models/pytorch/pose_coco/pose_hrnet_w32_256x192.pth \ + TEST.USE_GT_BBOX False +``` + +#### Training on COCO train2017 dataset + +``` +python tools/train.py \ + --cfg experiments/coco/hrnet/w32_256x192_adam_lr1e-3.yaml \ +``` + +### Visualization + +#### Visualizing predictions on COCO val + +``` +python visualization/plot_coco.py \ + --prediction output/coco/w48_384x288_adam_lr1e-3/results/keypoints_val2017_results_0.json \ + --save-path visualization/results + +``` + + + + + + +### Other applications +Many other dense prediction tasks, such as segmentation, face alignment and object detection, etc. have been benefited by HRNet. More information can be found at [High-Resolution Networks](https://github.com/HRNet). + +### Other implementation +[mmpose](https://github.com/open-mmlab/mmpose) + + +### Citation +If you use our code or models in your research, please cite with: +``` +@inproceedings{sun2019deep, + title={Deep High-Resolution Representation Learning for Human Pose Estimation}, + author={Sun, Ke and Xiao, Bin and Liu, Dong and Wang, Jingdong}, + booktitle={CVPR}, + year={2019} +} + +@inproceedings{xiao2018simple, + author={Xiao, Bin and Wu, Haiping and Wei, Yichen}, + title={Simple Baselines for Human Pose Estimation and Tracking}, + booktitle = {European Conference on Computer Vision (ECCV)}, + year = {2018} +} + +@article{WangSCJDZLMTWLX19, + title={Deep High-Resolution Representation Learning for Visual Recognition}, + author={Jingdong Wang and Ke Sun and Tianheng Cheng and + Borui Jiang and Chaorui Deng and Yang Zhao and Dong Liu and Yadong Mu and + Mingkui Tan and Xinggang Wang and Wenyu Liu and Bin Xiao}, + journal = {TPAMI} + year={2019} +} +``` diff --git a/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_ak.yaml b/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_ak.yaml new file mode 100644 index 00000000..963602bb --- /dev/null +++ b/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_ak.yaml @@ -0,0 +1,121 @@ +AUTO_RESUME: true +CUDNN: + BENCHMARK: true + DETERMINISTIC: false + ENABLED: true +DATA_DIR: '' +GPUS: (0,) #[0] #(0,1) ## Change based on number of GPUs +OUTPUT_DIR: 'output/ak_P2' #'output/ak_P3_reptile' ## Change based on Protocol +LOG_DIR: 'log/ak_P2' #'log/ak_P3_reptile' ## Change based on Protocol +WORKERS: 4 # 24 +PRINT_FREQ: 100 + +DATASET: + COLOR_RGB: true + DATASET: ak + DATA_FORMAT: jpg + FLIP: true + NUM_JOINTS_HALF_BODY: 11 + PROB_HALF_BODY: -1.0 + ROOT: 'data/ak_P2' ## Change based on Protocol + IMAGE_ROOT: "E:/huazhen/dataset/AnimalKingdom-PoseEstimation/dataset/" # "F:/dataset/Animal_Kingdom/pose_estimation/dataset/" + ROT_FACTOR: 30 + SCALE_FACTOR: 0.25 + TEST_SET: test + TRAIN_SET: train +MODEL: + INIT_WEIGHTS: true + NAME: pose_hrnet + NUM_JOINTS: 23 + PRETRAINED: '' #'models/pytorch/imagenet/hrnet_w32-36af842e.pth' + TARGET_TYPE: gaussian + IMAGE_SIZE: + - 256 + - 256 + HEATMAP_SIZE: + - 64 + - 64 + SIGMA: 2 + EXTRA: + PRETRAINED_LAYERS: + - 'conv1' + - 'bn1' + - 'conv2' + - 'bn2' + - 'layer1' + - 'transition1' + - 'stage2' + - 'transition2' + - 'stage3' + - 'transition3' + - 'stage4' + FINAL_CONV_KERNEL: 1 + STAGE2: + NUM_MODULES: 1 + NUM_BRANCHES: 2 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + FUSE_METHOD: SUM + STAGE3: + NUM_MODULES: 4 + NUM_BRANCHES: 3 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + - 128 + FUSE_METHOD: SUM + STAGE4: + NUM_MODULES: 3 + NUM_BRANCHES: 4 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + - 128 + - 256 + FUSE_METHOD: SUM +LOSS: + USE_TARGET_WEIGHT: true +TRAIN: + BATCH_SIZE_PER_GPU: 32 + SHUFFLE: true + BEGIN_EPOCH: 0 + END_EPOCH: 150 + OPTIMIZER: adam + LR: 0.001 + LR_FACTOR: 0.1 + LR_STEP: + - 170 + - 200 + WD: 0.0001 + GAMMA1: 0.99 + GAMMA2: 0.0 + MOMENTUM: 0.9 + NESTEROV: false +TEST: + BATCH_SIZE_PER_GPU: 32 + MODEL_FILE: '' + FLIP_TEST: true + POST_PROCESS: true + SHIFT_HEATMAP: true +DEBUG: + DEBUG: true + SAVE_BATCH_IMAGES_GT: true + SAVE_BATCH_IMAGES_PRED: true + SAVE_HEATMAPS_GT: true + SAVE_HEATMAPS_PRED: true diff --git a/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_akP1.yaml b/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_akP1.yaml new file mode 100644 index 00000000..c95ede89 --- /dev/null +++ b/experiments/mpii/hrnet/w32_256x256_adam_lr1e-3_akP1.yaml @@ -0,0 +1,120 @@ +AUTO_RESUME: true +CUDNN: + BENCHMARK: true + DETERMINISTIC: false + ENABLED: true +DATA_DIR: '' +GPUS: [0] #(0,1) ## Change based on number of GPUs +OUTPUT_DIR: 'output/ak_P1' ## Change based on Protocol +LOG_DIR: 'log/ak_P1' ## Change based on Protocol +WORKERS: 24 +PRINT_FREQ: 100 + +DATASET: + COLOR_RGB: true + DATASET: ak + DATA_FORMAT: jpg + FLIP: true + NUM_JOINTS_HALF_BODY: 11 + PROB_HALF_BODY: -1.0 + ROOT: 'data/ak_P1' ## Change based on Protocol + ROT_FACTOR: 30 + SCALE_FACTOR: 0.25 + TEST_SET: test + TRAIN_SET: train +MODEL: + INIT_WEIGHTS: true + NAME: pose_hrnet + NUM_JOINTS: 23 + PRETRAINED: '' #'models/pytorch/imagenet/hrnet_w32-36af842e.pth' + TARGET_TYPE: gaussian + IMAGE_SIZE: + - 256 + - 256 + HEATMAP_SIZE: + - 64 + - 64 + SIGMA: 2 + EXTRA: + PRETRAINED_LAYERS: + - 'conv1' + - 'bn1' + - 'conv2' + - 'bn2' + - 'layer1' + - 'transition1' + - 'stage2' + - 'transition2' + - 'stage3' + - 'transition3' + - 'stage4' + FINAL_CONV_KERNEL: 1 + STAGE2: + NUM_MODULES: 1 + NUM_BRANCHES: 2 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + FUSE_METHOD: SUM + STAGE3: + NUM_MODULES: 4 + NUM_BRANCHES: 3 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + - 128 + FUSE_METHOD: SUM + STAGE4: + NUM_MODULES: 3 + NUM_BRANCHES: 4 + BLOCK: BASIC + NUM_BLOCKS: + - 4 + - 4 + - 4 + - 4 + NUM_CHANNELS: + - 32 + - 64 + - 128 + - 256 + FUSE_METHOD: SUM +LOSS: + USE_TARGET_WEIGHT: true +TRAIN: + BATCH_SIZE_PER_GPU: 32 + SHUFFLE: true + BEGIN_EPOCH: 0 + END_EPOCH: 150 + OPTIMIZER: adam + LR: 0.001 + LR_FACTOR: 0.1 + LR_STEP: + - 170 + - 200 + WD: 0.0001 + GAMMA1: 0.99 + GAMMA2: 0.0 + MOMENTUM: 0.9 + NESTEROV: false +TEST: + BATCH_SIZE_PER_GPU: 32 + MODEL_FILE: '' + FLIP_TEST: true + POST_PROCESS: true + SHIFT_HEATMAP: true +DEBUG: + DEBUG: true + SAVE_BATCH_IMAGES_GT: true + SAVE_BATCH_IMAGES_PRED: true + SAVE_HEATMAPS_GT: true + SAVE_HEATMAPS_PRED: true diff --git a/lib/config/default.py b/lib/config/default.py index 72d3faf3..e851bb25 100644 --- a/lib/config/default.py +++ b/lib/config/default.py @@ -54,6 +54,7 @@ # DATASET related params _C.DATASET = CN() _C.DATASET.ROOT = '' +_C.DATASET.IMAGE_ROOT = '' _C.DATASET.DATASET = 'mpii' _C.DATASET.TRAIN_SET = 'train' _C.DATASET.TEST_SET = 'valid' @@ -137,6 +138,15 @@ def update_config(cfg, args): if args.dataDir: cfg.DATA_DIR = args.dataDir + if args.model_file: + cfg.TEST.MODEL_FILE = args.model_file + + if hasattr(args, "save_batch_images_gt"): + cfg.DEBUG.SAVE_BATCH_IMAGES_GT = args.save_batch_images_gt + + if hasattr(args, "save_heatmaps_gt"): + cfg.DEBUG.SAVE_HEATMAPS_GT = args.save_heatmaps_gt + cfg.DATASET.ROOT = os.path.join( cfg.DATA_DIR, cfg.DATASET.ROOT ) @@ -145,10 +155,10 @@ def update_config(cfg, args): cfg.DATA_DIR, cfg.MODEL.PRETRAINED ) - if cfg.TEST.MODEL_FILE: - cfg.TEST.MODEL_FILE = os.path.join( - cfg.DATA_DIR, cfg.TEST.MODEL_FILE - ) + # if cfg.TEST.MODEL_FILE: + # cfg.TEST.MODEL_FILE = os.path.join( + # cfg.DATA_DIR, cfg.TEST.MODEL_FILE + # ) cfg.freeze() diff --git a/lib/core/function.py b/lib/core/function.py index 1bc19daa..b9f2465f 100755 --- a/lib/core/function.py +++ b/lib/core/function.py @@ -18,14 +18,14 @@ from core.evaluate import accuracy from core.inference import get_final_preds from utils.transforms import flip_back -from utils.vis import save_debug_images +from utils.vis import save_batch_image_with_joints_separately, save_debug_images logger = logging.getLogger(__name__) def train(config, train_loader, model, criterion, optimizer, epoch, - output_dir, tb_log_dir, writer_dict): + output_dir, tb_log_dir, device, writer_dict=None): batch_time = AverageMeter() data_time = AverageMeter() losses = AverageMeter() @@ -35,15 +35,15 @@ def train(config, train_loader, model, criterion, optimizer, epoch, model.train() end = time.time() - for i, (input, target, target_weight, meta) in enumerate(train_loader): + for i, (image, target, target_weight, meta) in enumerate(train_loader): # measure data loading time data_time.update(time.time() - end) # compute output - outputs = model(input) + outputs = model(image) - target = target.cuda(non_blocking=True) - target_weight = target_weight.cuda(non_blocking=True) + target = target.to(device, non_blocking=True) + target_weight = target_weight.to(device, non_blocking=True) if isinstance(outputs, list): loss = criterion(outputs[0], target, target_weight) @@ -61,7 +61,7 @@ def train(config, train_loader, model, criterion, optimizer, epoch, optimizer.step() # measure accuracy and record loss - losses.update(loss.item(), input.size(0)) + losses.update(loss.item(), image.size(0)) _, avg_acc, cnt, pred = accuracy(output.detach().cpu().numpy(), target.detach().cpu().numpy()) @@ -79,23 +79,24 @@ def train(config, train_loader, model, criterion, optimizer, epoch, 'Loss {loss.val:.5f} ({loss.avg:.5f})\t' \ 'Accuracy {acc.val:.3f} ({acc.avg:.3f})'.format( epoch, i, len(train_loader), batch_time=batch_time, - speed=input.size(0)/batch_time.val, + speed=image.size(0)/batch_time.val, data_time=data_time, loss=losses, acc=acc) logger.info(msg) - writer = writer_dict['writer'] - global_steps = writer_dict['train_global_steps'] - writer.add_scalar('train_loss', losses.val, global_steps) - writer.add_scalar('train_acc', acc.val, global_steps) - writer_dict['train_global_steps'] = global_steps + 1 + if writer_dict: + writer = writer_dict['writer'] + global_steps = writer_dict['train_global_steps'] + writer.add_scalar('train_loss', losses.val, global_steps) + writer.add_scalar('train_acc', acc.val, global_steps) + writer_dict['train_global_steps'] = global_steps + 1 prefix = '{}_{}'.format(os.path.join(output_dir, 'train'), i) - save_debug_images(config, input, meta, target, pred*4, output, + save_debug_images(config, image, meta, target, pred*4, output, prefix) def validate(config, val_loader, val_dataset, model, criterion, output_dir, - tb_log_dir, writer_dict=None): + tb_log_dir, device, writer_dict=None): batch_time = AverageMeter() losses = AverageMeter() acc = AverageMeter() @@ -115,16 +116,16 @@ def validate(config, val_loader, val_dataset, model, criterion, output_dir, idx = 0 with torch.no_grad(): end = time.time() - for i, (input, target, target_weight, meta) in enumerate(val_loader): + for i, (image, target, target_weight, meta) in enumerate(val_loader): # compute output - outputs = model(input) + outputs = model(image) if isinstance(outputs, list): output = outputs[-1] else: output = outputs if config.TEST.FLIP_TEST: - input_flipped = input.flip(3) + input_flipped = image.flip(3) outputs_flipped = model(input_flipped) if isinstance(outputs_flipped, list): @@ -134,7 +135,7 @@ def validate(config, val_loader, val_dataset, model, criterion, output_dir, output_flipped = flip_back(output_flipped.cpu().numpy(), val_dataset.flip_pairs) - output_flipped = torch.from_numpy(output_flipped.copy()).cuda() + output_flipped = torch.from_numpy(output_flipped.copy()).to(device) # feature is not aligned, shift flipped heatmap for higher accuracy @@ -144,12 +145,12 @@ def validate(config, val_loader, val_dataset, model, criterion, output_dir, output = (output + output_flipped) * 0.5 - target = target.cuda(non_blocking=True) - target_weight = target_weight.cuda(non_blocking=True) + target = target.to(device, non_blocking=True) + target_weight = target_weight.to(device, non_blocking=True) loss = criterion(output, target, target_weight) - num_images = input.size(0) + num_images = image.size(0) # measure accuracy and record loss losses.update(loss.item(), num_images) _, avg_acc, cnt, pred = accuracy(output.cpu().numpy(), @@ -191,7 +192,7 @@ def validate(config, val_loader, val_dataset, model, criterion, output_dir, prefix = '{}_{}'.format( os.path.join(output_dir, 'val'), i ) - save_debug_images(config, input, meta, target, pred*4, output, + save_debug_images(config, image, meta, target, pred*4, output, prefix) name_values, perf_indicator = val_dataset.evaluate( @@ -237,6 +238,80 @@ def validate(config, val_loader, val_dataset, model, criterion, output_dir, return perf_indicator +def inference(config, val_loader, val_dataset, model, output_dir, device, save_dir): + batch_time = AverageMeter() + + # switch to evaluate mode + model.eval() + + num_samples = len(val_dataset) + all_preds = np.zeros( + (num_samples, config.MODEL.NUM_JOINTS, 3), + dtype=np.float32 + ) + image_path = [] + idx = 0 + with torch.no_grad(): + end = time.time() + for i, (image, meta) in enumerate(val_loader): + outputs = model(image) + if isinstance(outputs, list): + output = outputs[-1] + else: + output = outputs + + if config.TEST.FLIP_TEST: + input_flipped = image.flip(3) + outputs_flipped = model(input_flipped) + + if isinstance(outputs_flipped, list): + output_flipped = outputs_flipped[-1] + else: + output_flipped = outputs_flipped + + output_flipped = flip_back(output_flipped.cpu().numpy(), + val_dataset.flip_pairs) + output_flipped = torch.from_numpy(output_flipped.copy()).to(device) + + + # feature is not aligned, shift flipped heatmap for higher accuracy + if config.TEST.SHIFT_HEATMAP: + output_flipped[:, :, :, 1:] = \ + output_flipped.clone()[:, :, :, 0:-1] + + output = (output + output_flipped) * 0.5 + + num_images = image.size(0) + + # measure elapsed time + batch_time.update(time.time() - end) + end = time.time() + + preds, maxvals = get_final_preds( + config, output.clone().cpu().numpy(), center=None, scale=None) + + all_preds[idx:idx + num_images, :, 0:2] = preds[:, :, 0:2] + all_preds[idx:idx + num_images, :, 2:3] = maxvals + image_path.extend(meta['image_path']) + + + if i % config.PRINT_FREQ == 0: + msg = 'Test: [{0}/{1}]\t' \ + 'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'.format( + i, len(val_loader), batch_time=batch_time) + logger.info(msg) + prefix = '{}_{}'.format(os.path.join(output_dir, 'inference'), i) + save_debug_images(config, image, meta, None, preds*4, output, prefix) + + ### render predicted joints # 此部分放到主函数更好 + save_batch_image_with_joints_separately(image, preds*4, save_dir, idx, maxvals) + + idx += num_images + + return all_preds # TODO 由主函数解析并做可视化 + + + # markdown format output def _print_name_value(name_value, full_arch_name): names = name_value.keys() diff --git a/lib/core/inference.py b/lib/core/inference.py index ba2bac8f..21e4b775 100644 --- a/lib/core/inference.py +++ b/lib/core/inference.py @@ -71,9 +71,10 @@ def get_final_preds(config, batch_heatmaps, center, scale): preds = coords.copy() # Transform back - for i in range(coords.shape[0]): - preds[i] = transform_preds( - coords[i], center[i], scale[i], [heatmap_width, heatmap_height] - ) + if center and scale: + for i in range(coords.shape[0]): + preds[i] = transform_preds( + coords[i], center[i], scale[i], [heatmap_width, heatmap_height] + ) return preds, maxvals diff --git a/lib/dataset/__init__.py b/lib/dataset/__init__.py index 16e2413b..27766a40 100644 --- a/lib/dataset/__init__.py +++ b/lib/dataset/__init__.py @@ -8,5 +8,7 @@ from __future__ import division from __future__ import print_function -from .mpii import MPIIDataset as mpii -from .coco import COCODataset as coco +# from .mpii import MPIIDataset as mpii +# from .coco import COCODataset as coco +from .ak import AnimalKingdomDataset as ak +from .ak import AnimalKingdomDatasetInference as akinference diff --git a/lib/dataset/ak.py b/lib/dataset/ak.py new file mode 100644 index 00000000..2166b302 --- /dev/null +++ b/lib/dataset/ak.py @@ -0,0 +1,385 @@ +# ------------------------------------------------------------------------------ +# Copyright (c) Microsoft +# Licensed under the MIT License. +# Written by Bin Xiao (Bin.Xiao@microsoft.com) +# ------------------------------------------------------------------------------ + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function +import math +import logging +import os +import json_tricks as json +from collections import OrderedDict +import json +import numpy as np +import cv2 +from pathlib import Path +from scipy.io import loadmat, savemat + +from dataset.JointsDataset import JointsDataset +from utils.transforms import get_affine_transform + + +logger = logging.getLogger(__name__) + + +class AnimalKingdomDataset(JointsDataset): + def __init__(self, cfg, root, image_set, is_train, img_root=None, transform=None): + super().__init__(cfg, root, image_set, is_train, transform) + ''' + 0: Head_Mid_Top + 1: Eye_Left + 2: Eye_Right + 3: Mouth_Front_Top + 4: Mouth_Back_Left + 5: Mouth_Back_Right + 6: Mouth_Front_Bottom + 7: Shoulder_Left + 8: Shoulder_Right + 9: Elbow_Left + 10: Elbow_Right + 11: Wrist_Left + 12: Wrist_Right + 13: Torso_Mid_Back + 14: Hip_Left + 15: Hip_Right + 16: Knee_Left + 17: Knee_Right + 18: Ankle_Left + 19: Ankle_Right + 20: Tail_Top_Back + 21: Tail_Mid_Back + 22: Tail_End_Back + ''' + ### Changes below ### + self.num_joints = 23 + self.flip_pairs = [[1, 2], [4, 5], [7, 8], [9, 10], [11, 12], [14,15], [16,17], [18,19]] + self.parent_ids = [3,3,3,6,6,6,13,13,13,7,8,9,10,13,13,13,14,15,16,17,12,20,21] + + self.upper_body_ids = (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13) + self.lower_body_ids = (14, 15, 16, 17, 18, 19, 20, 21, 22) + self.img_root = img_root + + self.db = self._get_db() + + if is_train and cfg.DATASET.SELECT_DATA: + self.db = self.select_data(self.db) + + logger.info('=> load {} samples'.format(len(self.db))) + + def _get_db(self): + # Create train/val split + file_name = os.path.join( + self.root, 'annot', self.image_set+'.json' + ) + with open(file_name) as anno_file: + anno = json.load(anno_file) + + gt_db = [] + for a in anno: + image_name = a['image'] + + c = np.array(a['center'], dtype=np.float) + s = np.array([a['scale'], a['scale']], dtype=np.float) + + # Adjust center/scale slightly to avoid cropping limbs + if c[0] != -1: + # c[1] = c[1] + 15 * s[1] + s = s * 1.25 + + # MPII uses matlab format, index is based 1, + # # we should first convert to 0-based index + # c = c - 1 + + joints_3d = np.zeros((self.num_joints, 3), dtype=np.float) + joints_3d_vis = np.zeros((self.num_joints, 3), dtype=np.float) + if self.image_set != 'test': + joints = np.array(a['joints']) + joints[:, 0:2] = joints[:, 0:2] + joints_vis = np.array(a['joints_vis']) + assert len(joints) == self.num_joints, \ + 'joint num diff: {} vs {}'.format(len(joints), + self.num_joints) + + joints_3d[:, 0:2] = joints[:, 0:2] + joints_3d_vis[:, 0] = joints_vis[:] + joints_3d_vis[:, 1] = joints_vis[:] + + # image_dir = 'images.zip@' if self.data_format == 'zip' else 'images' + gt_db.append( + { + 'image': os.path.join(self.img_root, image_name), + 'center': c, + 'scale': s, + 'joints_3d': joints_3d, + 'joints_3d_vis': joints_3d_vis, + 'filename': '', + 'imgnum': 0, + } + ) + + return gt_db + + def evaluate(self, cfg, preds, output_dir, *args, **kwargs): + # Convert 0-based index to 1-based index + preds = preds[:, :, 0:2] + 1.0 + + if output_dir: + pred_file = os.path.join(output_dir, 'pred.mat') + savemat(pred_file, mdict={'preds': preds}) + + # if 'test' in cfg.DATASET.TEST_SET: + # return {'Null': 0.0}, 0.0 + + SC_BIAS = 1 + threshold = 0.1 + + gt_file = os.path.join(cfg.DATASET.ROOT, + 'annot', + '{}.json' #gt_{}.json' + .format(cfg.DATASET.TEST_SET) + ) + + + with open(gt_file) as f: + gt_dict = json.load(f) + + ### Changes below ### + + # dataset_joints = gt_dict['dataset_joints'] + # jnt_visible = [v for k, v in gt_dict['joints_vis'].items()] + # pos_gt_src = [v for k, v in gt_dict['joints'].items()] + # scale = [v for k, v in gt_dict['scale'].items()] + + dataset_joints = [ + [ + "Head_Mid_Top" + ], + [ + "Eye_Left" + ], + [ + "Eye_Right" + ], + [ + "Mouth_Front_Top" + ], + [ + "Mouth_Back_Left" + ], + [ + "Mouth_Back_Right" + ], + [ + "Mouth_Front_Bottom" + ], + [ + "Shoulder_Left" + ], + [ + "Shoulder_Right" + ], + [ + "Elbow_Left" + ], + [ + "Elbow_Right" + ], + [ + "Wrist_Left" + ], + [ + "Wrist_Right" + ], + [ + "Torso_Mid_Back" + ], + [ + "Hip_Left" + ], + [ + "Hip_Right" + ], + [ + "Knee_Left" + ], + [ + "Knee_Right" + ], + [ + "Ankle_Left" + ], + [ + "Ankle_Right" + ], + [ + "Tail_Top_Back" + ], + [ + "Tail_Mid_Back" + ], + [ + "Tail_End_Back" + ] + ] + + jnt_visible = [x['joints_vis'] for x in gt_dict] + pos_gt_src = [x['joints'] for x in gt_dict] + scale = [x['scale'] for x in gt_dict] + + scale=np.array(scale) + scale=scale*200*math.sqrt(2) + + jnt_visible=np.transpose(jnt_visible, [1, 0]) + pos_pred_src = np.transpose(preds, [1, 2, 0]) + pos_gt_src=np.transpose(pos_gt_src, [1, 2, 0]) + dataset_joints=np.array(dataset_joints) + head = np.where(dataset_joints == 'Head_Mid_Top')[0][0] + lsho = np.where(dataset_joints == 'Shoulder_Left')[0][0] + lelb = np.where(dataset_joints == 'Elbow_Left')[0][0] + lwri = np.where(dataset_joints == 'Wrist_Left')[0][0] + lhip = np.where(dataset_joints == 'Hip_Left')[0][0] + lkne = np.where(dataset_joints == 'Knee_Left')[0][0] + lank = np.where(dataset_joints == 'Ankle_Left')[0][0] + + rsho = np.where(dataset_joints == 'Shoulder_Right')[0][0] + relb = np.where(dataset_joints == 'Elbow_Right')[0][0] + rwri = np.where(dataset_joints == 'Wrist_Right')[0][0] + rhip = np.where(dataset_joints == 'Hip_Right')[0][0] + rkne = np.where(dataset_joints == 'Knee_Right')[0][0] + rank = np.where(dataset_joints == 'Ankle_Right')[0][0] + + tmouth = np.where(dataset_joints == 'Mouth_Front_Top')[0][0] + lmouth = np.where(dataset_joints == 'Mouth_Back_Left')[0][0] + rmouth = np.where(dataset_joints == 'Mouth_Back_Right')[0][0] + bmouth = np.where(dataset_joints == 'Mouth_Front_Bottom')[0][0] + ttail = np.where(dataset_joints == 'Tail_Top_Back')[0][0] + mtail = np.where(dataset_joints == 'Tail_Mid_Back')[0][0] + btail = np.where(dataset_joints == 'Tail_End_Back')[0][0] + + + uv_error = pos_pred_src - pos_gt_src + + uv_err = np.linalg.norm(uv_error, axis=1) + + # headsizes = headboxes_src[1, :, :] - headboxes_src[0, :, :] + # headsizes = np.linalg.norm(headsizes, axis=0) + scale *= SC_BIAS + headsizes=scale + + + scale = np.multiply(headsizes, np.ones((len(uv_err), 1))) + scaled_uv_err = np.divide(uv_err, scale) + scaled_uv_err = np.multiply(scaled_uv_err, jnt_visible) + jnt_count = np.sum(jnt_visible, axis=1) + + less_than_threshold = np.multiply((scaled_uv_err <= threshold), + jnt_visible) + PCKh = np.divide(100.*np.sum(less_than_threshold, axis=1), jnt_count) + # save + rng = np.arange(0, 0.5+0.01, 0.01) + pckAll = np.zeros((len(rng), 23)) + + for r in range(len(rng)): + threshold = rng[r] + less_than_threshold = np.multiply(scaled_uv_err <= threshold, + jnt_visible) + pckAll[r, :] = np.divide(100.*np.sum(less_than_threshold, axis=1), + jnt_count) + + # PCKh = np.ma.array(PCKh, mask=False) + # PCKh.mask[21:22] = True + + # jnt_count = np.ma.array(jnt_count, mask=False) + # jnt_count.mask[21:22] = True + + jnt_ratio = jnt_count / np.sum(jnt_count).astype(np.float64) + name_value = [ + ('Head', PCKh[head]), + ('Shoulder', 0.5 * (PCKh[lsho] + PCKh[rsho])), + ('Elbow', 0.5 * (PCKh[lelb] + PCKh[relb])), + ('Wrist', 0.5 * (PCKh[lwri] + PCKh[rwri])), + ('Hip', 0.5 * (PCKh[lhip] + PCKh[rhip])), + ('Knee', 0.5 * (PCKh[lkne] + PCKh[rkne])), + ('Ankle', 0.5 * (PCKh[lank] + PCKh[rank])), + ('Mouth', 0.25 * (PCKh[tmouth] + PCKh[lmouth]+ PCKh[rmouth]+ PCKh[bmouth])), + ('Tail', (PCKh[ttail] + PCKh[mtail]+ PCKh[btail])/3), + ('Mean', np.sum(PCKh * jnt_ratio)) + # ('Mean@0.1', np.sum(pckAll[11, :] * jnt_ratio)) + ] + name_value = OrderedDict(name_value) + return name_value, name_value['Mean'] + + +class AnimalKingdomDatasetInference(object): + + def __init__(self, cfg, video_path, transform=None, frame_root="extracted_frames"): + self.num_joints = 23 + self.flip_pairs = [[1, 2], [4, 5], [7, 8], [9, 10], [11, 12], [14,15], [16,17], [18,19]] + self.video_path = video_path + self.color_rgb = cfg.DATASET.COLOR_RGB + self.transform = transform + self.frame_root = frame_root + self.frame_dir = os.path.join(self.frame_root, Path(self.video_path).stem) + self.db = self._get_db() + + def _get_db(self): + """ extract frames from mp4 video file + """ + db = [] + logger.info("load video: {}".format(self.video_path)) + cap = cv2.VideoCapture(self.video_path) + frame_total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) + + if os.path.exists(self.frame_dir) and len(os.listdir(self.frame_dir)) == frame_total: + for frame_idx, filename in enumerate(os.listdir(self.frame_dir)): + print("find frames: {}/{}".format(frame_idx+1, frame_total), end="\r") + db.append({ + 'image_path': os.path.join(self.frame_dir, filename), + "image_name": filename + }) + print("find frames: {}/{}".format(frame_idx+1, frame_total)) + else: + os.makedirs(self.frame_dir, exist_ok=True) + frame_idx = 0 + while cap.isOpened(): + ok, frame = cap.read() # BGR + if not ok: + break + print("extract frames: {}/{}".format(frame_idx+1, frame_total), end="\r") + frame_path = os.path.join(self.frame_dir, "{}.png".format(frame_idx)) + cv2.imwrite(frame_path, frame) + db.append({ + 'image_path': frame_path, + "image_name": "{}.png".format(frame_idx) + }) + frame_idx += 1 + print("extract frames: {}/{}".format(frame_idx+1, frame_total)) + return db + + def __len__(self,): + return len(self.db) + + def __getitem__(self, idx): + + image_path, image_name = self.db[idx]['image_path'], self.db[idx]['image_name'] + + data_numpy = cv2.imread(image_path, cv2.IMREAD_COLOR | cv2.IMREAD_IGNORE_ORIENTATION) + if self.color_rgb: + data_numpy = cv2.cvtColor(data_numpy, cv2.COLOR_BGR2RGB) + if data_numpy is None: + logger.error('=> fail to read {}'.format(image_path)) + raise ValueError('Fail to read {}'.format(image_path)) + + if self.transform: + image = self.transform(data_numpy) + + meta = { + 'image_path': image_path, + 'image_name': image_name, + "joints_vis": np.ones((self.num_joints, 1)) + } + + return image, meta diff --git a/lib/description-pak b/lib/description-pak new file mode 100644 index 00000000..1c8e4235 --- /dev/null +++ b/lib/description-pak @@ -0,0 +1 @@ +Package created with checkinstall 1.6.3 diff --git a/lib/nms/cpu_nms.c b/lib/nms/cpu_nms.c new file mode 100644 index 00000000..2ccd9729 --- /dev/null +++ b/lib/nms/cpu_nms.c @@ -0,0 +1,7697 @@ +/* Generated by Cython 0.29.30 */ + +#ifndef PY_SSIZE_T_CLEAN +#define PY_SSIZE_T_CLEAN +#endif /* PY_SSIZE_T_CLEAN */ +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_30" +#define CYTHON_HEX_VERSION 0x001D1EF0 +#define CYTHON_FUTURE_DIVISION 1 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef 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(PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #if PY_VERSION_HEX >= 0x030B00A4 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 + #elif !defined(CYTHON_USE_EXC_INFO_STACK) + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif + #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC + #define CYTHON_UPDATE_DESCRIPTOR_DOC 1 + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #if PY_MAJOR_VERSION < 3 + #include "longintrepr.h" + #endif + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #elif defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" + #define __Pyx_DefaultClassType PyType_Type +#if PY_VERSION_HEX >= 0x030B00A1 + static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f, + PyObject *code, PyObject *c, PyObject* n, PyObject *v, + PyObject *fv, PyObject *cell, PyObject* fn, + PyObject *name, int fline, PyObject *lnos) { + PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL; + PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL; + const char *fn_cstr=NULL; + const char *name_cstr=NULL; + PyCodeObject* co=NULL; + PyObject *type, *value, *traceback; + PyErr_Fetch(&type, &value, &traceback); + if (!(kwds=PyDict_New())) goto end; + if (!(argcount=PyLong_FromLong(a))) goto end; + if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end; + if (!(posonlyargcount=PyLong_FromLong(0))) goto end; + if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end; + if (!(kwonlyargcount=PyLong_FromLong(k))) goto end; + if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end; + if (!(nlocals=PyLong_FromLong(l))) goto end; + if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end; + if (!(stacksize=PyLong_FromLong(s))) goto end; + if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end; + if (!(flags=PyLong_FromLong(f))) goto end; + if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end; + if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end; + if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end; + if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end; + if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too; + if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here + if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too; + Py_XDECREF((PyObject*)co); + co = (PyCodeObject*)call_result; + call_result = NULL; + if (0) { + cleanup_code_too: + Py_XDECREF((PyObject*)co); + co = NULL; + } + end: + Py_XDECREF(kwds); + Py_XDECREF(argcount); + Py_XDECREF(posonlyargcount); + Py_XDECREF(kwonlyargcount); + Py_XDECREF(nlocals); + Py_XDECREF(stacksize); + Py_XDECREF(replace); + Py_XDECREF(call_result); + Py_XDECREF(empty); + if (type) { + PyErr_Restore(type, value, traceback); + } + return co; + } +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #if defined(PyUnicode_IS_READY) + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #else + #define __Pyx_PyUnicode_READY(op) (0) + #endif + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000 + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length)) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #endif + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsHash_t +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(_WIN32) || defined(WIN32) || defined(MS_WINDOWS) + #if !defined(_USE_MATH_DEFINES) + #define _USE_MATH_DEFINES + #endif +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__cpu_nms +#define __PYX_HAVE_API__cpu_nms +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "cpu_nms.pyx", + "__init__.pxd", + "type.pxd", +}; +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; +#endif +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + + +/*--- Type declarations ---*/ + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":728 + * ctypedef npy_longdouble longdouble_t + * + * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t + */ +typedef npy_cfloat __pyx_t_5numpy_cfloat_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":729 + * + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< + * ctypedef npy_clongdouble clongdouble_t + * + */ +typedef npy_cdouble __pyx_t_5numpy_cdouble_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":730 + * ctypedef npy_cfloat cfloat_t + * ctypedef npy_cdouble cdouble_t + * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cdouble complex_t + */ +typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":732 + * ctypedef npy_clongdouble clongdouble_t + * + * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< + * + * cdef inline object PyArray_MultiIterNew1(a): + */ +typedef npy_cdouble __pyx_t_5numpy_complex_t; 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r = NULL; __Pyx_DECREF(tmp);}} while(0) + +/* PyObjectGetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +#endif + +/* GetBuiltinName.proto */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name); + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); 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(PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* PyIntBinop.proto */ +#if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace, int zerodivision_check); +#else +#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace, zerodivision_check)\ + (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif +#if CYTHON_FAST_PYCALL + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" +#if PY_VERSION_HEX >= 0x030b00a6 + #ifndef Py_BUILD_CORE + #define Py_BUILD_CORE 1 + #endif + #include "internal/pycore_frame.h" +#endif + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif // CYTHON_FAST_PYCALL +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* BufferIndexError.proto */ +static void __Pyx_RaiseBufferIndexError(int axis); + +#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) +/* ListAppend.proto */ +#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS +static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { + PyListObject* L = (PyListObject*) list; + Py_ssize_t len = Py_SIZE(list); + if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { + Py_INCREF(x); + PyList_SET_ITEM(list, len, x); + __Pyx_SET_SIZE(list, len + 1); + return 0; + } + return PyList_Append(list, x); +} +#else +#define __Pyx_PyList_Append(L,x) PyList_Append(L,x) +#endif + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; + +/* Module declarations from 'cpu_nms' */ +static CYTHON_INLINE __pyx_t_5numpy_float32_t __pyx_f_7cpu_nms_max(__pyx_t_5numpy_float32_t, __pyx_t_5numpy_float32_t); /*proto*/ +static CYTHON_INLINE __pyx_t_5numpy_float32_t __pyx_f_7cpu_nms_min(__pyx_t_5numpy_float32_t, __pyx_t_5numpy_float32_t); /*proto*/ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t = { "float32_t", NULL, sizeof(__pyx_t_5numpy_float32_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_int_t = { "int_t", NULL, sizeof(__pyx_t_5numpy_int_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5numpy_int_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5numpy_int_t), 0 }; +#define __Pyx_MODULE_NAME "cpu_nms" +extern int __pyx_module_is_main_cpu_nms; +int __pyx_module_is_main_cpu_nms = 0; + +/* Implementation of 'cpu_nms' */ +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_ImportError; +static const char __pyx_k_h[] = "h"; +static const char __pyx_k_i[] = "i"; +static const char __pyx_k_j[] = "_j"; +static const char __pyx_k_w[] = "w"; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_x1[] = "x1"; +static const char __pyx_k_x2[] = "x2"; +static const char __pyx_k_y1[] = "y1"; +static const char __pyx_k_y2[] = "y2"; +static const char __pyx_k_i_2[] = "_i"; +static const char __pyx_k_int[] = "int"; +static const char __pyx_k_ix1[] = "ix1"; +static const char __pyx_k_ix2[] = "ix2"; +static const char __pyx_k_iy1[] = "iy1"; +static const char __pyx_k_iy2[] = "iy2"; +static const char __pyx_k_j_2[] = "j"; +static const char __pyx_k_ovr[] = "ovr"; +static const char __pyx_k_xx1[] = "xx1"; +static const char __pyx_k_xx2[] = "xx2"; +static const char __pyx_k_yy1[] = "yy1"; +static const char __pyx_k_yy2[] = "yy2"; +static const char __pyx_k_dets[] = "dets"; +static const char __pyx_k_keep[] = "keep"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_name[] = "__name__"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_areas[] = "areas"; +static const char __pyx_k_dtype[] = "dtype"; +static const char __pyx_k_iarea[] = "iarea"; +static const char __pyx_k_inter[] = "inter"; +static const char __pyx_k_ndets[] = "ndets"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_order[] = "order"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_zeros[] = "zeros"; +static const char __pyx_k_astype[] = "astype"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_scores[] = "scores"; +static const char __pyx_k_thresh[] = "thresh"; +static const char __pyx_k_argsort[] = "argsort"; +static const char __pyx_k_cpu_nms[] = "cpu_nms"; +static const char __pyx_k_suppressed[] = "suppressed"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_cpu_nms_pyx[] = "cpu_nms.pyx"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_n_s_areas; +static PyObject *__pyx_n_s_argsort; +static PyObject *__pyx_n_s_astype; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_n_s_cpu_nms; +static PyObject *__pyx_kp_s_cpu_nms_pyx; +static PyObject *__pyx_n_s_dets; +static PyObject *__pyx_n_s_dtype; +static PyObject *__pyx_n_s_h; +static PyObject *__pyx_n_s_i; +static PyObject *__pyx_n_s_i_2; +static PyObject *__pyx_n_s_iarea; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_int; +static PyObject *__pyx_n_s_inter; +static PyObject *__pyx_n_s_ix1; +static PyObject *__pyx_n_s_ix2; +static PyObject *__pyx_n_s_iy1; +static PyObject *__pyx_n_s_iy2; +static PyObject *__pyx_n_s_j; +static PyObject *__pyx_n_s_j_2; +static PyObject *__pyx_n_s_keep; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_ndets; +static PyObject *__pyx_n_s_np; +static PyObject *__pyx_n_s_numpy; +static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_order; +static PyObject *__pyx_n_s_ovr; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_scores; +static PyObject *__pyx_n_s_suppressed; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_n_s_thresh; +static PyObject *__pyx_n_s_w; +static PyObject *__pyx_n_s_x1; +static PyObject *__pyx_n_s_x2; +static PyObject *__pyx_n_s_xx1; +static PyObject *__pyx_n_s_xx2; 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+ if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* IsLittleEndian */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* BufferGetAndValidate */ + static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (unlikely(info->buf == NULL)) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} +static void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static int __Pyx__GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + buf->buf = NULL; + if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { + __Pyx_ZeroBuffer(buf); + return -1; + } + if (unlikely(buf->ndim != nd)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if (unlikely((size_t)buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_SafeReleaseBuffer(buf); + return -1; +} + +/* GetItemInt */ + static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ + #if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* ExtTypeTest */ + static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* PyIntBinop */ + #if !CYTHON_COMPILING_IN_PYPY +static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, int inplace, int zerodivision_check) { + (void)inplace; + (void)zerodivision_check; + #if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(op1))) { + const long b = intval; + long x; + long a = PyInt_AS_LONG(op1); + x = (long)((unsigned long)a + b); + if (likely((x^a) >= 0 || (x^b) >= 0)) + return PyInt_FromLong(x); + return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + #endif + #if CYTHON_USE_PYLONG_INTERNALS + if (likely(PyLong_CheckExact(op1))) { + const long b = intval; + long a, x; +#ifdef HAVE_LONG_LONG + const PY_LONG_LONG llb = intval; + PY_LONG_LONG lla, llx; +#endif + const digit* digits = ((PyLongObject*)op1)->ob_digit; + const Py_ssize_t size = Py_SIZE(op1); + if (likely(__Pyx_sst_abs(size) <= 1)) { + a = likely(size) ? digits[0] : 0; + if (size == -1) a = -a; + } else { + switch (size) { + case -2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 2: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 3: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case -4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + case 4: + if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); + break; +#ifdef HAVE_LONG_LONG + } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { + lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); + goto long_long; +#endif + } + CYTHON_FALLTHROUGH; + default: return PyLong_Type.tp_as_number->nb_add(op1, op2); + } + } + x = a + b; + return PyLong_FromLong(x); +#ifdef HAVE_LONG_LONG + long_long: + llx = lla + llb; + return PyLong_FromLongLong(llx); +#endif + + + } + #endif + if (PyFloat_CheckExact(op1)) { + const long b = intval; + double a = PyFloat_AS_DOUBLE(op1); + double result; + PyFPE_START_PROTECT("add", return NULL) + result = ((double)a) + (double)b; + PyFPE_END_PROTECT(result) + return PyFloat_FromDouble(result); + } + return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); +} +#endif + +/* PyFunctionFastCall */ + #if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCall */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = Py_TYPE(func)->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallMethO */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallNoArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* PyCFunctionFastCall */ + #if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyObjectCallOneArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyObjectCall2Args */ + static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ + #if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* BufferIndexError */ + static void __Pyx_RaiseBufferIndexError(int axis) { + PyErr_Format(PyExc_IndexError, + "Out of bounds on buffer access (axis %d)", axis); +} + +/* PyErrFetchRestore */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* RaiseException */ + #if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +#if PY_VERSION_HEX >= 0x030b00a6 + #ifndef Py_BUILD_CORE + #define Py_BUILD_CORE 1 + #endif + #include "internal/pycore_frame.h" +#endif +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = NULL; + PyObject *py_funcname = NULL; + #if PY_MAJOR_VERSION < 3 + PyObject *py_srcfile = NULL; + py_srcfile = PyString_FromString(filename); + if (!py_srcfile) goto bad; + #endif + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + funcname = PyUnicode_AsUTF8(py_funcname); + if (!funcname) goto bad; + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + if (!py_funcname) goto bad; + #endif + } + #if PY_MAJOR_VERSION < 3 + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + #else + py_code = PyCode_NewEmpty(filename, funcname, py_line); + #endif + Py_XDECREF(py_funcname); // XDECREF since it's only set on Py3 if cline + return py_code; +bad: + Py_XDECREF(py_funcname); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_srcfile); + #endif + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject *ptype, *pvalue, *ptraceback; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) { + /* If the code object creation fails, then we should clear the + fetched exception references and propagate the new exception */ + Py_XDECREF(ptype); + Py_XDECREF(pvalue); + Py_XDECREF(ptraceback); + goto bad; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i '9'); + break; + } + if (rt_from_call[i] != ctversion[i]) { + same = 0; + break; + } + } + if (!same) { + char rtversion[5] = {'\0'}; + char message[200]; + for (i=0; i<4; ++i) { + if (rt_from_call[i] == '.') { + if (found_dot) break; + found_dot = 1; + } else if (rt_from_call[i] < '0' || rt_from_call[i] > '9') { + break; + } + rtversion[i] = rt_from_call[i]; + } + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* InitStrings */ + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) { + if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) { + return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o); +#if PY_MAJOR_VERSION < 3 + } else if (likely(PyInt_CheckExact(o))) { + return PyInt_AS_LONG(o); +#endif + } else { + Py_ssize_t ival; + PyObject *x; + x = PyNumber_Index(o); + if (!x) return -1; + ival = PyInt_AsLong(x); + Py_DECREF(x); + return ival; + } +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/lib/nms/cpu_nms.cpython-36m-x86_64-linux-gnu.so b/lib/nms/cpu_nms.cpython-36m-x86_64-linux-gnu.so new file mode 100644 index 00000000..4d7ab49e Binary files /dev/null and b/lib/nms/cpu_nms.cpython-36m-x86_64-linux-gnu.so differ diff --git a/lib/nms/cpu_nms.cpython-39-x86_64-linux-gnu.so b/lib/nms/cpu_nms.cpython-39-x86_64-linux-gnu.so new file mode 100644 index 00000000..84aa023e Binary files /dev/null and b/lib/nms/cpu_nms.cpython-39-x86_64-linux-gnu.so differ diff --git a/lib/nms/gpu_nms.cpp b/lib/nms/gpu_nms.cpp new file mode 100644 index 00000000..5cfbe5c0 --- /dev/null +++ b/lib/nms/gpu_nms.cpp @@ -0,0 +1,7102 @@ +/* Generated by Cython 0.29.30 */ + +#ifndef PY_SSIZE_T_CLEAN +#define PY_SSIZE_T_CLEAN +#endif /* PY_SSIZE_T_CLEAN */ +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_30" +#define CYTHON_HEX_VERSION 0x001D1EF0 +#define CYTHON_FUTURE_DIVISION 1 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define CYTHON_COMPILING_IN_PYPY 1 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #undef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 0 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #if PY_VERSION_HEX < 0x03050000 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #undef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #undef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 1 + #undef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 0 + #undef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 0 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 + #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC + #define CYTHON_UPDATE_DESCRIPTOR_DOC (PYPY_VERSION_HEX >= 0x07030900) + #endif +#elif defined(PYSTON_VERSION) + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 1 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 + #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC + #define CYTHON_UPDATE_DESCRIPTOR_DOC 0 + #endif +#else + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 1 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) + #define CYTHON_USE_PYTYPE_LOOKUP 1 + #endif + #if PY_MAJOR_VERSION < 3 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #elif !defined(CYTHON_USE_PYLONG_INTERNALS) + #define CYTHON_USE_PYLONG_INTERNALS 1 + #endif + #ifndef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 1 + #endif + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #elif !defined(CYTHON_USE_UNICODE_WRITER) + #define CYTHON_USE_UNICODE_WRITER 1 + #endif + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #if PY_VERSION_HEX >= 0x030B00A4 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #elif !defined(CYTHON_FAST_THREAD_STATE) + #define CYTHON_FAST_THREAD_STATE 1 + #endif + #ifndef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030A0000) + #endif + #ifndef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) + #endif + #ifndef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #if PY_VERSION_HEX >= 0x030B00A4 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 + #elif !defined(CYTHON_USE_EXC_INFO_STACK) + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif + #ifndef CYTHON_UPDATE_DESCRIPTOR_DOC + #define CYTHON_UPDATE_DESCRIPTOR_DOC 1 + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #if PY_MAJOR_VERSION < 3 + #include "longintrepr.h" + #endif + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef __cplusplus + #error "Cython files generated with the C++ option must be compiled with a C++ compiler." +#endif +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #else + #define CYTHON_INLINE inline + #endif +#endif +template +void __Pyx_call_destructor(T& x) { + x.~T(); +} +template +class __Pyx_FakeReference { + public: + __Pyx_FakeReference() : ptr(NULL) { } + __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } + T *operator->() { return ptr; } + T *operator&() { return ptr; } + operator T&() { return *ptr; } + template bool operator ==(U other) { return *ptr == other; } + template bool operator !=(U other) { return *ptr != other; } + private: + T *ptr; +}; + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" + #define __Pyx_DefaultClassType PyType_Type +#if PY_VERSION_HEX >= 0x030B00A1 + static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f, + PyObject *code, PyObject *c, PyObject* n, PyObject *v, + PyObject *fv, PyObject *cell, PyObject* fn, + PyObject *name, int fline, PyObject *lnos) { + PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL; + PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL; + const char *fn_cstr=NULL; + const char *name_cstr=NULL; + PyCodeObject* co=NULL; + PyObject *type, *value, *traceback; + PyErr_Fetch(&type, &value, &traceback); + if (!(kwds=PyDict_New())) goto end; + if (!(argcount=PyLong_FromLong(a))) goto end; + if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end; + if (!(posonlyargcount=PyLong_FromLong(0))) goto end; + if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end; + if (!(kwonlyargcount=PyLong_FromLong(k))) goto end; + if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end; + if (!(nlocals=PyLong_FromLong(l))) goto end; + if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end; + if (!(stacksize=PyLong_FromLong(s))) goto end; + if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end; + if (!(flags=PyLong_FromLong(f))) goto end; + if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end; + if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end; + if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end; + if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end; + if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too; + if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here + if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too; + Py_XDECREF((PyObject*)co); + co = (PyCodeObject*)call_result; + call_result = NULL; + if (0) { + cleanup_code_too: + Py_XDECREF((PyObject*)co); + co = NULL; + } + end: + Py_XDECREF(kwds); + Py_XDECREF(argcount); + Py_XDECREF(posonlyargcount); + Py_XDECREF(kwonlyargcount); + Py_XDECREF(nlocals); + Py_XDECREF(stacksize); + Py_XDECREF(replace); + Py_XDECREF(call_result); + Py_XDECREF(empty); + if (type) { + PyErr_Restore(type, value, traceback); + } + return co; + } +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #if defined(PyUnicode_IS_READY) + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #else + #define __Pyx_PyUnicode_READY(op) (0) + #endif + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000 + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length)) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #endif + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsHash_t +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(_WIN32) || defined(WIN32) || defined(MS_WINDOWS) + #if !defined(_USE_MATH_DEFINES) + #define _USE_MATH_DEFINES + #endif +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__gpu_nms +#define __PYX_HAVE_API__gpu_nms +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include "gpu_nms.hpp" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "gpu_nms.pyx", + "__init__.pxd", + "type.pxd", +}; +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../../../../anaconda3/envs/pose/lib/python3.6/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; 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r = NULL; __Pyx_DECREF(tmp);}} while(0) + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* IsLittleEndian.proto */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); + +/* BufferFormatCheck.proto */ +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); 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+#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif +#if CYTHON_FAST_PYCALL + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" +#if PY_VERSION_HEX >= 0x030b00a6 + #ifndef Py_BUILD_CORE + #define Py_BUILD_CORE 1 + #endif + #include "internal/pycore_frame.h" +#endif + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif // CYTHON_FAST_PYCALL +#endif + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* BufferIndexError.proto */ +static void __Pyx_RaiseBufferIndexError(int axis); + +#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) +#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) +/* BufferFallbackError.proto */ +static void __Pyx_RaiseBufferFallbackError(void); + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* CIntFromPy.proto */ +static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; + +/* Module declarations from 'gpu_nms' */ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t = { "float32_t", NULL, sizeof(__pyx_t_5numpy_float32_t), { 0 }, 0, 'R', 0, 0 }; +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_int32_t = { "int32_t", NULL, sizeof(__pyx_t_5numpy_int32_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5numpy_int32_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5numpy_int32_t), 0 }; +#define __Pyx_MODULE_NAME "gpu_nms" +extern int __pyx_module_is_main_gpu_nms; +int __pyx_module_is_main_gpu_nms = 0; + +/* Implementation of 'gpu_nms' */ +static PyObject *__pyx_builtin_ImportError; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_dets[] = "dets"; +static const char __pyx_k_keep[] = "keep"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_name[] = "__name__"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_dtype[] = "dtype"; +static const char __pyx_k_int32[] = "int32"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_order[] = "order"; +static const char __pyx_k_zeros[] = "zeros"; +static const char __pyx_k_astype[] = "astype"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_scores[] = "scores"; +static const char __pyx_k_thresh[] = "thresh"; +static const char __pyx_k_argsort[] = "argsort"; +static const char __pyx_k_gpu_nms[] = "gpu_nms"; +static const char __pyx_k_num_out[] = "num_out"; +static const char __pyx_k_boxes_dim[] = "boxes_dim"; +static const char __pyx_k_boxes_num[] = "boxes_num"; +static const char __pyx_k_device_id[] = "device_id"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_gpu_nms_pyx[] = "gpu_nms.pyx"; +static const char __pyx_k_sorted_dets[] = "sorted_dets"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_n_s_argsort; +static PyObject *__pyx_n_s_astype; +static PyObject *__pyx_n_s_boxes_dim; +static PyObject *__pyx_n_s_boxes_num; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_n_s_dets; +static PyObject *__pyx_n_s_device_id; 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+ more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* IsLittleEndian */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* BufferGetAndValidate */ + static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (unlikely(info->buf == NULL)) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} +static void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static int __Pyx__GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + buf->buf = NULL; + if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { + __Pyx_ZeroBuffer(buf); + return -1; + } + if (unlikely(buf->ndim != nd)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if (unlikely((size_t)buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_SafeReleaseBuffer(buf); + return -1; +} + +/* PyObjectGetAttrStr */ + #if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro)) + return tp->tp_getattro(obj, attr_name); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_getattr)) + return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); +#endif + return PyObject_GetAttr(obj, attr_name); +} +#endif + +/* GetBuiltinName */ + static PyObject *__Pyx_GetBuiltinName(PyObject *name) { + PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); + if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + +/* PyDictVersioning */ + #if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ + #if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* PyObjectCall */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = Py_TYPE(func)->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* ExtTypeTest */ + static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* GetItemInt */ + static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ + #if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* PyFunctionFastCall */ + #if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCallMethO */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallNoArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* PyCFunctionFastCall */ + #if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyObjectCallOneArg */ + #if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyObjectCall2Args */ + static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* BufferIndexError */ + static void __Pyx_RaiseBufferIndexError(int axis) { + PyErr_Format(PyExc_IndexError, + "Out of bounds on buffer access (axis %d)", axis); +} + +/* BufferFallbackError */ + static void __Pyx_RaiseBufferFallbackError(void) { + PyErr_SetString(PyExc_ValueError, + "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); +} + +/* PyErrFetchRestore */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* RaiseException */ + #if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +#if PY_VERSION_HEX >= 0x030b00a6 + #ifndef Py_BUILD_CORE + #define Py_BUILD_CORE 1 + #endif + #include "internal/pycore_frame.h" +#endif +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = NULL; + PyObject *py_funcname = NULL; + #if PY_MAJOR_VERSION < 3 + PyObject *py_srcfile = NULL; + py_srcfile = PyString_FromString(filename); + if (!py_srcfile) goto bad; + #endif + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + funcname = PyUnicode_AsUTF8(py_funcname); + if (!funcname) goto bad; + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + if (!py_funcname) goto bad; + #endif + } + #if PY_MAJOR_VERSION < 3 + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + #else + py_code = PyCode_NewEmpty(filename, funcname, py_line); + #endif + Py_XDECREF(py_funcname); // XDECREF since it's only set on Py3 if cline + return py_code; +bad: + Py_XDECREF(py_funcname); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_srcfile); + #endif + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject *ptype, *pvalue, *ptraceback; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) { + /* If the code object creation fails, then we should clear the + fetched exception references and propagate the new exception */ + Py_XDECREF(ptype); + Py_XDECREF(pvalue); + Py_XDECREF(ptraceback); + goto bad; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* CIntFromPy */ + static CYTHON_INLINE npy_int32 __Pyx_PyInt_As_npy_int32(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const npy_int32 neg_one = (npy_int32) -1, const_zero = (npy_int32) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(npy_int32) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (npy_int32) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, digits[0]) + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 2 * PyLong_SHIFT) { + return (npy_int32) (((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 3 * PyLong_SHIFT) { + return (npy_int32) (((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) >= 4 * PyLong_SHIFT) { + return (npy_int32) (((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (npy_int32) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(npy_int32) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (npy_int32) 0; + case -1: __PYX_VERIFY_RETURN_INT(npy_int32, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(npy_int32, digit, +digits[0]) + case -2: + if (8 * sizeof(npy_int32) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(npy_int32) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + return (npy_int32) ((((((npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(npy_int32) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(npy_int32) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + return (npy_int32) ((((((((npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(npy_int32) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) (((npy_int32)-1)*(((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(npy_int32) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(npy_int32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(npy_int32) - 1 > 4 * PyLong_SHIFT) { + return (npy_int32) ((((((((((npy_int32)digits[3]) << PyLong_SHIFT) | (npy_int32)digits[2]) << PyLong_SHIFT) | (npy_int32)digits[1]) << PyLong_SHIFT) | (npy_int32)digits[0]))); + } + } + break; + } +#endif + if (sizeof(npy_int32) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_int32) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(npy_int32, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + npy_int32 val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (npy_int32) -1; + } + } else { + npy_int32 val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (npy_int32) -1; + val = __Pyx_PyInt_As_npy_int32(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to npy_int32"); + return (npy_int32) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to npy_int32"); + return (npy_int32) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; i '9'); + break; + } + if (rt_from_call[i] != ctversion[i]) { + same = 0; + break; + } + } + if (!same) { + char rtversion[5] = {'\0'}; + char message[200]; + for (i=0; i<4; ++i) { + if (rt_from_call[i] == '.') { + if (found_dot) break; + found_dot = 1; + } else if (rt_from_call[i] < '0' || rt_from_call[i] > '9') { + break; + } + rtversion[i] = rt_from_call[i]; + } + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + return PyErr_WarnEx(NULL, message, 1); + } + return 0; +} + +/* InitStrings */ + static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) { + if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) { + return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o); +#if PY_MAJOR_VERSION < 3 + } else if (likely(PyInt_CheckExact(o))) { + return PyInt_AS_LONG(o); +#endif + } else { + Py_ssize_t ival; + PyObject *x; + x = PyNumber_Index(o); + if (!x) return -1; + ival = PyInt_AsLong(x); + Py_DECREF(x); + return ival; + } +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/lib/nms/gpu_nms.cpython-36m-x86_64-linux-gnu.so b/lib/nms/gpu_nms.cpython-36m-x86_64-linux-gnu.so new file mode 100644 index 00000000..befd166f Binary files /dev/null and b/lib/nms/gpu_nms.cpython-36m-x86_64-linux-gnu.so differ diff --git a/lib/utils/utils.py b/lib/utils/utils.py index 5c31ca10..d1a33dbd 100644 --- a/lib/utils/utils.py +++ b/lib/utils/utils.py @@ -24,7 +24,7 @@ def create_logger(cfg, cfg_name, phase='train'): # set up logger if not root_output_dir.exists(): print('=> creating {}'.format(root_output_dir)) - root_output_dir.mkdir() + root_output_dir.mkdir(parents=True) dataset = cfg.DATASET.DATASET + '_' + cfg.DATASET.HYBRID_JOINTS_TYPE \ if cfg.DATASET.HYBRID_JOINTS_TYPE else cfg.DATASET.DATASET diff --git a/lib/utils/vis.py b/lib/utils/vis.py index adc0947a..d95cebd1 100755 --- a/lib/utils/vis.py +++ b/lib/utils/vis.py @@ -9,10 +9,12 @@ from __future__ import print_function import math +import os import numpy as np import torchvision import cv2 +from PIL import Image from core.inference import get_max_preds @@ -51,6 +53,30 @@ def save_batch_image_with_joints(batch_image, batch_joints, batch_joints_vis, cv2.imwrite(file_name, ndarr) +def save_batch_image_with_joints_separately(batch_image, batch_joints, save_dir, start_idx, scores): + ''' + batch_image: [batch_size, channel, height, width] + batch_joints: [batch_size, num_joints, 3], + ''' + threshold = 0.0 + ndarr = batch_image.permute(0, 2, 3, 1).cpu().numpy() # BHWC + B, H, W, C = ndarr.shape + ndarr = ndarr.reshape((B, -1, C)) + minimum, maximum = np.min(ndarr, axis=1, keepdims=True), np.max(ndarr, axis=1, keepdims=True) + ndarr = ((ndarr-minimum) / (maximum-minimum) * 255).astype(np.uint8) + ndarr = ndarr.reshape((B, H, W, C)) + ndarr = ndarr.copy() + + for i in range(B): + joints = batch_joints[i] + for j, joint in enumerate(joints): + if scores[i][j] >= threshold: + cv2.circle(ndarr[i], (int(joint[0]), int(joint[1])), 2, [255, 0, 0], 2) + cv2.putText(ndarr[i], "{}".format(round(scores[i][j].item(), 2)), (int(joint[0])+5, int(joint[1])+5), cv2.FONT_HERSHEY_SIMPLEX, 0.3, color=[255,0,0]) + save_image = cv2.resize(ndarr[i], (1024, 1024), interpolation=cv2.INTER_LINEAR) + cv2.imwrite(os.path.join(save_dir, "{}.png".format(start_idx+i)), save_image) + + def save_batch_heatmaps(batch_image, batch_heatmaps, file_name, normalize=True): ''' diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_hm_pred.jpg b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_hm_pred.jpg new file mode 100644 index 00000000..9b203166 Binary files /dev/null and b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_hm_pred.jpg differ diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_pred.jpg b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_pred.jpg new file mode 100644 index 00000000..6cc09599 Binary files /dev/null and b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/inference_0_pred.jpg differ diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pose_hrnet.py b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pose_hrnet.py new file mode 100644 index 00000000..09ff346a --- /dev/null +++ b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pose_hrnet.py @@ -0,0 +1,501 @@ +# ------------------------------------------------------------------------------ +# Copyright (c) Microsoft +# Licensed under the MIT License. +# Written by Bin Xiao (Bin.Xiao@microsoft.com) +# ------------------------------------------------------------------------------ + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import os +import logging + +import torch +import torch.nn as nn + + +BN_MOMENTUM = 0.1 +logger = logging.getLogger(__name__) + + +def conv3x3(in_planes, out_planes, stride=1): + """3x3 convolution with padding""" + return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride, + padding=1, bias=False) + + +class BasicBlock(nn.Module): + expansion = 1 + + def __init__(self, inplanes, planes, stride=1, downsample=None): + super(BasicBlock, self).__init__() + self.conv1 = conv3x3(inplanes, planes, stride) + self.bn1 = nn.BatchNorm2d(planes, momentum=BN_MOMENTUM) + self.relu = nn.ReLU(inplace=True) + self.conv2 = conv3x3(planes, planes) + self.bn2 = nn.BatchNorm2d(planes, momentum=BN_MOMENTUM) + self.downsample = downsample + self.stride = stride + + def forward(self, x): + residual = x + + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + + out = self.conv2(out) + out = self.bn2(out) + + if self.downsample is not None: + residual = self.downsample(x) + + out += residual + out = self.relu(out) + + return out + + +class Bottleneck(nn.Module): + expansion = 4 + + def __init__(self, inplanes, planes, stride=1, downsample=None): + super(Bottleneck, self).__init__() + self.conv1 = nn.Conv2d(inplanes, planes, kernel_size=1, bias=False) + self.bn1 = nn.BatchNorm2d(planes, momentum=BN_MOMENTUM) + self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, + padding=1, bias=False) + self.bn2 = nn.BatchNorm2d(planes, momentum=BN_MOMENTUM) + self.conv3 = nn.Conv2d(planes, planes * self.expansion, kernel_size=1, + bias=False) + self.bn3 = nn.BatchNorm2d(planes * self.expansion, + momentum=BN_MOMENTUM) + self.relu = nn.ReLU(inplace=True) + self.downsample = downsample + self.stride = stride + + def forward(self, x): + residual = x + + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + + out = self.conv2(out) + out = self.bn2(out) + out = self.relu(out) + + out = self.conv3(out) + out = self.bn3(out) + + if self.downsample is not None: + residual = self.downsample(x) + + out += residual + out = self.relu(out) + + return out + + +class HighResolutionModule(nn.Module): + def __init__(self, num_branches, blocks, num_blocks, num_inchannels, + num_channels, fuse_method, multi_scale_output=True): + super(HighResolutionModule, self).__init__() + self._check_branches( + num_branches, blocks, num_blocks, num_inchannels, num_channels) + + self.num_inchannels = num_inchannels + self.fuse_method = fuse_method + self.num_branches = num_branches + + self.multi_scale_output = multi_scale_output + + self.branches = self._make_branches( + num_branches, blocks, num_blocks, num_channels) + self.fuse_layers = self._make_fuse_layers() + self.relu = nn.ReLU(True) + + def _check_branches(self, num_branches, blocks, num_blocks, + num_inchannels, num_channels): + if num_branches != len(num_blocks): + error_msg = 'NUM_BRANCHES({}) <> NUM_BLOCKS({})'.format( + num_branches, len(num_blocks)) + logger.error(error_msg) + raise ValueError(error_msg) + + if num_branches != len(num_channels): + error_msg = 'NUM_BRANCHES({}) <> NUM_CHANNELS({})'.format( + num_branches, len(num_channels)) + logger.error(error_msg) + raise ValueError(error_msg) + + if num_branches != len(num_inchannels): + error_msg = 'NUM_BRANCHES({}) <> NUM_INCHANNELS({})'.format( + num_branches, len(num_inchannels)) + logger.error(error_msg) + raise ValueError(error_msg) + + def _make_one_branch(self, branch_index, block, num_blocks, num_channels, + stride=1): + downsample = None + if stride != 1 or \ + self.num_inchannels[branch_index] != num_channels[branch_index] * block.expansion: + downsample = nn.Sequential( + nn.Conv2d( + self.num_inchannels[branch_index], + num_channels[branch_index] * block.expansion, + kernel_size=1, stride=stride, bias=False + ), + nn.BatchNorm2d( + num_channels[branch_index] * block.expansion, + momentum=BN_MOMENTUM + ), + ) + + layers = [] + layers.append( + block( + self.num_inchannels[branch_index], + num_channels[branch_index], + stride, + downsample + ) + ) + self.num_inchannels[branch_index] = \ + num_channels[branch_index] * block.expansion + for i in range(1, num_blocks[branch_index]): + layers.append( + block( + self.num_inchannels[branch_index], + num_channels[branch_index] + ) + ) + + return nn.Sequential(*layers) + + def _make_branches(self, num_branches, block, num_blocks, num_channels): + branches = [] + + for i in range(num_branches): + branches.append( + self._make_one_branch(i, block, num_blocks, num_channels) + ) + + return nn.ModuleList(branches) + + def _make_fuse_layers(self): + if self.num_branches == 1: + return None + + num_branches = self.num_branches + num_inchannels = self.num_inchannels + fuse_layers = [] + for i in range(num_branches if self.multi_scale_output else 1): + fuse_layer = [] + for j in range(num_branches): + if j > i: + fuse_layer.append( + nn.Sequential( + nn.Conv2d( + num_inchannels[j], + num_inchannels[i], + 1, 1, 0, bias=False + ), + nn.BatchNorm2d(num_inchannels[i]), + nn.Upsample(scale_factor=2**(j-i), mode='nearest') + ) + ) + elif j == i: + fuse_layer.append(None) + else: + conv3x3s = [] + for k in range(i-j): + if k == i - j - 1: + num_outchannels_conv3x3 = num_inchannels[i] + conv3x3s.append( + nn.Sequential( + nn.Conv2d( + num_inchannels[j], + num_outchannels_conv3x3, + 3, 2, 1, bias=False + ), + nn.BatchNorm2d(num_outchannels_conv3x3) + ) + ) + else: + num_outchannels_conv3x3 = num_inchannels[j] + conv3x3s.append( + nn.Sequential( + nn.Conv2d( + num_inchannels[j], + num_outchannels_conv3x3, + 3, 2, 1, bias=False + ), + nn.BatchNorm2d(num_outchannels_conv3x3), + nn.ReLU(True) + ) + ) + fuse_layer.append(nn.Sequential(*conv3x3s)) + fuse_layers.append(nn.ModuleList(fuse_layer)) + + return nn.ModuleList(fuse_layers) + + def get_num_inchannels(self): + return self.num_inchannels + + def forward(self, x): + if self.num_branches == 1: + return [self.branches[0](x[0])] + + for i in range(self.num_branches): + x[i] = self.branches[i](x[i]) + + x_fuse = [] + + for i in range(len(self.fuse_layers)): + y = x[0] if i == 0 else self.fuse_layers[i][0](x[0]) + for j in range(1, self.num_branches): + if i == j: + y = y + x[j] + else: + y = y + self.fuse_layers[i][j](x[j]) + x_fuse.append(self.relu(y)) + + return x_fuse + + +blocks_dict = { + 'BASIC': BasicBlock, + 'BOTTLENECK': Bottleneck +} + + +class PoseHighResolutionNet(nn.Module): + + def __init__(self, cfg, **kwargs): + self.inplanes = 64 + extra = cfg['MODEL']['EXTRA'] + super(PoseHighResolutionNet, self).__init__() + + # stem net + self.conv1 = nn.Conv2d(3, 64, kernel_size=3, stride=2, padding=1, + bias=False) + self.bn1 = nn.BatchNorm2d(64, momentum=BN_MOMENTUM) + self.conv2 = nn.Conv2d(64, 64, kernel_size=3, stride=2, padding=1, + bias=False) + self.bn2 = nn.BatchNorm2d(64, momentum=BN_MOMENTUM) + self.relu = nn.ReLU(inplace=True) + self.layer1 = self._make_layer(Bottleneck, 64, 4) + + self.stage2_cfg = extra['STAGE2'] + num_channels = self.stage2_cfg['NUM_CHANNELS'] + block = blocks_dict[self.stage2_cfg['BLOCK']] + num_channels = [ + num_channels[i] * block.expansion for i in range(len(num_channels)) + ] + self.transition1 = self._make_transition_layer([256], num_channels) + self.stage2, pre_stage_channels = self._make_stage( + self.stage2_cfg, num_channels) + + self.stage3_cfg = extra['STAGE3'] + num_channels = self.stage3_cfg['NUM_CHANNELS'] + block = blocks_dict[self.stage3_cfg['BLOCK']] + num_channels = [ + num_channels[i] * block.expansion for i in range(len(num_channels)) + ] + self.transition2 = self._make_transition_layer( + pre_stage_channels, num_channels) + self.stage3, pre_stage_channels = self._make_stage( + self.stage3_cfg, num_channels) + + self.stage4_cfg = extra['STAGE4'] + num_channels = self.stage4_cfg['NUM_CHANNELS'] + block = blocks_dict[self.stage4_cfg['BLOCK']] + num_channels = [ + num_channels[i] * block.expansion for i in range(len(num_channels)) + ] + self.transition3 = self._make_transition_layer( + pre_stage_channels, num_channels) + self.stage4, pre_stage_channels = self._make_stage( + self.stage4_cfg, num_channels, multi_scale_output=False) + + self.final_layer = nn.Conv2d( + in_channels=pre_stage_channels[0], + out_channels=cfg['MODEL']['NUM_JOINTS'], + kernel_size=extra['FINAL_CONV_KERNEL'], + stride=1, + padding=1 if extra['FINAL_CONV_KERNEL'] == 3 else 0 + ) + + self.pretrained_layers = extra['PRETRAINED_LAYERS'] + + def _make_transition_layer( + self, num_channels_pre_layer, num_channels_cur_layer): + num_branches_cur = len(num_channels_cur_layer) + num_branches_pre = len(num_channels_pre_layer) + + transition_layers = [] + for i in range(num_branches_cur): + if i < num_branches_pre: + if num_channels_cur_layer[i] != num_channels_pre_layer[i]: + transition_layers.append( + nn.Sequential( + nn.Conv2d( + num_channels_pre_layer[i], + num_channels_cur_layer[i], + 3, 1, 1, bias=False + ), + nn.BatchNorm2d(num_channels_cur_layer[i]), + nn.ReLU(inplace=True) + ) + ) + else: + transition_layers.append(None) + else: + conv3x3s = [] + for j in range(i+1-num_branches_pre): + inchannels = num_channels_pre_layer[-1] + outchannels = num_channels_cur_layer[i] \ + if j == i-num_branches_pre else inchannels + conv3x3s.append( + nn.Sequential( + nn.Conv2d( + inchannels, outchannels, 3, 2, 1, bias=False + ), + nn.BatchNorm2d(outchannels), + nn.ReLU(inplace=True) + ) + ) + transition_layers.append(nn.Sequential(*conv3x3s)) + + return nn.ModuleList(transition_layers) + + def _make_layer(self, block, planes, blocks, stride=1): + downsample = None + if stride != 1 or self.inplanes != planes * block.expansion: + downsample = nn.Sequential( + nn.Conv2d( + self.inplanes, planes * block.expansion, + kernel_size=1, stride=stride, bias=False + ), + nn.BatchNorm2d(planes * block.expansion, momentum=BN_MOMENTUM), + ) + + layers = [] + layers.append(block(self.inplanes, planes, stride, downsample)) + self.inplanes = planes * block.expansion + for i in range(1, blocks): + layers.append(block(self.inplanes, planes)) + + return nn.Sequential(*layers) + + def _make_stage(self, layer_config, num_inchannels, + multi_scale_output=True): + num_modules = layer_config['NUM_MODULES'] + num_branches = layer_config['NUM_BRANCHES'] + num_blocks = layer_config['NUM_BLOCKS'] + num_channels = layer_config['NUM_CHANNELS'] + block = blocks_dict[layer_config['BLOCK']] + fuse_method = layer_config['FUSE_METHOD'] + + modules = [] + for i in range(num_modules): + # multi_scale_output is only used last module + if not multi_scale_output and i == num_modules - 1: + reset_multi_scale_output = False + else: + reset_multi_scale_output = True + + modules.append( + HighResolutionModule( + num_branches, + block, + num_blocks, + num_inchannels, + num_channels, + fuse_method, + reset_multi_scale_output + ) + ) + num_inchannels = modules[-1].get_num_inchannels() + + return nn.Sequential(*modules), num_inchannels + + def forward(self, x): + x = self.conv1(x) + x = self.bn1(x) + x = self.relu(x) + x = self.conv2(x) + x = self.bn2(x) + x = self.relu(x) + x = self.layer1(x) + + x_list = [] + for i in range(self.stage2_cfg['NUM_BRANCHES']): + if self.transition1[i] is not None: + x_list.append(self.transition1[i](x)) + else: + x_list.append(x) + y_list = self.stage2(x_list) + + x_list = [] + for i in range(self.stage3_cfg['NUM_BRANCHES']): + if self.transition2[i] is not None: + x_list.append(self.transition2[i](y_list[-1])) + else: + x_list.append(y_list[i]) + y_list = self.stage3(x_list) + + x_list = [] + for i in range(self.stage4_cfg['NUM_BRANCHES']): + if self.transition3[i] is not None: + x_list.append(self.transition3[i](y_list[-1])) + else: + x_list.append(y_list[i]) + y_list = self.stage4(x_list) + + x = self.final_layer(y_list[0]) + + return x + + def init_weights(self, pretrained=''): + logger.info('=> init weights from normal distribution') + for m in self.modules(): + if isinstance(m, nn.Conv2d): + # nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu') + nn.init.normal_(m.weight, std=0.001) + for name, _ in m.named_parameters(): + if name in ['bias']: + nn.init.constant_(m.bias, 0) + elif isinstance(m, nn.BatchNorm2d): + nn.init.constant_(m.weight, 1) + nn.init.constant_(m.bias, 0) + elif isinstance(m, nn.ConvTranspose2d): + nn.init.normal_(m.weight, std=0.001) + for name, _ in m.named_parameters(): + if name in ['bias']: + nn.init.constant_(m.bias, 0) + + if os.path.isfile(pretrained): + pretrained_state_dict = torch.load(pretrained) + logger.info('=> loading pretrained model {}'.format(pretrained)) + + need_init_state_dict = {} + for name, m in pretrained_state_dict.items(): + if name.split('.')[0] in self.pretrained_layers \ + or self.pretrained_layers[0] is '*': + need_init_state_dict[name] = m + self.load_state_dict(need_init_state_dict, strict=False) + elif pretrained: + logger.error('=> please download pre-trained models first!') + raise ValueError('{} is not exist!'.format(pretrained)) + + +def get_pose_net(cfg, is_train, **kwargs): + model = PoseHighResolutionNet(cfg, **kwargs) + + if is_train and cfg['MODEL']['INIT_WEIGHTS']: + model.init_weights(cfg['MODEL']['PRETRAINED']) + + return model diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pred.mat b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pred.mat new file mode 100644 index 00000000..90152608 Binary files /dev/null and b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/pred.mat differ diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/train_0_gt.jpg b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/train_0_gt.jpg new file mode 100644 index 00000000..dc5db919 Binary files /dev/null and b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/train_0_gt.jpg differ diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/train_0_hm_gt.jpg b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/train_0_hm_gt.jpg new file mode 100644 index 00000000..3c471602 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differ diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-01-14-11-20_train.log b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-01-14-11-20_train.log new file mode 100644 index 00000000..1583a301 --- /dev/null +++ b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-01-14-11-20_train.log @@ -0,0 +1,1315 @@ +2023-01-14 11:20:21,363 Namespace(cfg='.\\experiments\\mpii\\hrnet\\w32_256x256_adam_lr1e-3_ak.yaml', dataDir='', logDir='', modelDir='', opts=[], prevModelDir='') +2023-01-14 11:20:21,363 AUTO_RESUME: True +CUDNN: + BENCHMARK: True + DETERMINISTIC: False + ENABLED: True +DATASET: + COLOR_RGB: True + DATASET: ak + DATA_FORMAT: jpg + FLIP: True + HYBRID_JOINTS_TYPE: + IMAGE_ROOT: E:/huazhen/dataset/AnimalKingdom-PoseEstimation/dataset/ + NUM_JOINTS_HALF_BODY: 11 + PROB_HALF_BODY: -1.0 + ROOT: data/ak_P2 + ROT_FACTOR: 30 + SCALE_FACTOR: 0.25 + SELECT_DATA: False + TEST_SET: test + TRAIN_SET: train +DATA_DIR: +DEBUG: + DEBUG: True + SAVE_BATCH_IMAGES_GT: True + SAVE_BATCH_IMAGES_PRED: True + SAVE_HEATMAPS_GT: True + SAVE_HEATMAPS_PRED: True +GPUS: (0,) +LOG_DIR: log/ak_P2 +LOSS: + TOPK: 8 + USE_DIFFERENT_JOINTS_WEIGHT: False + USE_OHKM: False + USE_TARGET_WEIGHT: True +MODEL: + EXTRA: + FINAL_CONV_KERNEL: 1 + PRETRAINED_LAYERS: ['conv1', 'bn1', 'conv2', 'bn2', 'layer1', 'transition1', 'stage2', 'transition2', 'stage3', 'transition3', 'stage4'] + STAGE2: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4] + NUM_BRANCHES: 2 + NUM_CHANNELS: [32, 64] + NUM_MODULES: 1 + STAGE3: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4, 4] + NUM_BRANCHES: 3 + NUM_CHANNELS: [32, 64, 128] + NUM_MODULES: 4 + STAGE4: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4, 4, 4] + NUM_BRANCHES: 4 + NUM_CHANNELS: [32, 64, 128, 256] + NUM_MODULES: 3 + HEATMAP_SIZE: [64, 64] + IMAGE_SIZE: [256, 256] + INIT_WEIGHTS: True + NAME: pose_hrnet + NUM_JOINTS: 23 + PRETRAINED: + SIGMA: 2 + TAG_PER_JOINT: True + TARGET_TYPE: gaussian +OUTPUT_DIR: output/ak_P2 +PIN_MEMORY: True +PRINT_FREQ: 100 +RANK: 0 +TEST: + BATCH_SIZE_PER_GPU: 32 + BBOX_THRE: 1.0 + COCO_BBOX_FILE: + FLIP_TEST: True + IMAGE_THRE: 0.1 + IN_VIS_THRE: 0.0 + MODEL_FILE: + NMS_THRE: 0.6 + OKS_THRE: 0.5 + POST_PROCESS: True + SHIFT_HEATMAP: True + SOFT_NMS: False + USE_GT_BBOX: False +TRAIN: + BATCH_SIZE_PER_GPU: 32 + BEGIN_EPOCH: 0 + CHECKPOINT: + END_EPOCH: 150 + GAMMA1: 0.99 + GAMMA2: 0.0 + LR: 0.001 + LR_FACTOR: 0.1 + LR_STEP: [170, 200] + MOMENTUM: 0.9 + NESTEROV: False + OPTIMIZER: adam + RESUME: False + SHUFFLE: True + WD: 0.0001 +WORKERS: 4 +2023-01-14 11:20:21,788 => init weights from normal distribution +2023-01-14 11:20:22,623 +Total Parameters: 28,536,311 +---------------------------------------------------------------------------------------------------------------------------------- +Total Multiply Adds (For Convolution and Linear Layers only): 9.4940185546875 GFLOPs +---------------------------------------------------------------------------------------------------------------------------------- +Number of Layers +Conv2d : 293 layers BatchNorm2d : 292 layers ReLU : 261 layers Bottleneck : 4 layers BasicBlock : 104 layers Upsample : 28 layers HighResolutionModule : 8 layers +2023-01-14 11:20:24,156 => load 6819 samples +2023-01-14 11:20:24,398 => load 1705 samples +2023-01-14 11:20:45,586 Epoch: [0][0/214] Time 21.173s (21.173s) Speed 1.5 samples/s Data 14.251s (14.251s) Loss 0.00122 (0.00122) Accuracy 0.008 (0.008) +2023-01-14 11:22:06,300 Epoch: [0][100/214] Time 0.785s (1.009s) Speed 40.8 samples/s Data 0.000s (0.161s) Loss 0.00089 (0.00100) Accuracy 0.014 (0.012) +2023-01-14 11:23:28,609 Epoch: [0][200/214] Time 0.812s (0.916s) Speed 39.4 samples/s Data 0.001s (0.089s) Loss 0.00077 (0.00090) Accuracy 0.064 (0.029) +2023-01-14 11:23:54,091 Test: [0/54] Time 11.992 (11.992) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:24:20,923 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:24:20,924 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:24:20,924 | pose_hrnet | 19.426 | 17.853 | 14.823 | 5.447 | 26.376 | 28.204 | 23.247 | 16.889 | 15.938 | 17.948 | +2023-01-14 11:24:20,925 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:24:36,144 Epoch: [1][0/214] Time 13.052s (13.052s) Speed 2.5 samples/s Data 11.983s (11.983s) Loss 0.00079 (0.00079) Accuracy 0.073 (0.073) +2023-01-14 11:25:57,415 Epoch: [1][100/214] Time 0.808s (0.934s) Speed 39.6 samples/s Data 0.000s (0.135s) Loss 0.00081 (0.00079) Accuracy 0.101 (0.084) +2023-01-14 11:27:18,411 Epoch: [1][200/214] Time 0.775s (0.872s) Speed 41.3 samples/s Data 0.000s (0.076s) Loss 0.00076 (0.00079) Accuracy 0.143 (0.095) +2023-01-14 11:27:41,519 Test: [0/54] Time 11.410 (11.410) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:28:07,444 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:28:07,444 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:28:07,445 | pose_hrnet | 43.754 | 23.948 | 16.686 | 11.092 | 42.547 | 41.086 | 36.502 | 40.199 | 20.953 | 32.258 | +2023-01-14 11:28:07,446 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:28:22,310 Epoch: [2][0/214] Time 12.658s (12.658s) Speed 2.5 samples/s Data 11.905s (11.905s) Loss 0.00080 (0.00080) Accuracy 0.124 (0.124) +2023-01-14 11:29:41,407 Epoch: [2][100/214] Time 0.788s (0.908s) Speed 40.6 samples/s Data 0.000s (0.134s) Loss 0.00079 (0.00078) Accuracy 0.145 (0.128) +2023-01-14 11:31:01,285 Epoch: [2][200/214] Time 0.784s (0.854s) Speed 40.8 samples/s Data 0.000s (0.075s) Loss 0.00076 (0.00078) Accuracy 0.158 (0.132) +2023-01-14 11:31:24,825 Test: [0/54] Time 11.777 (11.777) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:31:50,761 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:31:50,761 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:31:50,762 | pose_hrnet | 47.400 | 24.527 | 17.299 | 20.947 | 45.686 | 39.806 | 34.529 | 44.415 | 24.368 | 34.739 | +2023-01-14 11:31:50,763 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:32:05,325 Epoch: [3][0/214] Time 12.399s (12.399s) Speed 2.6 samples/s Data 11.663s (11.663s) Loss 0.00084 (0.00084) Accuracy 0.178 (0.178) +2023-01-14 11:33:24,693 Epoch: [3][100/214] Time 0.808s (0.909s) Speed 39.6 samples/s Data 0.000s (0.132s) Loss 0.00075 (0.00077) Accuracy 0.169 (0.152) +2023-01-14 11:34:44,700 Epoch: [3][200/214] Time 0.761s (0.855s) Speed 42.1 samples/s Data 0.001s (0.075s) Loss 0.00073 (0.00077) Accuracy 0.150 (0.160) +2023-01-14 11:35:08,113 Test: [0/54] Time 11.797 (11.797) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:35:33,929 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:35:33,930 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:35:33,930 | pose_hrnet | 51.704 | 30.688 | 21.036 | 26.561 | 50.386 | 44.660 | 43.455 | 53.967 | 27.124 | 40.501 | +2023-01-14 11:35:33,931 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:35:48,766 Epoch: [4][0/214] Time 12.533s (12.533s) Speed 2.6 samples/s Data 11.790s (11.790s) Loss 0.00080 (0.00080) Accuracy 0.190 (0.190) +2023-01-14 11:37:08,219 Epoch: [4][100/214] Time 0.763s (0.911s) Speed 41.9 samples/s Data 0.000s (0.134s) Loss 0.00072 (0.00076) Accuracy 0.154 (0.188) +2023-01-14 11:38:28,081 Epoch: [4][200/214] Time 0.762s (0.855s) Speed 42.0 samples/s Data 0.000s (0.075s) Loss 0.00075 (0.00076) Accuracy 0.253 (0.193) +2023-01-14 11:38:51,364 Test: [0/54] Time 11.607 (11.607) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:39:17,110 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:39:17,110 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:39:17,111 | pose_hrnet | 56.724 | 36.600 | 21.284 | 24.718 | 59.200 | 53.642 | 51.095 | 54.938 | 33.241 | 44.555 | +2023-01-14 11:39:17,112 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:39:31,809 Epoch: [5][0/214] Time 12.537s (12.537s) Speed 2.6 samples/s Data 11.779s (11.779s) Loss 0.00077 (0.00077) Accuracy 0.205 (0.205) +2023-01-14 11:40:50,988 Epoch: [5][100/214] Time 0.783s (0.908s) Speed 40.9 samples/s Data 0.000s (0.134s) Loss 0.00077 (0.00075) Accuracy 0.220 (0.215) +2023-01-14 11:42:10,892 Epoch: [5][200/214] Time 0.763s (0.854s) Speed 41.9 samples/s Data 0.000s (0.076s) Loss 0.00074 (0.00074) Accuracy 0.217 (0.223) +2023-01-14 11:42:34,166 Test: [0/54] Time 11.629 (11.629) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:42:59,905 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:42:59,905 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:42:59,906 | pose_hrnet | 56.605 | 41.182 | 26.830 | 31.682 | 56.305 | 51.652 | 47.244 | 59.700 | 37.442 | 47.184 | +2023-01-14 11:42:59,907 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:43:14,894 Epoch: [6][0/214] Time 12.689s (12.689s) Speed 2.5 samples/s Data 11.947s (11.947s) Loss 0.00073 (0.00073) Accuracy 0.229 (0.229) +2023-01-14 11:44:34,130 Epoch: [6][100/214] Time 0.777s (0.910s) Speed 41.2 samples/s Data 0.001s (0.135s) Loss 0.00075 (0.00073) Accuracy 0.259 (0.238) +2023-01-14 11:45:54,122 Epoch: [6][200/214] Time 0.783s (0.855s) Speed 40.9 samples/s Data 0.001s (0.076s) Loss 0.00073 (0.00072) Accuracy 0.302 (0.248) +2023-01-14 11:46:17,247 Test: [0/54] Time 11.287 (11.287) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:46:43,241 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:46:43,241 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:46:43,242 | pose_hrnet | 60.849 | 39.602 | 27.943 | 32.641 | 58.964 | 55.083 | 51.775 | 60.830 | 43.421 | 49.577 | +2023-01-14 11:46:43,244 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:46:57,926 Epoch: [7][0/214] Time 12.485s (12.485s) Speed 2.6 samples/s Data 11.746s (11.746s) Loss 0.00071 (0.00071) Accuracy 0.197 (0.197) +2023-01-14 11:48:16,936 Epoch: [7][100/214] Time 0.778s (0.906s) Speed 41.1 samples/s Data 0.000s (0.133s) Loss 0.00067 (0.00072) Accuracy 0.306 (0.261) +2023-01-14 11:49:36,738 Epoch: [7][200/214] Time 0.793s (0.852s) Speed 40.4 samples/s Data 0.001s (0.075s) Loss 0.00070 (0.00071) Accuracy 0.301 (0.277) +2023-01-14 11:50:00,068 Test: [0/54] Time 11.753 (11.753) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:50:25,844 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:50:25,844 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:50:25,844 | pose_hrnet | 62.343 | 47.968 | 30.888 | 38.310 | 65.725 | 58.589 | 53.067 | 67.027 | 47.157 | 54.468 | +2023-01-14 11:50:25,846 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:50:40,480 Epoch: [8][0/214] Time 12.426s (12.426s) Speed 2.6 samples/s Data 11.675s (11.675s) Loss 0.00072 (0.00072) Accuracy 0.254 (0.254) +2023-01-14 11:51:59,388 Epoch: [8][100/214] Time 0.804s (0.904s) Speed 39.8 samples/s Data 0.001s (0.133s) Loss 0.00074 (0.00070) Accuracy 0.303 (0.303) +2023-01-14 11:53:19,320 Epoch: [8][200/214] Time 0.775s (0.852s) Speed 41.3 samples/s Data 0.000s (0.075s) Loss 0.00064 (0.00069) Accuracy 0.349 (0.314) +2023-01-14 11:53:42,517 Test: [0/54] Time 11.677 (11.677) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:54:08,292 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:54:08,293 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:54:08,293 | pose_hrnet | 66.766 | 53.121 | 34.589 | 47.740 | 69.764 | 62.818 | 57.174 | 71.258 | 55.361 | 59.888 | +2023-01-14 11:54:08,295 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:54:22,912 Epoch: [9][0/214] Time 12.411s (12.411s) Speed 2.6 samples/s Data 11.692s (11.692s) Loss 0.00068 (0.00068) Accuracy 0.412 (0.412) +2023-01-14 11:55:41,952 Epoch: [9][100/214] Time 0.796s (0.905s) Speed 40.2 samples/s Data 0.000s (0.132s) Loss 0.00073 (0.00068) Accuracy 0.319 (0.342) +2023-01-14 11:57:01,612 Epoch: [9][200/214] Time 0.773s (0.851s) Speed 41.4 samples/s Data 0.000s (0.074s) Loss 0.00066 (0.00067) Accuracy 0.416 (0.352) +2023-01-14 11:57:24,812 Test: [0/54] Time 11.606 (11.606) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 11:57:50,590 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 11:57:50,591 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 11:57:50,591 | pose_hrnet | 71.070 | 56.649 | 41.437 | 48.552 | 73.265 | 67.464 | 61.329 | 72.933 | 57.668 | 63.081 | +2023-01-14 11:57:50,592 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 11:58:04,974 Epoch: [10][0/214] Time 12.218s (12.218s) Speed 2.6 samples/s Data 11.461s (11.461s) Loss 0.00061 (0.00061) Accuracy 0.471 (0.471) +2023-01-14 11:59:23,884 Epoch: [10][100/214] Time 0.807s (0.902s) Speed 39.7 samples/s Data 0.000s (0.130s) Loss 0.00058 (0.00066) Accuracy 0.380 (0.370) +2023-01-14 12:00:43,106 Epoch: [10][200/214] Time 0.775s (0.848s) Speed 41.3 samples/s Data 0.000s (0.074s) Loss 0.00058 (0.00065) Accuracy 0.411 (0.383) +2023-01-14 12:01:06,432 Test: [0/54] Time 11.620 (11.620) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:01:32,112 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:01:32,112 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:01:32,113 | pose_hrnet | 72.564 | 59.812 | 44.249 | 49.970 | 72.358 | 68.422 | 62.246 | 76.239 | 61.290 | 65.349 | +2023-01-14 12:01:32,114 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:01:46,837 Epoch: [11][0/214] Time 12.506s (12.506s) Speed 2.6 samples/s Data 11.737s (11.737s) Loss 0.00069 (0.00069) Accuracy 0.366 (0.366) +2023-01-14 12:03:05,748 Epoch: [11][100/214] Time 0.794s (0.905s) Speed 40.3 samples/s Data 0.000s (0.133s) Loss 0.00063 (0.00064) Accuracy 0.419 (0.395) +2023-01-14 12:04:25,621 Epoch: [11][200/214] Time 0.785s (0.852s) Speed 40.8 samples/s Data 0.000s (0.075s) Loss 0.00063 (0.00063) Accuracy 0.428 (0.404) +2023-01-14 12:04:49,027 Test: [0/54] Time 11.694 (11.694) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:05:14,657 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:05:14,658 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:05:14,658 | pose_hrnet | 60.669 | 49.564 | 39.776 | 42.469 | 63.907 | 58.681 | 57.307 | 64.227 | 52.801 | 55.825 | +2023-01-14 12:05:14,659 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:05:29,024 Epoch: [12][0/214] Time 12.777s (12.777s) Speed 2.5 samples/s Data 12.036s (12.036s) Loss 0.00059 (0.00059) Accuracy 0.408 (0.408) +2023-01-14 12:06:48,205 Epoch: [12][100/214] Time 0.778s (0.910s) Speed 41.1 samples/s Data 0.001s (0.136s) Loss 0.00058 (0.00062) Accuracy 0.393 (0.426) +2023-01-14 12:08:08,066 Epoch: [12][200/214] Time 0.784s (0.855s) Speed 40.8 samples/s Data 0.000s (0.076s) Loss 0.00063 (0.00062) Accuracy 0.371 (0.431) +2023-01-14 12:08:31,308 Test: [0/54] Time 11.671 (11.671) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:08:56,917 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:08:56,918 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:08:56,918 | pose_hrnet | 76.868 | 64.712 | 50.210 | 55.106 | 76.702 | 72.625 | 64.446 | 78.739 | 66.087 | 69.158 | +2023-01-14 12:08:56,920 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:09:11,574 Epoch: [13][0/214] Time 12.475s (12.475s) Speed 2.6 samples/s Data 11.734s (11.734s) Loss 0.00060 (0.00060) Accuracy 0.417 (0.417) +2023-01-14 12:10:30,709 Epoch: [13][100/214] Time 0.777s (0.907s) Speed 41.2 samples/s Data 0.001s (0.133s) Loss 0.00060 (0.00061) Accuracy 0.422 (0.443) +2023-01-14 12:11:50,137 Epoch: [13][200/214] Time 0.786s (0.851s) Speed 40.7 samples/s Data 0.000s (0.075s) Loss 0.00058 (0.00060) Accuracy 0.398 (0.452) +2023-01-14 12:12:13,589 Test: [0/54] Time 11.824 (11.824) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:12:39,365 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:12:39,365 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:12:39,365 | pose_hrnet | 75.672 | 66.087 | 50.537 | 56.537 | 79.054 | 72.441 | 66.857 | 79.418 | 66.189 | 69.880 | +2023-01-14 12:12:39,367 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:12:53,988 Epoch: [14][0/214] Time 12.354s (12.354s) Speed 2.6 samples/s Data 11.626s (11.626s) Loss 0.00048 (0.00048) Accuracy 0.506 (0.506) +2023-01-14 12:14:13,101 Epoch: [14][100/214] Time 0.808s (0.906s) Speed 39.6 samples/s Data 0.000s (0.132s) Loss 0.00058 (0.00059) Accuracy 0.533 (0.467) +2023-01-14 12:15:33,259 Epoch: [14][200/214] Time 0.794s (0.854s) Speed 40.3 samples/s Data 0.000s (0.075s) Loss 0.00057 (0.00059) Accuracy 0.552 (0.470) +2023-01-14 12:15:56,543 Test: [0/54] Time 11.705 (11.705) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:16:22,167 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:16:22,168 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:16:22,168 | pose_hrnet | 64.973 | 54.889 | 41.904 | 51.061 | 64.390 | 60.846 | 59.508 | 68.226 | 58.012 | 59.703 | +2023-01-14 12:16:22,169 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:16:36,527 Epoch: [15][0/214] Time 12.663s (12.663s) Speed 2.5 samples/s Data 11.921s (11.921s) Loss 0.00050 (0.00050) Accuracy 0.537 (0.537) +2023-01-14 12:17:55,617 Epoch: [15][100/214] Time 0.778s (0.908s) Speed 41.1 samples/s Data 0.000s (0.134s) Loss 0.00055 (0.00058) Accuracy 0.566 (0.476) +2023-01-14 12:19:15,595 Epoch: [15][200/214] Time 0.774s (0.854s) Speed 41.3 samples/s Data 0.000s (0.075s) Loss 0.00052 (0.00058) Accuracy 0.496 (0.484) +2023-01-14 12:19:38,824 Test: [0/54] Time 11.427 (11.427) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:20:04,395 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:20:04,396 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:20:04,396 | pose_hrnet | 78.004 | 69.709 | 56.197 | 60.200 | 80.206 | 75.935 | 69.890 | 83.918 | 69.388 | 73.476 | +2023-01-14 12:20:04,397 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:20:19,068 Epoch: [16][0/214] Time 12.545s (12.545s) Speed 2.6 samples/s Data 11.793s (11.793s) Loss 0.00054 (0.00054) Accuracy 0.517 (0.517) +2023-01-14 12:21:38,124 Epoch: [16][100/214] Time 0.775s (0.907s) Speed 41.3 samples/s Data 0.001s (0.132s) Loss 0.00062 (0.00058) Accuracy 0.499 (0.488) +2023-01-14 12:22:57,685 Epoch: [16][200/214] Time 0.779s (0.852s) Speed 41.1 samples/s Data 0.000s (0.074s) Loss 0.00067 (0.00057) Accuracy 0.404 (0.499) +2023-01-14 12:23:20,778 Test: [0/54] Time 11.454 (11.454) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:23:46,494 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:23:46,494 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:23:46,495 | pose_hrnet | 79.199 | 70.086 | 55.834 | 59.843 | 79.118 | 77.072 | 68.974 | 82.969 | 69.082 | 73.323 | +2023-01-14 12:23:46,496 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:24:00,338 Epoch: [17][0/214] Time 12.205s (12.205s) Speed 2.6 samples/s Data 11.469s (11.469s) Loss 0.00053 (0.00053) Accuracy 0.582 (0.582) +2023-01-14 12:25:18,925 Epoch: [17][100/214] Time 0.766s (0.899s) Speed 41.8 samples/s Data 0.000s (0.128s) Loss 0.00060 (0.00057) Accuracy 0.450 (0.506) +2023-01-14 12:26:38,705 Epoch: [17][200/214] Time 0.788s (0.849s) Speed 40.6 samples/s Data 0.001s (0.072s) Loss 0.00060 (0.00056) Accuracy 0.504 (0.516) +2023-01-14 12:27:01,721 Test: [0/54] Time 11.492 (11.492) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:27:27,392 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:27:27,393 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:27:27,393 | pose_hrnet | 81.231 | 71.810 | 57.314 | 58.253 | 81.471 | 76.956 | 68.434 | 85.461 | 70.289 | 74.814 | +2023-01-14 12:27:27,395 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:27:41,774 Epoch: [18][0/214] Time 12.252s (12.252s) Speed 2.6 samples/s Data 11.504s (11.504s) Loss 0.00054 (0.00054) Accuracy 0.469 (0.469) +2023-01-14 12:29:00,561 Epoch: [18][100/214] Time 0.777s (0.901s) Speed 41.2 samples/s Data 0.000s (0.131s) Loss 0.00055 (0.00055) Accuracy 0.482 (0.530) +2023-01-14 12:30:19,858 Epoch: [18][200/214] Time 0.759s (0.847s) Speed 42.2 samples/s Data 0.001s (0.073s) Loss 0.00055 (0.00054) Accuracy 0.539 (0.539) +2023-01-14 12:30:43,154 Test: [0/54] Time 11.618 (11.618) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:31:08,724 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:31:08,725 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:31:08,726 | pose_hrnet | 78.601 | 70.092 | 55.838 | 60.054 | 81.289 | 73.575 | 71.839 | 83.104 | 69.425 | 73.564 | +2023-01-14 12:31:08,727 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:31:22,799 Epoch: [19][0/214] Time 12.462s (12.462s) Speed 2.6 samples/s Data 11.728s (11.728s) Loss 0.00056 (0.00056) Accuracy 0.561 (0.561) +2023-01-14 12:32:41,488 Epoch: [19][100/214] Time 0.772s (0.902s) Speed 41.5 samples/s Data 0.000s (0.132s) Loss 0.00061 (0.00054) Accuracy 0.536 (0.544) +2023-01-14 12:34:01,172 Epoch: [19][200/214] Time 0.760s (0.850s) Speed 42.1 samples/s Data 0.000s (0.074s) Loss 0.00049 (0.00053) Accuracy 0.585 (0.550) +2023-01-14 12:34:24,280 Test: [0/54] Time 11.495 (11.495) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:34:49,883 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:34:49,884 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:34:49,884 | pose_hrnet | 82.606 | 69.863 | 57.486 | 61.016 | 81.592 | 78.222 | 73.056 | 85.943 | 72.770 | 75.864 | +2023-01-14 12:34:49,886 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:35:04,370 Epoch: [20][0/214] Time 12.222s (12.222s) Speed 2.6 samples/s Data 11.488s (11.488s) Loss 0.00053 (0.00053) Accuracy 0.502 (0.502) +2023-01-14 12:36:23,211 Epoch: [20][100/214] Time 0.770s (0.902s) Speed 41.6 samples/s Data 0.000s (0.129s) Loss 0.00051 (0.00053) Accuracy 0.528 (0.557) +2023-01-14 12:37:42,743 Epoch: [20][200/214] Time 0.783s (0.849s) Speed 40.9 samples/s Data 0.000s (0.073s) Loss 0.00055 (0.00053) Accuracy 0.612 (0.556) +2023-01-14 12:38:05,556 Test: [0/54] Time 11.079 (11.079) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:38:31,218 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:38:31,218 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:38:31,219 | pose_hrnet | 82.068 | 74.544 | 58.981 | 61.107 | 84.609 | 80.138 | 75.468 | 86.310 | 72.797 | 76.929 | +2023-01-14 12:38:31,221 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:38:45,732 Epoch: [21][0/214] Time 12.301s (12.301s) Speed 2.6 samples/s Data 11.571s (11.571s) Loss 0.00049 (0.00049) Accuracy 0.594 (0.594) +2023-01-14 12:40:04,620 Epoch: [21][100/214] Time 0.758s (0.903s) Speed 42.2 samples/s Data 0.000s (0.130s) Loss 0.00046 (0.00052) Accuracy 0.605 (0.570) +2023-01-14 12:41:24,108 Epoch: [21][200/214] Time 0.775s (0.849s) Speed 41.3 samples/s Data 0.001s (0.073s) Loss 0.00052 (0.00052) Accuracy 0.555 (0.573) +2023-01-14 12:41:47,515 Test: [0/54] Time 11.639 (11.639) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:42:13,123 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:42:13,123 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:42:13,124 | pose_hrnet | 79.617 | 74.281 | 58.873 | 63.565 | 81.893 | 78.219 | 73.281 | 84.931 | 73.401 | 76.193 | +2023-01-14 12:42:13,126 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:42:27,067 Epoch: [22][0/214] Time 12.364s (12.364s) Speed 2.6 samples/s Data 11.618s (11.618s) Loss 0.00052 (0.00052) Accuracy 0.553 (0.553) +2023-01-14 12:43:45,736 Epoch: [22][100/214] Time 0.776s (0.901s) Speed 41.2 samples/s Data 0.000s (0.130s) Loss 0.00047 (0.00051) Accuracy 0.632 (0.580) +2023-01-14 12:45:05,125 Epoch: [22][200/214] Time 0.805s (0.848s) Speed 39.7 samples/s Data 0.000s (0.073s) Loss 0.00049 (0.00051) Accuracy 0.603 (0.586) +2023-01-14 12:45:27,966 Test: [0/54] Time 11.214 (11.214) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:45:53,594 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:45:53,595 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:45:53,595 | pose_hrnet | 82.008 | 74.142 | 61.551 | 62.142 | 84.006 | 80.259 | 76.921 | 87.128 | 74.799 | 77.887 | +2023-01-14 12:45:53,596 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:46:07,895 Epoch: [23][0/214] Time 12.101s (12.101s) Speed 2.6 samples/s Data 11.361s (11.361s) Loss 0.00049 (0.00049) Accuracy 0.641 (0.641) +2023-01-14 12:47:26,915 Epoch: [23][100/214] Time 0.788s (0.902s) Speed 40.6 samples/s Data 0.000s (0.128s) Loss 0.00051 (0.00050) Accuracy 0.595 (0.600) +2023-01-14 12:48:46,562 Epoch: [23][200/214] Time 0.790s (0.850s) Speed 40.5 samples/s Data 0.000s (0.072s) Loss 0.00047 (0.00050) Accuracy 0.623 (0.601) +2023-01-14 12:49:09,547 Test: [0/54] Time 11.375 (11.375) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:49:35,208 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:49:35,208 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:49:35,209 | pose_hrnet | 79.199 | 71.879 | 59.714 | 64.008 | 81.650 | 77.594 | 75.249 | 83.374 | 71.773 | 75.244 | +2023-01-14 12:49:35,211 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:49:49,261 Epoch: [24][0/214] Time 12.335s (12.335s) Speed 2.6 samples/s Data 11.606s (11.606s) Loss 0.00044 (0.00044) Accuracy 0.669 (0.669) +2023-01-14 12:51:08,081 Epoch: [24][100/214] Time 0.809s (0.903s) Speed 39.6 samples/s Data 0.001s (0.130s) Loss 0.00049 (0.00049) Accuracy 0.574 (0.617) +2023-01-14 12:52:27,592 Epoch: [24][200/214] Time 0.776s (0.849s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00050 (0.00049) Accuracy 0.626 (0.613) +2023-01-14 12:52:50,834 Test: [0/54] Time 11.584 (11.584) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:53:16,429 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:53:16,430 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:53:16,430 | pose_hrnet | 71.548 | 63.251 | 49.428 | 51.705 | 73.505 | 68.855 | 66.695 | 74.883 | 60.462 | 65.951 | +2023-01-14 12:53:16,432 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:53:30,258 Epoch: [25][0/214] Time 12.253s (12.253s) Speed 2.6 samples/s Data 11.528s (11.528s) Loss 0.00051 (0.00051) Accuracy 0.625 (0.625) +2023-01-14 12:54:49,554 Epoch: [25][100/214] Time 0.784s (0.906s) Speed 40.8 samples/s Data 0.001s (0.129s) Loss 0.00055 (0.00056) Accuracy 0.602 (0.527) +2023-01-14 12:56:09,507 Epoch: [25][200/214] Time 0.807s (0.853s) Speed 39.7 samples/s Data 0.000s (0.073s) Loss 0.00053 (0.00053) Accuracy 0.532 (0.561) +2023-01-14 12:56:32,597 Test: [0/54] Time 11.438 (11.438) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 12:56:58,215 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 12:56:58,215 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 12:56:58,216 | pose_hrnet | 83.025 | 76.474 | 62.237 | 64.577 | 83.946 | 79.495 | 78.137 | 88.910 | 75.778 | 78.900 | +2023-01-14 12:56:58,218 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 12:57:12,689 Epoch: [26][0/214] Time 12.233s (12.233s) Speed 2.6 samples/s Data 11.499s (11.499s) Loss 0.00054 (0.00054) Accuracy 0.530 (0.530) +2023-01-14 12:58:31,126 Epoch: [26][100/214] Time 0.797s (0.898s) Speed 40.2 samples/s Data 0.000s (0.130s) Loss 0.00049 (0.00050) Accuracy 0.634 (0.592) +2023-01-14 12:59:50,728 Epoch: [26][200/214] Time 0.761s (0.847s) Speed 42.0 samples/s Data 0.001s (0.073s) Loss 0.00050 (0.00050) Accuracy 0.597 (0.605) +2023-01-14 13:00:13,571 Test: [0/54] Time 11.341 (11.341) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:00:39,207 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:00:39,208 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:00:39,208 | pose_hrnet | 84.758 | 78.507 | 64.208 | 65.811 | 85.695 | 81.030 | 78.289 | 88.966 | 77.603 | 80.469 | +2023-01-14 13:00:39,210 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:00:53,723 Epoch: [27][0/214] Time 12.307s (12.307s) Speed 2.6 samples/s Data 11.572s (11.572s) Loss 0.00047 (0.00047) Accuracy 0.583 (0.583) +2023-01-14 13:02:12,605 Epoch: [27][100/214] Time 0.788s (0.903s) Speed 40.6 samples/s Data 0.000s (0.130s) Loss 0.00048 (0.00048) Accuracy 0.620 (0.628) +2023-01-14 13:03:32,372 Epoch: [27][200/214] Time 0.784s (0.851s) Speed 40.8 samples/s Data 0.000s (0.074s) Loss 0.00046 (0.00047) Accuracy 0.638 (0.632) +2023-01-14 13:03:55,677 Test: [0/54] Time 11.554 (11.554) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:04:21,358 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:04:21,359 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:04:21,359 | pose_hrnet | 84.877 | 78.838 | 64.331 | 68.578 | 86.359 | 82.108 | 77.905 | 90.319 | 78.723 | 81.219 | +2023-01-14 13:04:21,362 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:04:35,998 Epoch: [28][0/214] Time 12.485s (12.485s) Speed 2.6 samples/s Data 11.724s (11.724s) Loss 0.00047 (0.00047) Accuracy 0.658 (0.658) +2023-01-14 13:05:54,599 Epoch: [28][100/214] Time 0.808s (0.902s) Speed 39.6 samples/s Data 0.000s (0.132s) Loss 0.00044 (0.00047) Accuracy 0.662 (0.640) +2023-01-14 13:07:14,366 Epoch: [28][200/214] Time 0.778s (0.850s) Speed 41.1 samples/s Data 0.000s (0.074s) Loss 0.00042 (0.00047) Accuracy 0.711 (0.641) +2023-01-14 13:07:37,458 Test: [0/54] Time 11.456 (11.456) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:08:03,056 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:08:03,057 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:08:03,058 | pose_hrnet | 83.981 | 77.537 | 64.836 | 66.821 | 85.696 | 82.171 | 77.905 | 88.505 | 76.967 | 79.974 | +2023-01-14 13:08:03,060 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:08:17,280 Epoch: [29][0/214] Time 12.516s (12.516s) Speed 2.6 samples/s Data 11.776s (11.776s) Loss 0.00044 (0.00044) Accuracy 0.681 (0.681) +2023-01-14 13:09:35,758 Epoch: [29][100/214] Time 0.760s (0.901s) Speed 42.1 samples/s Data 0.000s (0.132s) Loss 0.00037 (0.00046) Accuracy 0.701 (0.646) +2023-01-14 13:10:54,960 Epoch: [29][200/214] Time 0.780s (0.847s) Speed 41.0 samples/s Data 0.000s (0.074s) Loss 0.00048 (0.00046) Accuracy 0.626 (0.650) +2023-01-14 13:11:17,896 Test: [0/54] Time 11.308 (11.308) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:11:43,577 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:11:43,578 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:11:43,578 | pose_hrnet | 85.176 | 80.048 | 65.881 | 67.874 | 84.972 | 83.444 | 78.967 | 88.713 | 77.714 | 80.904 | +2023-01-14 13:11:43,581 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:11:57,750 Epoch: [30][0/214] Time 12.492s (12.492s) Speed 2.6 samples/s Data 11.765s (11.765s) Loss 0.00044 (0.00044) Accuracy 0.692 (0.692) +2023-01-14 13:13:16,223 Epoch: [30][100/214] Time 0.792s (0.901s) Speed 40.4 samples/s Data 0.000s (0.132s) Loss 0.00044 (0.00047) Accuracy 0.679 (0.628) +2023-01-14 13:14:35,653 Epoch: [30][200/214] Time 0.786s (0.848s) Speed 40.7 samples/s Data 0.001s (0.075s) Loss 0.00044 (0.00046) Accuracy 0.653 (0.645) +2023-01-14 13:14:58,854 Test: [0/54] Time 11.499 (11.499) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:15:24,490 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:15:24,491 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:15:24,491 | pose_hrnet | 84.937 | 78.528 | 66.051 | 66.439 | 85.636 | 81.085 | 78.366 | 88.247 | 76.943 | 80.173 | +2023-01-14 13:15:24,494 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:15:38,850 Epoch: [31][0/214] Time 12.604s (12.604s) Speed 2.5 samples/s Data 11.852s (11.852s) Loss 0.00053 (0.00053) Accuracy 0.594 (0.594) +2023-01-14 13:16:57,602 Epoch: [31][100/214] Time 0.784s (0.904s) Speed 40.8 samples/s Data 0.000s (0.134s) Loss 0.00051 (0.00045) Accuracy 0.647 (0.660) +2023-01-14 13:18:17,179 Epoch: [31][200/214] Time 0.781s (0.850s) Speed 41.0 samples/s Data 0.000s (0.075s) Loss 0.00048 (0.00044) Accuracy 0.594 (0.669) +2023-01-14 13:18:40,302 Test: [0/54] Time 11.461 (11.461) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:19:05,953 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:19:05,954 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:19:05,954 | pose_hrnet | 83.383 | 78.930 | 66.863 | 67.299 | 84.791 | 80.257 | 78.588 | 88.230 | 76.894 | 80.247 | +2023-01-14 13:19:05,956 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:19:19,827 Epoch: [32][0/214] Time 12.275s (12.275s) Speed 2.6 samples/s Data 11.543s (11.543s) Loss 0.00045 (0.00045) Accuracy 0.648 (0.648) +2023-01-14 13:20:38,328 Epoch: [32][100/214] Time 0.776s (0.899s) Speed 41.2 samples/s Data 0.000s (0.130s) Loss 0.00042 (0.00044) Accuracy 0.691 (0.671) +2023-01-14 13:21:57,951 Epoch: [32][200/214] Time 0.809s (0.848s) Speed 39.6 samples/s Data 0.000s (0.074s) Loss 0.00041 (0.00044) Accuracy 0.692 (0.677) +2023-01-14 13:22:21,061 Test: [0/54] Time 11.452 (11.452) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:22:46,597 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:22:46,598 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:22:46,598 | pose_hrnet | 86.730 | 80.598 | 69.087 | 68.637 | 87.207 | 84.906 | 80.782 | 90.164 | 80.405 | 82.677 | +2023-01-14 13:22:46,600 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:23:00,902 Epoch: [33][0/214] Time 12.051s (12.051s) Speed 2.7 samples/s Data 11.302s (11.302s) Loss 0.00040 (0.00040) Accuracy 0.731 (0.731) +2023-01-14 13:24:19,877 Epoch: [33][100/214] Time 0.806s (0.901s) Speed 39.7 samples/s Data 0.000s (0.128s) Loss 0.00044 (0.00045) Accuracy 0.645 (0.674) +2023-01-14 13:25:39,057 Epoch: [33][200/214] Time 0.808s (0.847s) Speed 39.6 samples/s Data 0.000s (0.072s) Loss 0.00043 (0.00043) Accuracy 0.663 (0.681) +2023-01-14 13:26:02,181 Test: [0/54] Time 11.398 (11.398) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:26:27,834 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:26:27,835 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:26:27,835 | pose_hrnet | 87.029 | 80.982 | 67.791 | 70.292 | 88.775 | 85.096 | 81.463 | 91.212 | 80.407 | 83.205 | +2023-01-14 13:26:27,837 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:26:42,180 Epoch: [34][0/214] Time 12.139s (12.139s) Speed 2.6 samples/s Data 11.405s (11.405s) Loss 0.00042 (0.00042) Accuracy 0.687 (0.687) +2023-01-14 13:28:00,859 Epoch: [34][100/214] Time 0.771s (0.899s) Speed 41.5 samples/s Data 0.000s (0.128s) Loss 0.00043 (0.00043) Accuracy 0.671 (0.693) +2023-01-14 13:29:20,274 Epoch: [34][200/214] Time 0.778s (0.847s) Speed 41.1 samples/s Data 0.001s (0.072s) Loss 0.00040 (0.00042) Accuracy 0.701 (0.695) +2023-01-14 13:29:43,454 Test: [0/54] Time 11.528 (11.528) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:30:09,082 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:30:09,083 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:30:09,083 | pose_hrnet | 85.296 | 79.156 | 68.832 | 67.225 | 87.688 | 82.679 | 79.419 | 88.395 | 79.196 | 81.339 | +2023-01-14 13:30:09,084 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:30:23,262 Epoch: [35][0/214] Time 12.551s (12.551s) Speed 2.5 samples/s Data 11.812s (11.812s) Loss 0.00039 (0.00039) Accuracy 0.727 (0.727) +2023-01-14 13:31:41,768 Epoch: [35][100/214] Time 0.794s (0.902s) Speed 40.3 samples/s Data 0.000s (0.132s) Loss 0.00050 (0.00043) Accuracy 0.625 (0.693) +2023-01-14 13:33:01,398 Epoch: [35][200/214] Time 0.776s (0.849s) Speed 41.2 samples/s Data 0.001s (0.075s) Loss 0.00042 (0.00042) Accuracy 0.711 (0.699) +2023-01-14 13:33:24,078 Test: [0/54] Time 11.008 (11.008) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:33:49,635 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:33:49,635 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:33:49,636 | pose_hrnet | 87.926 | 80.758 | 68.088 | 71.120 | 89.500 | 84.401 | 83.200 | 89.922 | 80.585 | 83.144 | +2023-01-14 13:33:49,637 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:34:03,356 Epoch: [36][0/214] Time 12.172s (12.172s) Speed 2.6 samples/s Data 11.438s (11.438s) Loss 0.00035 (0.00035) Accuracy 0.755 (0.755) +2023-01-14 13:35:21,936 Epoch: [36][100/214] Time 0.787s (0.899s) Speed 40.7 samples/s Data 0.000s (0.129s) Loss 0.00038 (0.00041) Accuracy 0.751 (0.709) +2023-01-14 13:36:41,333 Epoch: [36][200/214] Time 0.775s (0.847s) Speed 41.3 samples/s Data 0.000s (0.072s) Loss 0.00039 (0.00041) Accuracy 0.685 (0.709) +2023-01-14 13:37:04,514 Test: [0/54] Time 11.513 (11.513) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:37:30,121 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:37:30,121 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:37:30,122 | pose_hrnet | 87.507 | 81.339 | 68.949 | 70.736 | 88.411 | 85.986 | 81.461 | 92.465 | 81.419 | 83.973 | +2023-01-14 13:37:30,123 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:37:44,520 Epoch: [37][0/214] Time 12.229s (12.229s) Speed 2.6 samples/s Data 11.481s (11.481s) Loss 0.00046 (0.00046) Accuracy 0.718 (0.718) +2023-01-14 13:39:03,217 Epoch: [37][100/214] Time 0.787s (0.900s) Speed 40.7 samples/s Data 0.000s (0.130s) Loss 0.00050 (0.00044) Accuracy 0.621 (0.678) +2023-01-14 13:40:22,728 Epoch: [37][200/214] Time 0.778s (0.848s) Speed 41.1 samples/s Data 0.000s (0.073s) Loss 0.00040 (0.00042) Accuracy 0.751 (0.698) +2023-01-14 13:40:45,821 Test: [0/54] Time 11.378 (11.378) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:41:11,473 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:41:11,474 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:41:11,474 | pose_hrnet | 87.747 | 83.167 | 70.556 | 73.359 | 89.437 | 85.737 | 83.735 | 92.503 | 82.273 | 84.750 | +2023-01-14 13:41:11,477 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:41:25,982 Epoch: [38][0/214] Time 12.298s (12.298s) Speed 2.6 samples/s Data 11.570s (11.570s) Loss 0.00040 (0.00040) Accuracy 0.719 (0.719) +2023-01-14 13:42:44,645 Epoch: [38][100/214] Time 0.795s (0.901s) Speed 40.3 samples/s Data 0.000s (0.130s) Loss 0.00037 (0.00040) Accuracy 0.709 (0.724) +2023-01-14 13:44:04,156 Epoch: [38][200/214] Time 0.796s (0.848s) Speed 40.2 samples/s Data 0.001s (0.073s) Loss 0.00045 (0.00040) Accuracy 0.739 (0.722) +2023-01-14 13:44:27,222 Test: [0/54] Time 11.486 (11.486) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:44:52,810 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:44:52,811 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:44:52,811 | pose_hrnet | 86.910 | 82.033 | 70.439 | 70.178 | 89.319 | 86.370 | 83.057 | 90.681 | 82.046 | 83.862 | +2023-01-14 13:44:52,813 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:45:06,725 Epoch: [39][0/214] Time 12.227s (12.227s) Speed 2.6 samples/s Data 11.475s (11.475s) Loss 0.00042 (0.00042) Accuracy 0.631 (0.631) +2023-01-14 13:46:25,047 Epoch: [39][100/214] Time 0.781s (0.897s) Speed 41.0 samples/s Data 0.000s (0.129s) Loss 0.00047 (0.00040) Accuracy 0.712 (0.728) +2023-01-14 13:47:44,158 Epoch: [39][200/214] Time 0.780s (0.844s) Speed 41.0 samples/s Data 0.001s (0.073s) Loss 0.00041 (0.00040) Accuracy 0.722 (0.727) +2023-01-14 13:48:07,358 Test: [0/54] Time 11.556 (11.556) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:48:33,082 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:48:33,083 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:48:33,083 | pose_hrnet | 87.747 | 83.273 | 72.039 | 72.792 | 90.103 | 86.241 | 82.141 | 91.193 | 81.546 | 84.510 | +2023-01-14 13:48:33,084 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:48:46,794 Epoch: [40][0/214] Time 12.120s (12.120s) Speed 2.6 samples/s Data 11.360s (11.360s) Loss 0.00041 (0.00041) Accuracy 0.727 (0.727) +2023-01-14 13:50:05,239 Epoch: [40][100/214] Time 0.768s (0.897s) Speed 41.7 samples/s Data 0.000s (0.128s) Loss 0.00043 (0.00040) Accuracy 0.700 (0.728) +2023-01-14 13:51:24,727 Epoch: [40][200/214] Time 0.786s (0.846s) Speed 40.7 samples/s Data 0.001s (0.073s) Loss 0.00040 (0.00039) Accuracy 0.714 (0.736) +2023-01-14 13:51:47,611 Test: [0/54] Time 11.288 (11.288) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:52:13,177 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:52:13,178 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:52:13,178 | pose_hrnet | 88.165 | 81.928 | 72.161 | 73.543 | 90.226 | 87.067 | 84.334 | 92.703 | 82.981 | 85.264 | +2023-01-14 13:52:13,181 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:52:27,804 Epoch: [41][0/214] Time 12.380s (12.380s) Speed 2.6 samples/s Data 11.630s (11.630s) Loss 0.00038 (0.00038) Accuracy 0.706 (0.706) +2023-01-14 13:53:46,375 Epoch: [41][100/214] Time 0.797s (0.900s) Speed 40.2 samples/s Data 0.000s (0.131s) Loss 0.00036 (0.00038) Accuracy 0.771 (0.738) +2023-01-14 13:55:05,689 Epoch: [41][200/214] Time 0.773s (0.847s) Speed 41.4 samples/s Data 0.000s (0.074s) Loss 0.00038 (0.00038) Accuracy 0.787 (0.743) +2023-01-14 13:55:29,048 Test: [0/54] Time 11.756 (11.756) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:55:54,782 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:55:54,782 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:55:54,783 | pose_hrnet | 88.285 | 82.300 | 73.878 | 72.087 | 89.742 | 85.606 | 82.219 | 91.471 | 82.206 | 84.653 | +2023-01-14 13:55:54,784 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:56:08,426 Epoch: [42][0/214] Time 11.991s (11.991s) Speed 2.7 samples/s Data 11.245s (11.245s) Loss 0.00039 (0.00039) Accuracy 0.693 (0.693) +2023-01-14 13:57:26,995 Epoch: [42][100/214] Time 0.786s (0.897s) Speed 40.7 samples/s Data 0.001s (0.127s) Loss 0.00043 (0.00039) Accuracy 0.729 (0.740) +2023-01-14 13:58:46,188 Epoch: [42][200/214] Time 0.778s (0.845s) Speed 41.1 samples/s Data 0.000s (0.072s) Loss 0.00043 (0.00038) Accuracy 0.734 (0.748) +2023-01-14 13:59:09,022 Test: [0/54] Time 11.320 (11.320) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 13:59:34,569 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 13:59:34,569 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 13:59:34,570 | pose_hrnet | 88.464 | 83.654 | 72.282 | 74.680 | 90.223 | 85.730 | 82.368 | 92.589 | 83.195 | 85.352 | +2023-01-14 13:59:34,572 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 13:59:48,800 Epoch: [43][0/214] Time 11.996s (11.996s) Speed 2.7 samples/s Data 11.257s (11.257s) Loss 0.00038 (0.00038) Accuracy 0.773 (0.773) +2023-01-14 14:01:07,536 Epoch: [43][100/214] Time 0.786s (0.898s) Speed 40.7 samples/s Data 0.001s (0.128s) Loss 0.00035 (0.00038) Accuracy 0.733 (0.749) +2023-01-14 14:02:27,020 Epoch: [43][200/214] Time 0.770s (0.847s) Speed 41.6 samples/s Data 0.000s (0.073s) Loss 0.00039 (0.00038) Accuracy 0.763 (0.751) +2023-01-14 14:02:49,957 Test: [0/54] Time 11.327 (11.327) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:03:15,540 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:03:15,540 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:03:15,540 | pose_hrnet | 88.643 | 81.370 | 72.410 | 72.382 | 90.405 | 85.608 | 83.506 | 92.520 | 84.355 | 85.195 | +2023-01-14 14:03:15,542 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:03:29,595 Epoch: [44][0/214] Time 12.318s (12.318s) Speed 2.6 samples/s Data 11.555s (11.555s) Loss 0.00036 (0.00036) Accuracy 0.785 (0.785) +2023-01-14 14:04:48,418 Epoch: [44][100/214] Time 0.760s (0.902s) Speed 42.1 samples/s Data 0.000s (0.130s) Loss 0.00040 (0.00037) Accuracy 0.739 (0.761) +2023-01-14 14:06:07,917 Epoch: [44][200/214] Time 0.775s (0.849s) Speed 41.3 samples/s Data 0.000s (0.073s) Loss 0.00034 (0.00037) Accuracy 0.795 (0.763) +2023-01-14 14:06:31,064 Test: [0/54] Time 11.428 (11.428) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:06:56,788 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:06:56,788 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:06:56,789 | pose_hrnet | 88.822 | 81.484 | 69.754 | 71.776 | 89.741 | 85.665 | 83.652 | 91.784 | 81.569 | 84.186 | +2023-01-14 14:06:56,790 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:07:10,607 Epoch: [45][0/214] Time 12.141s (12.141s) Speed 2.6 samples/s Data 11.393s (11.393s) Loss 0.00039 (0.00039) Accuracy 0.757 (0.757) +2023-01-14 14:08:29,427 Epoch: [45][100/214] Time 0.756s (0.901s) Speed 42.3 samples/s Data 0.000s (0.129s) Loss 0.00037 (0.00037) Accuracy 0.690 (0.762) +2023-01-14 14:09:48,592 Epoch: [45][200/214] Time 0.778s (0.846s) Speed 41.1 samples/s Data 0.000s (0.073s) Loss 0.00032 (0.00037) Accuracy 0.783 (0.764) +2023-01-14 14:10:11,694 Test: [0/54] Time 11.436 (11.436) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:10:37,212 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:10:37,212 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:10:37,213 | pose_hrnet | 89.839 | 83.256 | 74.141 | 73.932 | 91.613 | 86.501 | 84.491 | 93.573 | 84.889 | 86.463 | +2023-01-14 14:10:37,214 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:10:51,449 Epoch: [46][0/214] Time 12.129s (12.129s) Speed 2.6 samples/s Data 11.392s (11.392s) Loss 0.00039 (0.00039) Accuracy 0.732 (0.732) +2023-01-14 14:12:09,835 Epoch: [46][100/214] Time 0.773s (0.896s) Speed 41.4 samples/s Data 0.000s (0.128s) Loss 0.00035 (0.00036) Accuracy 0.726 (0.766) +2023-01-14 14:13:29,285 Epoch: [46][200/214] Time 0.786s (0.846s) Speed 40.7 samples/s Data 0.001s (0.072s) Loss 0.00034 (0.00036) Accuracy 0.786 (0.768) +2023-01-14 14:13:52,456 Test: [0/54] Time 11.533 (11.533) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:14:18,154 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:14:18,155 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:14:18,156 | pose_hrnet | 88.583 | 82.566 | 73.149 | 72.623 | 89.983 | 86.436 | 83.284 | 91.960 | 83.146 | 85.107 | +2023-01-14 14:14:18,158 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:14:31,901 Epoch: [47][0/214] Time 12.172s (12.172s) Speed 2.6 samples/s Data 11.431s (11.431s) Loss 0.00035 (0.00035) Accuracy 0.842 (0.842) +2023-01-14 14:15:50,569 Epoch: [47][100/214] Time 0.805s (0.899s) Speed 39.8 samples/s Data 0.000s (0.129s) Loss 0.00031 (0.00035) Accuracy 0.780 (0.774) +2023-01-14 14:17:09,898 Epoch: [47][200/214] Time 0.760s (0.847s) Speed 42.1 samples/s Data 0.000s (0.073s) Loss 0.00034 (0.00036) Accuracy 0.814 (0.773) +2023-01-14 14:17:32,861 Test: [0/54] Time 11.376 (11.376) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:17:58,566 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:17:58,567 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:17:58,567 | pose_hrnet | 88.105 | 83.117 | 73.272 | 73.684 | 91.735 | 86.052 | 83.881 | 92.094 | 83.633 | 85.472 | +2023-01-14 14:17:58,569 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:18:12,096 Epoch: [48][0/214] Time 11.977s (11.977s) Speed 2.7 samples/s Data 11.230s (11.230s) Loss 0.00037 (0.00037) Accuracy 0.731 (0.731) +2023-01-14 14:19:30,688 Epoch: [48][100/214] Time 0.783s (0.897s) Speed 40.9 samples/s Data 0.001s (0.127s) Loss 0.00032 (0.00036) Accuracy 0.833 (0.773) +2023-01-14 14:20:50,151 Epoch: [48][200/214] Time 0.776s (0.846s) Speed 41.2 samples/s Data 0.000s (0.071s) Loss 0.00033 (0.00035) Accuracy 0.760 (0.775) +2023-01-14 14:21:13,160 Test: [0/54] Time 11.384 (11.384) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:21:38,917 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:21:38,917 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:21:38,918 | pose_hrnet | 89.659 | 83.835 | 72.970 | 74.587 | 90.345 | 86.691 | 83.508 | 92.125 | 83.368 | 85.551 | +2023-01-14 14:21:38,919 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:21:52,898 Epoch: [49][0/214] Time 12.283s (12.283s) Speed 2.6 samples/s Data 11.532s (11.532s) Loss 0.00035 (0.00035) Accuracy 0.772 (0.772) +2023-01-14 14:23:11,228 Epoch: [49][100/214] Time 0.788s (0.897s) Speed 40.6 samples/s Data 0.001s (0.130s) Loss 0.00039 (0.00035) Accuracy 0.737 (0.783) +2023-01-14 14:24:30,654 Epoch: [49][200/214] Time 0.773s (0.846s) Speed 41.4 samples/s Data 0.001s (0.073s) Loss 0.00034 (0.00035) Accuracy 0.772 (0.781) +2023-01-14 14:24:53,948 Test: [0/54] Time 11.561 (11.561) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:25:19,639 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:25:19,640 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:25:19,640 | pose_hrnet | 89.958 | 84.098 | 72.960 | 73.501 | 91.794 | 85.159 | 84.485 | 93.017 | 84.323 | 86.028 | +2023-01-14 14:25:19,643 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:25:33,802 Epoch: [50][0/214] Time 12.508s (12.508s) Speed 2.6 samples/s Data 11.789s (11.789s) Loss 0.00038 (0.00038) Accuracy 0.761 (0.761) +2023-01-14 14:26:52,516 Epoch: [50][100/214] Time 0.775s (0.903s) Speed 41.3 samples/s Data 0.000s (0.132s) Loss 0.00032 (0.00035) Accuracy 0.785 (0.777) +2023-01-14 14:28:11,962 Epoch: [50][200/214] Time 0.777s (0.849s) Speed 41.2 samples/s Data 0.000s (0.074s) Loss 0.00032 (0.00035) Accuracy 0.761 (0.783) +2023-01-14 14:28:35,069 Test: [0/54] Time 11.406 (11.406) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:29:00,776 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:29:00,777 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:29:00,777 | pose_hrnet | 83.981 | 78.697 | 67.872 | 69.574 | 85.637 | 80.636 | 78.964 | 86.124 | 79.133 | 80.367 | +2023-01-14 14:29:00,779 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:29:14,926 Epoch: [51][0/214] Time 12.453s (12.453s) Speed 2.6 samples/s Data 11.702s (11.702s) Loss 0.00033 (0.00033) Accuracy 0.801 (0.801) +2023-01-14 14:30:33,761 Epoch: [51][100/214] Time 0.774s (0.904s) Speed 41.3 samples/s Data 0.000s (0.132s) Loss 0.00031 (0.00034) Accuracy 0.813 (0.789) +2023-01-14 14:31:53,161 Epoch: [51][200/214] Time 0.776s (0.849s) Speed 41.2 samples/s Data 0.000s (0.074s) Loss 0.00030 (0.00034) Accuracy 0.824 (0.790) +2023-01-14 14:32:16,171 Test: [0/54] Time 11.388 (11.388) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:32:41,797 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:32:41,798 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:32:41,798 | pose_hrnet | 90.556 | 84.447 | 75.371 | 76.846 | 92.337 | 87.900 | 83.881 | 93.587 | 85.199 | 86.995 | +2023-01-14 14:32:41,801 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:32:56,458 Epoch: [52][0/214] Time 12.405s (12.405s) Speed 2.6 samples/s Data 11.666s (11.666s) Loss 0.00036 (0.00036) Accuracy 0.814 (0.814) +2023-01-14 14:34:14,809 Epoch: [52][100/214] Time 0.788s (0.899s) Speed 40.6 samples/s Data 0.000s (0.131s) Loss 0.00031 (0.00033) Accuracy 0.801 (0.798) +2023-01-14 14:35:34,419 Epoch: [52][200/214] Time 0.790s (0.848s) Speed 40.5 samples/s Data 0.000s (0.074s) Loss 0.00035 (0.00033) Accuracy 0.781 (0.800) +2023-01-14 14:35:57,422 Test: [0/54] Time 11.343 (11.343) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:36:22,990 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:36:22,990 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:36:22,991 | pose_hrnet | 88.344 | 84.010 | 75.674 | 77.121 | 91.732 | 86.314 | 84.113 | 92.213 | 84.444 | 86.199 | +2023-01-14 14:36:22,993 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:36:36,930 Epoch: [53][0/214] Time 12.376s (12.376s) Speed 2.6 samples/s Data 11.638s (11.638s) Loss 0.00032 (0.00032) Accuracy 0.830 (0.830) +2023-01-14 14:37:55,641 Epoch: [53][100/214] Time 0.779s (0.902s) Speed 41.1 samples/s Data 0.000s (0.131s) Loss 0.00037 (0.00033) Accuracy 0.805 (0.802) +2023-01-14 14:39:15,050 Epoch: [53][200/214] Time 0.784s (0.848s) Speed 40.8 samples/s Data 0.000s (0.074s) Loss 0.00033 (0.00033) Accuracy 0.801 (0.799) +2023-01-14 14:39:38,214 Test: [0/54] Time 11.511 (11.511) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:40:03,901 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:40:03,901 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:40:03,902 | pose_hrnet | 90.137 | 83.805 | 75.059 | 75.514 | 90.524 | 86.372 | 84.268 | 92.337 | 84.329 | 86.254 | +2023-01-14 14:40:03,904 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:40:18,035 Epoch: [54][0/214] Time 12.428s (12.428s) Speed 2.6 samples/s Data 11.692s (11.692s) Loss 0.00031 (0.00031) Accuracy 0.805 (0.805) +2023-01-14 14:41:36,289 Epoch: [54][100/214] Time 0.777s (0.898s) Speed 41.2 samples/s Data 0.000s (0.131s) Loss 0.00036 (0.00033) Accuracy 0.780 (0.805) +2023-01-14 14:42:55,704 Epoch: [54][200/214] Time 0.779s (0.846s) Speed 41.1 samples/s Data 0.001s (0.074s) Loss 0.00033 (0.00032) Accuracy 0.816 (0.806) +2023-01-14 14:43:18,485 Test: [0/54] Time 11.072 (11.072) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:43:44,116 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:43:44,117 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:43:44,117 | pose_hrnet | 90.137 | 84.317 | 74.250 | 73.792 | 90.767 | 87.205 | 83.808 | 92.589 | 84.919 | 86.356 | +2023-01-14 14:43:44,118 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:43:57,736 Epoch: [55][0/214] Time 12.017s (12.017s) Speed 2.7 samples/s Data 11.296s (11.296s) Loss 0.00030 (0.00030) Accuracy 0.848 (0.848) +2023-01-14 14:45:16,269 Epoch: [55][100/214] Time 0.772s (0.897s) Speed 41.5 samples/s Data 0.000s (0.127s) Loss 0.00033 (0.00032) Accuracy 0.758 (0.815) +2023-01-14 14:46:35,657 Epoch: [55][200/214] Time 0.794s (0.845s) Speed 40.3 samples/s Data 0.000s (0.072s) Loss 0.00038 (0.00032) Accuracy 0.752 (0.814) +2023-01-14 14:46:58,774 Test: [0/54] Time 11.525 (11.525) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:47:24,436 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:47:24,436 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:47:24,436 | pose_hrnet | 90.137 | 84.159 | 74.072 | 74.883 | 90.948 | 86.884 | 85.624 | 92.400 | 84.206 | 86.208 | +2023-01-14 14:47:24,438 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:47:38,414 Epoch: [56][0/214] Time 12.375s (12.375s) Speed 2.6 samples/s Data 11.638s (11.638s) Loss 0.00030 (0.00030) Accuracy 0.796 (0.796) +2023-01-14 14:48:57,177 Epoch: [56][100/214] Time 0.785s (0.902s) Speed 40.8 samples/s Data 0.001s (0.133s) Loss 0.00030 (0.00031) Accuracy 0.828 (0.820) +2023-01-14 14:50:16,457 Epoch: [56][200/214] Time 0.776s (0.848s) Speed 41.2 samples/s Data 0.000s (0.075s) Loss 0.00032 (0.00032) Accuracy 0.807 (0.812) +2023-01-14 14:50:39,234 Test: [0/54] Time 11.199 (11.199) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:51:04,870 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:51:04,871 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:51:04,872 | pose_hrnet | 89.779 | 84.921 | 75.502 | 76.202 | 91.492 | 87.833 | 84.565 | 93.732 | 86.798 | 87.148 | +2023-01-14 14:51:04,874 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:51:19,722 Epoch: [57][0/214] Time 12.521s (12.521s) Speed 2.6 samples/s Data 11.766s (11.766s) Loss 0.00029 (0.00029) Accuracy 0.816 (0.816) +2023-01-14 14:52:38,237 Epoch: [57][100/214] Time 0.770s (0.901s) Speed 41.6 samples/s Data 0.000s (0.133s) Loss 0.00029 (0.00032) Accuracy 0.869 (0.818) +2023-01-14 14:53:57,907 Epoch: [57][200/214] Time 0.787s (0.849s) Speed 40.7 samples/s Data 0.000s (0.075s) Loss 0.00028 (0.00031) Accuracy 0.840 (0.821) +2023-01-14 14:54:20,971 Test: [0/54] Time 11.385 (11.385) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:54:46,739 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:54:46,739 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:54:46,740 | pose_hrnet | 89.241 | 82.734 | 74.440 | 74.951 | 91.069 | 86.307 | 84.718 | 91.851 | 83.226 | 85.477 | +2023-01-14 14:54:46,741 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:55:00,308 Epoch: [58][0/214] Time 11.893s (11.893s) Speed 2.7 samples/s Data 11.151s (11.151s) Loss 0.00029 (0.00029) Accuracy 0.885 (0.885) +2023-01-14 14:56:18,828 Epoch: [58][100/214] Time 0.777s (0.895s) Speed 41.2 samples/s Data 0.001s (0.126s) Loss 0.00029 (0.00031) Accuracy 0.898 (0.826) +2023-01-14 14:57:38,358 Epoch: [58][200/214] Time 0.768s (0.845s) Speed 41.7 samples/s Data 0.000s (0.071s) Loss 0.00030 (0.00031) Accuracy 0.835 (0.819) +2023-01-14 14:58:01,415 Test: [0/54] Time 11.425 (11.425) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 14:58:27,095 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 14:58:27,096 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 14:58:27,096 | pose_hrnet | 90.675 | 85.809 | 76.780 | 78.391 | 92.938 | 87.516 | 85.696 | 94.189 | 86.315 | 87.823 | +2023-01-14 14:58:27,097 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 14:58:41,252 Epoch: [59][0/214] Time 12.043s (12.043s) Speed 2.7 samples/s Data 11.292s (11.292s) Loss 0.00028 (0.00028) Accuracy 0.862 (0.862) +2023-01-14 14:59:59,904 Epoch: [59][100/214] Time 0.779s (0.898s) Speed 41.1 samples/s Data 0.000s (0.128s) Loss 0.00030 (0.00032) Accuracy 0.807 (0.816) +2023-01-14 15:01:19,493 Epoch: [59][200/214] Time 0.775s (0.847s) Speed 41.3 samples/s Data 0.000s (0.072s) Loss 0.00029 (0.00031) Accuracy 0.863 (0.819) +2023-01-14 15:01:42,397 Test: [0/54] Time 11.302 (11.302) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:02:08,093 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:02:08,094 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:02:08,094 | pose_hrnet | 89.659 | 83.209 | 73.282 | 75.508 | 90.888 | 87.263 | 84.030 | 93.047 | 83.562 | 85.856 | +2023-01-14 15:02:08,096 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:02:21,917 Epoch: [60][0/214] Time 12.222s (12.222s) Speed 2.6 samples/s Data 11.441s (11.441s) Loss 0.00032 (0.00032) Accuracy 0.830 (0.830) +2023-01-14 15:03:40,856 Epoch: [60][100/214] Time 0.758s (0.903s) Speed 42.2 samples/s Data 0.000s (0.129s) Loss 0.00029 (0.00032) Accuracy 0.808 (0.810) +2023-01-14 15:05:00,406 Epoch: [60][200/214] Time 0.776s (0.849s) Speed 41.2 samples/s Data 0.001s (0.073s) Loss 0.00031 (0.00032) Accuracy 0.829 (0.816) +2023-01-14 15:05:23,299 Test: [0/54] Time 11.213 (11.213) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:05:48,950 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:05:48,950 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:05:48,951 | pose_hrnet | 89.301 | 85.649 | 75.060 | 77.009 | 92.999 | 87.837 | 85.548 | 93.915 | 85.454 | 87.305 | +2023-01-14 15:05:48,952 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:06:02,587 Epoch: [61][0/214] Time 12.015s (12.015s) Speed 2.7 samples/s Data 11.270s (11.270s) Loss 0.00029 (0.00029) Accuracy 0.854 (0.854) +2023-01-14 15:07:21,508 Epoch: [61][100/214] Time 0.759s (0.900s) Speed 42.2 samples/s Data 0.000s (0.127s) Loss 0.00026 (0.00031) Accuracy 0.836 (0.821) +2023-01-14 15:08:40,961 Epoch: [61][200/214] Time 0.782s (0.848s) Speed 40.9 samples/s Data 0.000s (0.072s) Loss 0.00031 (0.00031) Accuracy 0.824 (0.826) +2023-01-14 15:09:03,922 Test: [0/54] Time 11.291 (11.291) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:09:29,645 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:09:29,645 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:09:29,646 | pose_hrnet | 88.703 | 83.740 | 74.324 | 76.612 | 90.587 | 86.116 | 83.732 | 91.426 | 83.171 | 85.445 | +2023-01-14 15:09:29,647 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:09:43,564 Epoch: [62][0/214] Time 12.372s (12.372s) Speed 2.6 samples/s Data 11.636s (11.636s) Loss 0.00032 (0.00032) Accuracy 0.819 (0.819) +2023-01-14 15:11:02,363 Epoch: [62][100/214] Time 0.776s (0.903s) Speed 41.2 samples/s Data 0.000s (0.131s) Loss 0.00032 (0.00030) Accuracy 0.779 (0.829) +2023-01-14 15:12:21,868 Epoch: [62][200/214] Time 0.760s (0.849s) Speed 42.1 samples/s Data 0.000s (0.074s) Loss 0.00030 (0.00030) Accuracy 0.831 (0.833) +2023-01-14 15:12:44,894 Test: [0/54] Time 11.444 (11.444) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:13:10,712 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:13:10,712 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:13:10,712 | pose_hrnet | 90.915 | 84.355 | 76.179 | 78.083 | 92.579 | 88.469 | 85.621 | 93.600 | 86.152 | 87.476 | +2023-01-14 15:13:10,714 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:13:24,613 Epoch: [63][0/214] Time 12.172s (12.172s) Speed 2.6 samples/s Data 11.421s (11.421s) Loss 0.00031 (0.00031) Accuracy 0.832 (0.832) +2023-01-14 15:14:43,158 Epoch: [63][100/214] Time 0.775s (0.898s) Speed 41.3 samples/s Data 0.000s (0.129s) Loss 0.00028 (0.00030) Accuracy 0.853 (0.836) +2023-01-14 15:16:02,418 Epoch: [63][200/214] Time 0.778s (0.846s) Speed 41.1 samples/s Data 0.000s (0.072s) Loss 0.00031 (0.00030) Accuracy 0.864 (0.838) +2023-01-14 15:16:25,678 Test: [0/54] Time 11.606 (11.606) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:16:51,417 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:16:51,417 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:16:51,418 | pose_hrnet | 89.002 | 85.011 | 75.124 | 78.296 | 89.318 | 84.782 | 83.281 | 92.782 | 86.076 | 86.472 | +2023-01-14 15:16:51,419 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:17:05,337 Epoch: [64][0/214] Time 12.210s (12.210s) Speed 2.6 samples/s Data 11.481s (11.481s) Loss 0.00032 (0.00032) Accuracy 0.792 (0.792) +2023-01-14 15:18:23,878 Epoch: [64][100/214] Time 0.760s (0.899s) Speed 42.1 samples/s Data 0.001s (0.129s) Loss 0.00031 (0.00031) Accuracy 0.823 (0.827) +2023-01-14 15:19:43,320 Epoch: [64][200/214] Time 0.784s (0.847s) Speed 40.8 samples/s Data 0.001s (0.073s) Loss 0.00029 (0.00030) Accuracy 0.807 (0.835) +2023-01-14 15:20:06,405 Test: [0/54] Time 11.394 (11.394) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:20:32,068 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:20:32,069 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:20:32,069 | pose_hrnet | 89.480 | 85.660 | 76.302 | 78.296 | 91.490 | 87.518 | 83.962 | 93.449 | 85.858 | 87.180 | +2023-01-14 15:20:32,071 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:20:45,960 Epoch: [65][0/214] Time 12.064s (12.064s) Speed 2.7 samples/s Data 11.336s (11.336s) Loss 0.00027 (0.00027) Accuracy 0.882 (0.882) +2023-01-14 15:22:04,734 Epoch: [65][100/214] Time 0.778s (0.899s) Speed 41.1 samples/s Data 0.000s (0.128s) Loss 0.00028 (0.00029) Accuracy 0.820 (0.839) +2023-01-14 15:23:24,260 Epoch: [65][200/214] Time 0.772s (0.848s) Speed 41.5 samples/s Data 0.000s (0.073s) Loss 0.00030 (0.00029) Accuracy 0.827 (0.840) +2023-01-14 15:23:46,879 Test: [0/54] Time 11.000 (11.000) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:24:12,520 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:24:12,520 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:24:12,521 | pose_hrnet | 90.377 | 84.925 | 75.922 | 78.767 | 90.163 | 87.135 | 85.768 | 92.806 | 85.685 | 87.088 | +2023-01-14 15:24:12,522 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:24:26,664 Epoch: [66][0/214] Time 12.544s (12.544s) Speed 2.6 samples/s Data 11.808s (11.808s) Loss 0.00024 (0.00024) Accuracy 0.859 (0.859) +2023-01-14 15:25:45,298 Epoch: [66][100/214] Time 0.784s (0.903s) Speed 40.8 samples/s Data 0.000s (0.133s) Loss 0.00024 (0.00029) Accuracy 0.902 (0.843) +2023-01-14 15:27:04,941 Epoch: [66][200/214] Time 0.781s (0.850s) Speed 41.0 samples/s Data 0.000s (0.075s) Loss 0.00028 (0.00029) Accuracy 0.831 (0.845) +2023-01-14 15:27:27,986 Test: [0/54] Time 11.437 (11.437) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:27:53,731 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:27:53,732 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:27:53,732 | pose_hrnet | 84.579 | 79.977 | 72.672 | 72.558 | 86.482 | 81.788 | 80.851 | 88.208 | 80.941 | 82.196 | +2023-01-14 15:27:53,735 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:28:07,305 Epoch: [67][0/214] Time 11.970s (11.970s) Speed 2.7 samples/s Data 11.207s (11.207s) Loss 0.00028 (0.00028) Accuracy 0.858 (0.858) +2023-01-14 15:29:25,829 Epoch: [67][100/214] Time 0.783s (0.896s) Speed 40.9 samples/s Data 0.001s (0.127s) Loss 0.00029 (0.00029) Accuracy 0.823 (0.837) +2023-01-14 15:30:45,305 Epoch: [67][200/214] Time 0.785s (0.846s) Speed 40.8 samples/s Data 0.001s (0.072s) Loss 0.00030 (0.00029) Accuracy 0.822 (0.844) +2023-01-14 15:31:08,255 Test: [0/54] Time 11.277 (11.277) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:31:33,992 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:31:33,992 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:31:33,993 | pose_hrnet | 89.958 | 84.085 | 74.512 | 75.766 | 91.311 | 86.691 | 84.411 | 92.156 | 85.332 | 86.338 | +2023-01-14 15:31:33,996 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:31:47,860 Epoch: [68][0/214] Time 12.169s (12.169s) Speed 2.6 samples/s Data 11.437s (11.437s) Loss 0.00023 (0.00023) Accuracy 0.923 (0.923) +2023-01-14 15:33:06,683 Epoch: [68][100/214] Time 0.805s (0.901s) Speed 39.8 samples/s Data 0.001s (0.129s) Loss 0.00028 (0.00028) Accuracy 0.874 (0.851) +2023-01-14 15:34:25,907 Epoch: [68][200/214] Time 0.776s (0.847s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00028 (0.00028) Accuracy 0.839 (0.848) +2023-01-14 15:34:48,867 Test: [0/54] Time 11.413 (11.413) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:35:14,604 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:35:14,605 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:35:14,605 | pose_hrnet | 88.763 | 82.652 | 72.538 | 75.567 | 91.551 | 87.329 | 84.332 | 92.660 | 85.293 | 85.824 | +2023-01-14 15:35:14,607 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:35:28,625 Epoch: [69][0/214] Time 12.344s (12.344s) Speed 2.6 samples/s Data 11.611s (11.611s) Loss 0.00030 (0.00030) Accuracy 0.828 (0.828) +2023-01-14 15:36:47,204 Epoch: [69][100/214] Time 0.799s (0.900s) Speed 40.1 samples/s Data 0.000s (0.130s) Loss 0.00028 (0.00030) Accuracy 0.838 (0.834) +2023-01-14 15:38:06,986 Epoch: [69][200/214] Time 0.778s (0.849s) Speed 41.1 samples/s Data 0.001s (0.073s) Loss 0.00032 (0.00029) Accuracy 0.784 (0.839) +2023-01-14 15:38:29,813 Test: [0/54] Time 11.152 (11.152) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:38:55,500 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:38:55,501 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:38:55,502 | pose_hrnet | 90.496 | 86.274 | 76.163 | 77.964 | 93.543 | 89.172 | 86.077 | 93.812 | 87.090 | 88.078 | +2023-01-14 15:38:55,504 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:39:09,389 Epoch: [70][0/214] Time 11.663s (11.663s) Speed 2.7 samples/s Data 10.912s (10.912s) Loss 0.00028 (0.00028) Accuracy 0.853 (0.853) +2023-01-14 15:40:28,252 Epoch: [70][100/214] Time 0.781s (0.896s) Speed 41.0 samples/s Data 0.000s (0.124s) Loss 0.00027 (0.00028) Accuracy 0.877 (0.852) +2023-01-14 15:41:47,671 Epoch: [70][200/214] Time 0.762s (0.845s) Speed 42.0 samples/s Data 0.000s (0.070s) Loss 0.00026 (0.00028) Accuracy 0.875 (0.854) +2023-01-14 15:42:10,926 Test: [0/54] Time 11.646 (11.646) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:42:36,587 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:42:36,588 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:42:36,588 | pose_hrnet | 91.154 | 85.331 | 77.466 | 80.006 | 93.059 | 90.010 | 87.213 | 94.765 | 87.400 | 88.749 | +2023-01-14 15:42:36,591 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:42:50,765 Epoch: [71][0/214] Time 11.852s (11.852s) Speed 2.7 samples/s Data 11.123s (11.123s) Loss 0.00028 (0.00028) Accuracy 0.868 (0.868) +2023-01-14 15:44:09,475 Epoch: [71][100/214] Time 0.774s (0.897s) Speed 41.3 samples/s Data 0.000s (0.126s) Loss 0.00029 (0.00028) Accuracy 0.851 (0.853) +2023-01-14 15:45:28,883 Epoch: [71][200/214] Time 0.771s (0.846s) Speed 41.5 samples/s Data 0.000s (0.071s) Loss 0.00027 (0.00028) Accuracy 0.847 (0.856) +2023-01-14 15:45:52,066 Test: [0/54] Time 11.573 (11.573) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:46:17,725 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:46:17,726 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:46:17,726 | pose_hrnet | 82.247 | 78.857 | 71.176 | 72.046 | 86.303 | 83.752 | 78.045 | 83.487 | 80.828 | 80.543 | +2023-01-14 15:46:17,727 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:46:31,684 Epoch: [72][0/214] Time 12.398s (12.398s) Speed 2.6 samples/s Data 11.636s (11.636s) Loss 0.00032 (0.00032) Accuracy 0.827 (0.827) +2023-01-14 15:47:50,130 Epoch: [72][100/214] Time 0.775s (0.899s) Speed 41.3 samples/s Data 0.000s (0.131s) Loss 0.00023 (0.00028) Accuracy 0.869 (0.856) +2023-01-14 15:49:09,411 Epoch: [72][200/214] Time 0.777s (0.846s) Speed 41.2 samples/s Data 0.000s (0.074s) Loss 0.00030 (0.00027) Accuracy 0.858 (0.859) +2023-01-14 15:49:32,484 Test: [0/54] Time 11.447 (11.447) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:49:58,206 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:49:58,207 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:49:58,207 | pose_hrnet | 90.795 | 84.862 | 76.402 | 79.046 | 92.276 | 89.746 | 86.837 | 93.495 | 87.223 | 87.967 | +2023-01-14 15:49:58,209 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:50:11,943 Epoch: [73][0/214] Time 12.127s (12.127s) Speed 2.6 samples/s Data 11.394s (11.394s) Loss 0.00026 (0.00026) Accuracy 0.855 (0.855) +2023-01-14 15:51:30,563 Epoch: [73][100/214] Time 0.807s (0.898s) Speed 39.7 samples/s Data 0.000s (0.129s) Loss 0.00027 (0.00027) Accuracy 0.873 (0.863) +2023-01-14 15:52:49,709 Epoch: [73][200/214] Time 0.759s (0.845s) Speed 42.2 samples/s Data 0.000s (0.073s) Loss 0.00028 (0.00027) Accuracy 0.847 (0.861) +2023-01-14 15:53:12,949 Test: [0/54] Time 11.492 (11.492) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:53:38,626 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:53:38,626 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:53:38,627 | pose_hrnet | 92.170 | 85.136 | 78.567 | 79.395 | 93.000 | 88.786 | 87.663 | 94.831 | 88.068 | 88.805 | +2023-01-14 15:53:38,629 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:53:53,129 Epoch: [74][0/214] Time 12.273s (12.273s) Speed 2.6 samples/s Data 11.543s (11.543s) Loss 0.00027 (0.00027) Accuracy 0.847 (0.847) +2023-01-14 15:55:11,566 Epoch: [74][100/214] Time 0.777s (0.898s) Speed 41.2 samples/s Data 0.001s (0.130s) Loss 0.00026 (0.00027) Accuracy 0.856 (0.865) +2023-01-14 15:56:31,249 Epoch: [74][200/214] Time 0.777s (0.848s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00023 (0.00027) Accuracy 0.885 (0.867) +2023-01-14 15:56:54,212 Test: [0/54] Time 11.355 (11.355) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 15:57:19,867 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 15:57:19,867 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 15:57:19,868 | pose_hrnet | 91.393 | 87.181 | 78.019 | 80.207 | 94.329 | 90.128 | 87.747 | 94.977 | 87.965 | 89.286 | +2023-01-14 15:57:19,870 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 15:57:34,539 Epoch: [75][0/214] Time 12.339s (12.339s) Speed 2.6 samples/s Data 11.596s (11.596s) Loss 0.00025 (0.00025) Accuracy 0.849 (0.849) +2023-01-14 15:58:52,949 Epoch: [75][100/214] Time 0.764s (0.899s) Speed 41.9 samples/s Data 0.000s (0.131s) Loss 0.00025 (0.00027) Accuracy 0.892 (0.863) +2023-01-14 16:00:12,471 Epoch: [75][200/214] Time 0.777s (0.847s) Speed 41.2 samples/s Data 0.001s (0.075s) Loss 0.00021 (0.00027) Accuracy 0.932 (0.865) +2023-01-14 16:00:35,677 Test: [0/54] Time 11.399 (11.399) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:01:01,411 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:01:01,412 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:01:01,412 | pose_hrnet | 91.811 | 86.542 | 77.784 | 80.695 | 94.507 | 90.959 | 86.765 | 95.793 | 88.919 | 89.587 | +2023-01-14 16:01:01,414 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:01:16,074 Epoch: [76][0/214] Time 12.533s (12.533s) Speed 2.6 samples/s Data 11.795s (11.795s) Loss 0.00028 (0.00028) Accuracy 0.848 (0.848) +2023-01-14 16:02:34,849 Epoch: [76][100/214] Time 0.772s (0.904s) Speed 41.5 samples/s Data 0.000s (0.132s) Loss 0.00023 (0.00026) Accuracy 0.913 (0.874) +2023-01-14 16:03:54,392 Epoch: [76][200/214] Time 0.763s (0.850s) Speed 41.9 samples/s Data 0.000s (0.075s) Loss 0.00023 (0.00026) Accuracy 0.913 (0.870) +2023-01-14 16:04:17,447 Test: [0/54] Time 11.345 (11.345) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:04:43,106 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:04:43,106 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:04:43,107 | pose_hrnet | 92.349 | 86.893 | 79.373 | 80.031 | 93.423 | 89.106 | 88.803 | 95.408 | 87.368 | 89.346 | +2023-01-14 16:04:43,109 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:04:56,963 Epoch: [77][0/214] Time 12.225s (12.225s) Speed 2.6 samples/s Data 11.481s (11.481s) Loss 0.00026 (0.00026) Accuracy 0.855 (0.855) +2023-01-14 16:06:15,426 Epoch: [77][100/214] Time 0.793s (0.898s) Speed 40.4 samples/s Data 0.000s (0.129s) Loss 0.00025 (0.00026) Accuracy 0.899 (0.872) +2023-01-14 16:07:34,614 Epoch: [77][200/214] Time 0.776s (0.845s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00031 (0.00026) Accuracy 0.854 (0.874) +2023-01-14 16:07:57,586 Test: [0/54] Time 11.344 (11.344) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:08:23,161 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:08:23,162 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:08:23,162 | pose_hrnet | 92.588 | 85.723 | 77.213 | 78.899 | 93.844 | 88.535 | 86.989 | 94.957 | 88.284 | 88.818 | +2023-01-14 16:08:23,164 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:08:37,219 Epoch: [78][0/214] Time 12.479s (12.479s) Speed 2.6 samples/s Data 11.727s (11.727s) Loss 0.00022 (0.00022) Accuracy 0.871 (0.871) +2023-01-14 16:09:56,148 Epoch: [78][100/214] Time 0.773s (0.905s) Speed 41.4 samples/s Data 0.001s (0.132s) Loss 0.00025 (0.00026) Accuracy 0.831 (0.872) +2023-01-14 16:11:15,655 Epoch: [78][200/214] Time 0.783s (0.850s) Speed 40.9 samples/s Data 0.000s (0.075s) Loss 0.00024 (0.00026) Accuracy 0.909 (0.872) +2023-01-14 16:11:38,634 Test: [0/54] Time 11.235 (11.235) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:12:04,350 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:12:04,350 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:12:04,351 | pose_hrnet | 90.436 | 85.879 | 78.079 | 79.879 | 93.059 | 87.962 | 87.436 | 93.094 | 88.320 | 88.416 | +2023-01-14 16:12:04,353 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:12:18,204 Epoch: [79][0/214] Time 12.221s (12.221s) Speed 2.6 samples/s Data 11.496s (11.496s) Loss 0.00026 (0.00026) Accuracy 0.846 (0.846) +2023-01-14 16:13:36,909 Epoch: [79][100/214] Time 0.786s (0.900s) Speed 40.7 samples/s Data 0.001s (0.129s) Loss 0.00022 (0.00025) Accuracy 0.900 (0.875) +2023-01-14 16:14:56,147 Epoch: [79][200/214] Time 0.790s (0.847s) Speed 40.5 samples/s Data 0.001s (0.072s) Loss 0.00027 (0.00026) Accuracy 0.854 (0.872) +2023-01-14 16:15:19,266 Test: [0/54] Time 11.396 (11.396) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:15:44,836 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:15:44,837 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:15:44,838 | pose_hrnet | 89.002 | 84.384 | 74.698 | 77.985 | 91.913 | 86.369 | 86.447 | 91.805 | 84.851 | 86.375 | +2023-01-14 16:15:44,840 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:15:58,862 Epoch: [80][0/214] Time 12.336s (12.336s) Speed 2.6 samples/s Data 11.605s (11.605s) Loss 0.00025 (0.00025) Accuracy 0.890 (0.890) +2023-01-14 16:17:17,279 Epoch: [80][100/214] Time 0.761s (0.899s) Speed 42.0 samples/s Data 0.000s (0.131s) Loss 0.00026 (0.00026) Accuracy 0.867 (0.871) +2023-01-14 16:18:36,775 Epoch: [80][200/214] Time 0.797s (0.847s) Speed 40.2 samples/s Data 0.000s (0.074s) Loss 0.00026 (0.00026) Accuracy 0.841 (0.872) +2023-01-14 16:19:00,065 Test: [0/54] Time 11.599 (11.599) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:19:25,688 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:19:25,689 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:19:25,690 | pose_hrnet | 90.795 | 86.079 | 75.246 | 79.661 | 92.757 | 88.665 | 87.590 | 93.837 | 87.277 | 88.092 | +2023-01-14 16:19:25,692 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:19:40,072 Epoch: [81][0/214] Time 12.590s (12.590s) Speed 2.5 samples/s Data 11.842s (11.842s) Loss 0.00022 (0.00022) Accuracy 0.894 (0.894) +2023-01-14 16:20:58,200 Epoch: [81][100/214] Time 0.784s (0.898s) Speed 40.8 samples/s Data 0.000s (0.133s) Loss 0.00028 (0.00025) Accuracy 0.837 (0.879) +2023-01-14 16:22:17,596 Epoch: [81][200/214] Time 0.777s (0.846s) Speed 41.2 samples/s Data 0.000s (0.075s) Loss 0.00025 (0.00025) Accuracy 0.853 (0.877) +2023-01-14 16:22:40,141 Test: [0/54] Time 10.976 (10.976) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:23:05,792 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:23:05,792 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:23:05,793 | pose_hrnet | 91.931 | 84.628 | 77.532 | 81.395 | 92.698 | 89.814 | 87.667 | 95.085 | 88.380 | 89.184 | +2023-01-14 16:23:05,795 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:23:19,681 Epoch: [82][0/214] Time 12.196s (12.196s) Speed 2.6 samples/s Data 11.454s (11.454s) Loss 0.00023 (0.00023) Accuracy 0.867 (0.867) +2023-01-14 16:24:38,143 Epoch: [82][100/214] Time 0.795s (0.898s) Speed 40.3 samples/s Data 0.000s (0.129s) Loss 0.00026 (0.00026) Accuracy 0.844 (0.873) +2023-01-14 16:25:57,529 Epoch: [82][200/214] Time 0.776s (0.846s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00025 (0.00026) Accuracy 0.891 (0.873) +2023-01-14 16:26:20,615 Test: [0/54] Time 11.440 (11.440) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:26:46,278 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:26:46,278 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:26:46,278 | pose_hrnet | 91.273 | 84.506 | 76.356 | 78.281 | 93.363 | 88.280 | 87.138 | 93.756 | 86.717 | 87.819 | +2023-01-14 16:26:46,281 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:26:59,987 Epoch: [83][0/214] Time 12.130s (12.130s) Speed 2.6 samples/s Data 11.378s (11.378s) Loss 0.00026 (0.00026) Accuracy 0.876 (0.876) +2023-01-14 16:28:18,552 Epoch: [83][100/214] Time 0.775s (0.898s) Speed 41.3 samples/s Data 0.001s (0.128s) Loss 0.00021 (0.00025) Accuracy 0.929 (0.880) +2023-01-14 16:29:37,795 Epoch: [83][200/214] Time 0.777s (0.845s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00030 (0.00025) Accuracy 0.851 (0.880) +2023-01-14 16:30:00,555 Test: [0/54] Time 11.232 (11.232) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:30:26,165 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:30:26,166 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:30:26,167 | pose_hrnet | 91.572 | 85.491 | 77.517 | 78.759 | 92.760 | 88.727 | 87.516 | 94.423 | 86.878 | 88.342 | +2023-01-14 16:30:26,169 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:30:39,995 Epoch: [84][0/214] Time 12.209s (12.209s) Speed 2.6 samples/s Data 11.477s (11.477s) Loss 0.00024 (0.00024) Accuracy 0.911 (0.911) +2023-01-14 16:31:58,589 Epoch: [84][100/214] Time 0.758s (0.899s) Speed 42.2 samples/s Data 0.000s (0.130s) Loss 0.00027 (0.00025) Accuracy 0.867 (0.883) +2023-01-14 16:33:17,841 Epoch: [84][200/214] Time 0.820s (0.846s) Speed 39.0 samples/s Data 0.000s (0.073s) Loss 0.00020 (0.00024) Accuracy 0.918 (0.885) +2023-01-14 16:33:40,841 Test: [0/54] Time 11.352 (11.352) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:34:06,532 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:34:06,533 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:34:06,533 | pose_hrnet | 91.154 | 85.647 | 77.647 | 81.211 | 93.122 | 90.133 | 86.833 | 93.754 | 86.739 | 88.407 | +2023-01-14 16:34:06,535 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:34:20,573 Epoch: [85][0/214] Time 12.365s (12.365s) Speed 2.6 samples/s Data 11.615s (11.615s) Loss 0.00031 (0.00031) Accuracy 0.888 (0.888) +2023-01-14 16:35:39,063 Epoch: [85][100/214] Time 0.763s (0.900s) Speed 41.9 samples/s Data 0.000s (0.131s) Loss 0.00022 (0.00024) Accuracy 0.886 (0.885) +2023-01-14 16:36:58,459 Epoch: [85][200/214] Time 0.774s (0.847s) Speed 41.3 samples/s Data 0.000s (0.074s) Loss 0.00024 (0.00025) Accuracy 0.912 (0.883) +2023-01-14 16:37:21,612 Test: [0/54] Time 11.486 (11.486) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:37:47,237 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:37:47,237 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:37:47,238 | pose_hrnet | 90.795 | 85.868 | 76.716 | 79.981 | 93.121 | 89.237 | 87.135 | 94.055 | 87.280 | 88.328 | +2023-01-14 16:37:47,240 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:38:00,933 Epoch: [86][0/214] Time 12.095s (12.095s) Speed 2.6 samples/s Data 11.363s (11.363s) Loss 0.00024 (0.00024) Accuracy 0.910 (0.910) +2023-01-14 16:39:19,659 Epoch: [86][100/214] Time 0.798s (0.899s) Speed 40.1 samples/s Data 0.000s (0.129s) Loss 0.00025 (0.00025) Accuracy 0.903 (0.884) +2023-01-14 16:40:39,143 Epoch: [86][200/214] Time 0.774s (0.847s) Speed 41.3 samples/s Data 0.000s (0.073s) Loss 0.00025 (0.00024) Accuracy 0.835 (0.887) +2023-01-14 16:41:02,375 Test: [0/54] Time 11.488 (11.488) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:41:28,023 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:41:28,024 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:41:28,024 | pose_hrnet | 91.094 | 85.344 | 76.905 | 78.960 | 91.673 | 87.645 | 85.238 | 93.261 | 86.323 | 87.388 | +2023-01-14 16:41:28,026 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:41:41,855 Epoch: [87][0/214] Time 12.282s (12.282s) Speed 2.6 samples/s Data 11.544s (11.544s) Loss 0.00027 (0.00027) Accuracy 0.885 (0.885) +2023-01-14 16:43:00,514 Epoch: [87][100/214] Time 0.793s (0.900s) Speed 40.4 samples/s Data 0.000s (0.130s) Loss 0.00025 (0.00025) Accuracy 0.899 (0.885) +2023-01-14 16:44:19,800 Epoch: [87][200/214] Time 0.757s (0.847s) Speed 42.3 samples/s Data 0.000s (0.073s) Loss 0.00023 (0.00025) Accuracy 0.929 (0.884) +2023-01-14 16:44:42,993 Test: [0/54] Time 11.503 (11.503) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:45:08,438 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:45:08,439 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:45:08,440 | pose_hrnet | 89.898 | 86.066 | 78.380 | 79.719 | 93.544 | 88.857 | 86.305 | 93.737 | 86.778 | 88.231 | +2023-01-14 16:45:08,441 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:45:22,130 Epoch: [88][0/214] Time 12.117s (12.117s) Speed 2.6 samples/s Data 11.375s (11.375s) Loss 0.00021 (0.00021) Accuracy 0.920 (0.920) +2023-01-14 16:46:40,555 Epoch: [88][100/214] Time 0.775s (0.896s) Speed 41.3 samples/s Data 0.000s (0.128s) Loss 0.00020 (0.00023) Accuracy 0.943 (0.893) +2023-01-14 16:47:59,909 Epoch: [88][200/214] Time 0.762s (0.845s) Speed 42.0 samples/s Data 0.000s (0.072s) Loss 0.00022 (0.00023) Accuracy 0.891 (0.893) +2023-01-14 16:48:22,757 Test: [0/54] Time 11.330 (11.330) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:48:48,294 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:48:48,295 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:48:48,295 | pose_hrnet | 90.795 | 86.948 | 78.750 | 80.071 | 94.147 | 89.365 | 88.268 | 94.967 | 87.611 | 89.059 | +2023-01-14 16:48:48,297 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:49:01,884 Epoch: [89][0/214] Time 12.003s (12.003s) Speed 2.7 samples/s Data 11.248s (11.248s) Loss 0.00024 (0.00024) Accuracy 0.844 (0.844) +2023-01-14 16:50:20,513 Epoch: [89][100/214] Time 0.807s (0.897s) Speed 39.7 samples/s Data 0.000s (0.127s) Loss 0.00021 (0.00023) Accuracy 0.913 (0.895) +2023-01-14 16:51:39,647 Epoch: [89][200/214] Time 0.777s (0.845s) Speed 41.2 samples/s Data 0.000s (0.072s) Loss 0.00022 (0.00023) Accuracy 0.911 (0.893) +2023-01-14 16:52:02,879 Test: [0/54] Time 11.452 (11.452) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:52:28,437 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:52:28,437 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:52:28,438 | pose_hrnet | 91.512 | 86.312 | 79.442 | 80.866 | 93.906 | 88.667 | 87.818 | 93.747 | 86.640 | 88.606 | +2023-01-14 16:52:28,440 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:52:42,229 Epoch: [90][0/214] Time 12.166s (12.166s) Speed 2.6 samples/s Data 11.409s (11.409s) Loss 0.00023 (0.00023) Accuracy 0.859 (0.859) +2023-01-14 16:54:00,788 Epoch: [90][100/214] Time 0.799s (0.898s) Speed 40.1 samples/s Data 0.000s (0.129s) Loss 0.00025 (0.00024) Accuracy 0.907 (0.892) +2023-01-14 16:55:20,278 Epoch: [90][200/214] Time 0.779s (0.847s) Speed 41.1 samples/s Data 0.000s (0.073s) Loss 0.00020 (0.00023) Accuracy 0.935 (0.892) +2023-01-14 16:55:43,801 Test: [0/54] Time 11.778 (11.778) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:56:09,483 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:56:09,484 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:56:09,485 | pose_hrnet | 91.811 | 86.487 | 79.245 | 80.826 | 92.336 | 89.813 | 87.588 | 94.491 | 88.188 | 89.110 | +2023-01-14 16:56:09,487 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 16:56:23,474 Epoch: [91][0/214] Time 12.398s (12.398s) Speed 2.6 samples/s Data 11.658s (11.658s) Loss 0.00026 (0.00026) Accuracy 0.895 (0.895) +2023-01-14 16:57:42,387 Epoch: [91][100/214] Time 0.767s (0.904s) Speed 41.7 samples/s Data 0.001s (0.131s) Loss 0.00025 (0.00025) Accuracy 0.895 (0.881) +2023-01-14 16:59:01,743 Epoch: [91][200/214] Time 0.783s (0.849s) Speed 40.9 samples/s Data 0.000s (0.074s) Loss 0.00021 (0.00024) Accuracy 0.902 (0.886) +2023-01-14 16:59:24,720 Test: [0/54] Time 11.303 (11.303) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 16:59:50,334 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 16:59:50,335 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 16:59:50,335 | pose_hrnet | 90.018 | 85.495 | 77.284 | 79.288 | 92.579 | 89.236 | 86.380 | 92.807 | 86.636 | 87.680 | +2023-01-14 16:59:50,337 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:00:03,892 Epoch: [92][0/214] Time 11.997s (11.997s) Speed 2.7 samples/s Data 11.259s (11.259s) Loss 0.00021 (0.00021) Accuracy 0.921 (0.921) +2023-01-14 17:01:22,367 Epoch: [92][100/214] Time 0.792s (0.896s) Speed 40.4 samples/s Data 0.000s (0.127s) Loss 0.00028 (0.00024) Accuracy 0.808 (0.888) +2023-01-14 17:02:41,718 Epoch: [92][200/214] Time 0.777s (0.845s) Speed 41.2 samples/s Data 0.000s (0.072s) Loss 0.00025 (0.00024) Accuracy 0.892 (0.891) +2023-01-14 17:03:04,862 Test: [0/54] Time 11.540 (11.540) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:03:30,737 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:03:30,737 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:03:30,738 | pose_hrnet | 91.452 | 86.735 | 77.205 | 78.772 | 93.363 | 89.301 | 86.453 | 93.435 | 86.787 | 88.138 | +2023-01-14 17:03:30,740 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:03:44,540 Epoch: [93][0/214] Time 12.175s (12.175s) Speed 2.6 samples/s Data 11.430s (11.430s) Loss 0.00021 (0.00021) Accuracy 0.914 (0.914) +2023-01-14 17:05:03,320 Epoch: [93][100/214] Time 0.783s (0.901s) Speed 40.9 samples/s Data 0.001s (0.129s) Loss 0.00022 (0.00023) Accuracy 0.885 (0.899) +2023-01-14 17:06:22,830 Epoch: [93][200/214] Time 0.779s (0.848s) Speed 41.1 samples/s Data 0.001s (0.072s) Loss 0.00022 (0.00023) Accuracy 0.913 (0.898) +2023-01-14 17:06:45,808 Test: [0/54] Time 11.331 (11.331) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:07:11,539 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:07:11,540 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:07:11,541 | pose_hrnet | 90.317 | 84.929 | 77.227 | 79.173 | 92.516 | 88.032 | 84.788 | 92.879 | 86.707 | 87.486 | +2023-01-14 17:07:11,543 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:07:25,362 Epoch: [94][0/214] Time 12.270s (12.270s) Speed 2.6 samples/s Data 11.527s (11.527s) Loss 0.00023 (0.00023) Accuracy 0.897 (0.897) +2023-01-14 17:08:44,027 Epoch: [94][100/214] Time 0.779s (0.900s) Speed 41.1 samples/s Data 0.000s (0.130s) Loss 0.00022 (0.00023) Accuracy 0.905 (0.896) +2023-01-14 17:10:03,534 Epoch: [94][200/214] Time 0.777s (0.848s) Speed 41.2 samples/s Data 0.000s (0.074s) Loss 0.00026 (0.00023) Accuracy 0.879 (0.897) +2023-01-14 17:10:26,584 Test: [0/54] Time 11.419 (11.419) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:10:52,272 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:10:52,273 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:10:52,273 | pose_hrnet | 90.078 | 85.851 | 78.506 | 80.202 | 92.457 | 88.856 | 84.939 | 93.081 | 86.008 | 87.740 | +2023-01-14 17:10:52,275 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:11:05,943 Epoch: [95][0/214] Time 12.065s (12.065s) Speed 2.7 samples/s Data 11.326s (11.326s) Loss 0.00023 (0.00023) Accuracy 0.901 (0.901) +2023-01-14 17:12:24,548 Epoch: [95][100/214] Time 0.815s (0.898s) Speed 39.3 samples/s Data 0.001s (0.128s) Loss 0.00020 (0.00023) Accuracy 0.914 (0.900) +2023-01-14 17:13:44,327 Epoch: [95][200/214] Time 0.776s (0.848s) Speed 41.2 samples/s Data 0.001s (0.072s) Loss 0.00025 (0.00022) Accuracy 0.912 (0.902) +2023-01-14 17:14:07,686 Test: [0/54] Time 11.586 (11.586) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:14:33,423 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:14:33,424 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:14:33,424 | pose_hrnet | 90.915 | 86.628 | 77.907 | 78.328 | 90.707 | 87.265 | 84.638 | 93.154 | 86.395 | 87.430 | +2023-01-14 17:14:33,426 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:14:47,101 Epoch: [96][0/214] Time 12.050s (12.050s) Speed 2.7 samples/s Data 11.318s (11.318s) Loss 0.00023 (0.00023) Accuracy 0.915 (0.915) +2023-01-14 17:16:05,657 Epoch: [96][100/214] Time 0.778s (0.897s) Speed 41.1 samples/s Data 0.000s (0.127s) Loss 0.00023 (0.00023) Accuracy 0.898 (0.901) +2023-01-14 17:17:25,044 Epoch: [96][200/214] Time 0.774s (0.846s) Speed 41.3 samples/s Data 0.000s (0.072s) Loss 0.00024 (0.00023) Accuracy 0.892 (0.900) +2023-01-14 17:17:47,785 Test: [0/54] Time 11.113 (11.113) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:18:13,585 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:18:13,585 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:18:13,586 | pose_hrnet | 91.393 | 87.255 | 78.213 | 78.489 | 92.396 | 88.792 | 85.922 | 93.593 | 87.119 | 88.221 | +2023-01-14 17:18:13,588 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:18:27,753 Epoch: [97][0/214] Time 12.578s (12.578s) Speed 2.5 samples/s Data 11.836s (11.836s) Loss 0.00023 (0.00023) Accuracy 0.873 (0.873) +2023-01-14 17:19:46,713 Epoch: [97][100/214] Time 0.785s (0.906s) Speed 40.8 samples/s Data 0.000s (0.133s) Loss 0.00019 (0.00022) Accuracy 0.953 (0.902) +2023-01-14 17:21:06,148 Epoch: [97][200/214] Time 0.784s (0.851s) Speed 40.8 samples/s Data 0.000s (0.075s) Loss 0.00024 (0.00022) Accuracy 0.882 (0.903) +2023-01-14 17:21:29,081 Test: [0/54] Time 11.335 (11.335) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:21:54,786 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:21:54,787 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:21:54,788 | pose_hrnet | 90.915 | 85.226 | 76.712 | 77.423 | 90.646 | 87.901 | 84.948 | 92.855 | 86.177 | 87.240 | +2023-01-14 17:21:54,790 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:22:08,438 Epoch: [98][0/214] Time 11.980s (11.980s) Speed 2.7 samples/s Data 11.249s (11.249s) Loss 0.00021 (0.00021) Accuracy 0.938 (0.938) +2023-01-14 17:23:27,029 Epoch: [98][100/214] Time 0.760s (0.897s) Speed 42.1 samples/s Data 0.000s (0.127s) Loss 0.00019 (0.00022) Accuracy 0.942 (0.907) +2023-01-14 17:24:46,475 Epoch: [98][200/214] Time 0.785s (0.846s) Speed 40.8 samples/s Data 0.001s (0.072s) Loss 0.00024 (0.00022) Accuracy 0.884 (0.904) +2023-01-14 17:25:09,650 Test: [0/54] Time 11.425 (11.425) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:25:35,241 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:25:35,242 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:25:35,242 | pose_hrnet | 89.241 | 84.256 | 76.607 | 77.874 | 91.853 | 87.203 | 83.120 | 91.881 | 84.783 | 86.403 | +2023-01-14 17:25:35,244 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:25:48,782 Epoch: [99][0/214] Time 11.919s (11.919s) Speed 2.7 samples/s Data 11.180s (11.180s) Loss 0.00020 (0.00020) Accuracy 0.949 (0.949) +2023-01-14 17:27:07,478 Epoch: [99][100/214] Time 0.795s (0.897s) Speed 40.3 samples/s Data 0.000s (0.126s) Loss 0.00019 (0.00022) Accuracy 0.939 (0.904) +2023-01-14 17:28:26,929 Epoch: [99][200/214] Time 0.773s (0.846s) Speed 41.4 samples/s Data 0.000s (0.071s) Loss 0.00023 (0.00022) Accuracy 0.888 (0.906) +2023-01-14 17:28:50,128 Test: [0/54] Time 11.539 (11.539) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:29:15,680 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:29:15,681 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:29:15,681 | pose_hrnet | 90.616 | 85.875 | 77.632 | 78.345 | 92.032 | 89.112 | 84.717 | 93.624 | 86.573 | 87.828 | +2023-01-14 17:29:15,683 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:29:29,588 Epoch: [100][0/214] Time 12.307s (12.307s) Speed 2.6 samples/s Data 11.571s (11.571s) Loss 0.00018 (0.00018) Accuracy 0.935 (0.935) +2023-01-14 17:30:47,968 Epoch: [100][100/214] Time 0.757s (0.898s) Speed 42.3 samples/s Data 0.000s (0.131s) Loss 0.00022 (0.00021) Accuracy 0.867 (0.910) +2023-01-14 17:32:07,370 Epoch: [100][200/214] Time 0.782s (0.846s) Speed 40.9 samples/s Data 0.000s (0.074s) Loss 0.00023 (0.00021) Accuracy 0.881 (0.911) +2023-01-14 17:32:30,227 Test: [0/54] Time 11.257 (11.257) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:32:55,906 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:32:55,907 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:32:55,907 | pose_hrnet | 90.616 | 85.399 | 75.799 | 76.971 | 90.887 | 87.712 | 85.621 | 93.225 | 86.154 | 87.236 | +2023-01-14 17:32:55,910 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:33:09,777 Epoch: [101][0/214] Time 12.237s (12.237s) Speed 2.6 samples/s Data 11.506s (11.506s) Loss 0.00023 (0.00023) Accuracy 0.852 (0.852) +2023-01-14 17:34:28,319 Epoch: [101][100/214] Time 0.771s (0.899s) Speed 41.5 samples/s Data 0.000s (0.130s) Loss 0.00020 (0.00022) Accuracy 0.938 (0.905) +2023-01-14 17:35:47,996 Epoch: [101][200/214] Time 0.779s (0.848s) Speed 41.1 samples/s Data 0.000s (0.073s) Loss 0.00020 (0.00022) Accuracy 0.918 (0.906) +2023-01-14 17:36:11,020 Test: [0/54] Time 11.390 (11.390) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:36:36,658 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:36:36,659 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:36:36,659 | pose_hrnet | 90.197 | 85.668 | 77.217 | 78.366 | 91.611 | 87.329 | 85.397 | 93.675 | 86.341 | 87.569 | +2023-01-14 17:36:36,662 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:36:50,215 Epoch: [102][0/214] Time 11.964s (11.964s) Speed 2.7 samples/s Data 11.221s (11.221s) Loss 0.00022 (0.00022) Accuracy 0.882 (0.882) +2023-01-14 17:38:08,546 Epoch: [102][100/214] Time 0.785s (0.894s) Speed 40.8 samples/s Data 0.001s (0.126s) Loss 0.00020 (0.00021) Accuracy 0.948 (0.911) +2023-01-14 17:39:27,979 Epoch: [102][200/214] Time 0.777s (0.844s) Speed 41.2 samples/s Data 0.000s (0.071s) Loss 0.00022 (0.00021) Accuracy 0.888 (0.910) +2023-01-14 17:39:50,979 Test: [0/54] Time 11.306 (11.306) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:40:16,728 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:40:16,728 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:40:16,728 | pose_hrnet | 91.333 | 85.631 | 77.786 | 79.251 | 92.879 | 88.471 | 85.855 | 93.843 | 86.248 | 88.018 | +2023-01-14 17:40:16,730 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:40:30,703 Epoch: [103][0/214] Time 12.421s (12.421s) Speed 2.6 samples/s Data 11.661s (11.661s) Loss 0.00019 (0.00019) Accuracy 0.925 (0.925) +2023-01-14 17:41:49,219 Epoch: [103][100/214] Time 0.794s (0.900s) Speed 40.3 samples/s Data 0.001s (0.131s) Loss 0.00021 (0.00022) Accuracy 0.905 (0.906) +2023-01-14 17:43:08,599 Epoch: [103][200/214] Time 0.788s (0.847s) Speed 40.6 samples/s Data 0.000s (0.073s) Loss 0.00019 (0.00022) Accuracy 0.940 (0.908) +2023-01-14 17:43:31,705 Test: [0/54] Time 11.328 (11.328) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:43:57,485 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:43:57,486 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:43:57,486 | pose_hrnet | 93.066 | 87.259 | 78.633 | 81.407 | 93.784 | 89.176 | 86.079 | 95.099 | 87.585 | 89.253 | +2023-01-14 17:43:57,489 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:44:11,191 Epoch: [104][0/214] Time 12.038s (12.038s) Speed 2.7 samples/s Data 11.304s (11.304s) Loss 0.00019 (0.00019) Accuracy 0.938 (0.938) +2023-01-14 17:45:29,882 Epoch: [104][100/214] Time 0.784s (0.898s) Speed 40.8 samples/s Data 0.000s (0.128s) Loss 0.00020 (0.00022) Accuracy 0.914 (0.907) +2023-01-14 17:46:49,170 Epoch: [104][200/214] Time 0.765s (0.846s) Speed 41.8 samples/s Data 0.001s (0.072s) Loss 0.00018 (0.00021) Accuracy 0.942 (0.908) +2023-01-14 17:47:12,151 Test: [0/54] Time 11.327 (11.327) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:47:38,005 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:47:38,006 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:47:38,006 | pose_hrnet | 89.420 | 83.412 | 75.623 | 78.858 | 90.947 | 88.030 | 84.489 | 92.728 | 84.497 | 86.467 | +2023-01-14 17:47:38,008 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:47:51,809 Epoch: [105][0/214] Time 12.154s (12.154s) Speed 2.6 samples/s Data 11.403s (11.403s) Loss 0.00021 (0.00021) Accuracy 0.923 (0.923) +2023-01-14 17:49:10,370 Epoch: [105][100/214] Time 0.808s (0.898s) Speed 39.6 samples/s Data 0.001s (0.129s) Loss 0.00017 (0.00021) Accuracy 0.960 (0.914) +2023-01-14 17:50:29,970 Epoch: [105][200/214] Time 0.761s (0.847s) Speed 42.1 samples/s Data 0.000s (0.073s) Loss 0.00021 (0.00021) Accuracy 0.904 (0.915) +2023-01-14 17:50:52,948 Test: [0/54] Time 11.416 (11.416) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:51:18,712 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:51:18,712 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:51:18,713 | pose_hrnet | 89.659 | 86.072 | 76.533 | 79.693 | 91.310 | 88.534 | 85.016 | 93.110 | 85.359 | 87.393 | +2023-01-14 17:51:18,715 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:51:32,677 Epoch: [106][0/214] Time 12.399s (12.399s) Speed 2.6 samples/s Data 11.660s (11.660s) Loss 0.00021 (0.00021) Accuracy 0.903 (0.903) +2023-01-14 17:52:51,183 Epoch: [106][100/214] Time 0.785s (0.900s) Speed 40.8 samples/s Data 0.000s (0.131s) Loss 0.00017 (0.00021) Accuracy 0.956 (0.917) +2023-01-14 17:54:10,548 Epoch: [106][200/214] Time 0.775s (0.847s) Speed 41.3 samples/s Data 0.000s (0.073s) Loss 0.00019 (0.00021) Accuracy 0.931 (0.915) +2023-01-14 17:54:33,720 Test: [0/54] Time 11.451 (11.451) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:54:59,394 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:54:59,394 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:54:59,395 | pose_hrnet | 91.034 | 86.079 | 78.079 | 80.226 | 92.757 | 88.471 | 85.320 | 93.259 | 86.261 | 88.013 | +2023-01-14 17:54:59,397 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:55:13,117 Epoch: [107][0/214] Time 12.173s (12.173s) Speed 2.6 samples/s Data 11.434s (11.434s) Loss 0.00021 (0.00021) Accuracy 0.931 (0.931) +2023-01-14 17:56:31,500 Epoch: [107][100/214] Time 0.777s (0.897s) Speed 41.2 samples/s Data 0.000s (0.129s) Loss 0.00017 (0.00021) Accuracy 0.956 (0.918) +2023-01-14 17:57:50,851 Epoch: [107][200/214] Time 0.761s (0.845s) Speed 42.0 samples/s Data 0.001s (0.073s) Loss 0.00015 (0.00020) Accuracy 0.947 (0.918) +2023-01-14 17:58:14,001 Test: [0/54] Time 11.525 (11.525) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 17:58:39,574 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 17:58:39,575 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 17:58:39,575 | pose_hrnet | 91.213 | 87.194 | 78.695 | 81.247 | 92.336 | 88.155 | 84.566 | 93.642 | 86.802 | 88.268 | +2023-01-14 17:58:39,578 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 17:58:53,631 Epoch: [108][0/214] Time 12.390s (12.390s) Speed 2.6 samples/s Data 11.637s (11.637s) Loss 0.00016 (0.00016) Accuracy 0.972 (0.972) +2023-01-14 18:00:11,989 Epoch: [108][100/214] Time 0.779s (0.898s) Speed 41.1 samples/s Data 0.000s (0.130s) Loss 0.00018 (0.00020) Accuracy 0.936 (0.918) +2023-01-14 18:01:31,432 Epoch: [108][200/214] Time 0.793s (0.847s) Speed 40.4 samples/s Data 0.000s (0.073s) Loss 0.00023 (0.00020) Accuracy 0.922 (0.915) +2023-01-14 18:01:54,570 Test: [0/54] Time 11.395 (11.395) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:02:20,235 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:02:20,236 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:02:20,236 | pose_hrnet | 91.990 | 87.916 | 78.991 | 82.251 | 93.421 | 89.107 | 85.545 | 94.792 | 87.416 | 89.203 | +2023-01-14 18:02:20,239 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:02:34,061 Epoch: [109][0/214] Time 12.206s (12.206s) Speed 2.6 samples/s Data 11.464s (11.464s) Loss 0.00022 (0.00022) Accuracy 0.897 (0.897) +2023-01-14 18:03:52,441 Epoch: [109][100/214] Time 0.784s (0.897s) Speed 40.8 samples/s Data 0.000s (0.129s) Loss 0.00018 (0.00020) Accuracy 0.929 (0.915) +2023-01-14 18:05:11,761 Epoch: [109][200/214] Time 0.763s (0.845s) Speed 41.9 samples/s Data 0.001s (0.073s) Loss 0.00018 (0.00020) Accuracy 0.944 (0.915) +2023-01-14 18:05:34,712 Test: [0/54] Time 11.337 (11.337) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:06:00,287 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:06:00,287 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:06:00,288 | pose_hrnet | 89.480 | 85.102 | 75.991 | 79.936 | 89.740 | 87.393 | 84.409 | 92.288 | 85.900 | 86.842 | +2023-01-14 18:06:00,289 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:06:14,309 Epoch: [110][0/214] Time 12.413s (12.413s) Speed 2.6 samples/s Data 11.653s (11.653s) Loss 0.00017 (0.00017) Accuracy 0.942 (0.942) +2023-01-14 18:07:32,896 Epoch: [110][100/214] Time 0.789s (0.901s) Speed 40.6 samples/s Data 0.000s (0.131s) Loss 0.00018 (0.00020) Accuracy 0.928 (0.919) +2023-01-14 18:08:52,154 Epoch: [110][200/214] Time 0.774s (0.847s) Speed 41.3 samples/s Data 0.000s (0.074s) Loss 0.00021 (0.00020) Accuracy 0.932 (0.918) +2023-01-14 18:09:15,340 Test: [0/54] Time 11.399 (11.399) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:09:40,858 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:09:40,859 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:09:40,859 | pose_hrnet | 89.480 | 84.742 | 77.958 | 79.395 | 90.225 | 87.580 | 84.189 | 91.539 | 84.053 | 86.444 | +2023-01-14 18:09:40,862 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:09:54,720 Epoch: [111][0/214] Time 12.093s (12.093s) Speed 2.6 samples/s Data 11.364s (11.364s) Loss 0.00022 (0.00022) Accuracy 0.891 (0.891) +2023-01-14 18:11:13,257 Epoch: [111][100/214] Time 0.779s (0.897s) Speed 41.1 samples/s Data 0.000s (0.128s) Loss 0.00020 (0.00021) Accuracy 0.928 (0.912) +2023-01-14 18:12:32,531 Epoch: [111][200/214] Time 0.793s (0.845s) Speed 40.4 samples/s Data 0.000s (0.072s) Loss 0.00021 (0.00020) Accuracy 0.932 (0.915) +2023-01-14 18:12:55,575 Test: [0/54] Time 11.316 (11.316) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:13:21,121 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:13:21,122 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:13:21,123 | pose_hrnet | 89.480 | 85.673 | 76.543 | 79.423 | 91.975 | 86.302 | 85.923 | 92.187 | 85.274 | 86.916 | +2023-01-14 18:13:21,125 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:13:35,099 Epoch: [112][0/214] Time 12.375s (12.375s) Speed 2.6 samples/s Data 11.615s (11.615s) Loss 0.00017 (0.00017) Accuracy 0.935 (0.935) +2023-01-14 18:14:53,516 Epoch: [112][100/214] Time 0.776s (0.899s) Speed 41.2 samples/s Data 0.000s (0.130s) Loss 0.00023 (0.00021) Accuracy 0.920 (0.912) +2023-01-14 18:16:12,715 Epoch: [112][200/214] Time 0.760s (0.846s) Speed 42.1 samples/s Data 0.000s (0.073s) Loss 0.00017 (0.00021) Accuracy 0.942 (0.915) +2023-01-14 18:16:35,888 Test: [0/54] Time 11.495 (11.495) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:17:01,628 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:17:01,629 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:17:01,629 | pose_hrnet | 90.436 | 85.506 | 79.012 | 80.378 | 91.853 | 87.266 | 84.642 | 93.176 | 86.584 | 87.833 | +2023-01-14 18:17:01,632 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:17:15,755 Epoch: [113][0/214] Time 12.525s (12.525s) Speed 2.6 samples/s Data 11.790s (11.790s) Loss 0.00018 (0.00018) Accuracy 0.924 (0.924) +2023-01-14 18:18:34,460 Epoch: [113][100/214] Time 0.780s (0.903s) Speed 41.0 samples/s Data 0.000s (0.133s) Loss 0.00021 (0.00020) Accuracy 0.921 (0.920) +2023-01-14 18:19:53,784 Epoch: [113][200/214] Time 0.782s (0.849s) Speed 40.9 samples/s Data 0.000s (0.074s) Loss 0.00019 (0.00020) Accuracy 0.924 (0.919) +2023-01-14 18:20:16,801 Test: [0/54] Time 11.367 (11.367) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:20:42,571 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:20:42,571 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:20:42,572 | pose_hrnet | 90.018 | 85.950 | 77.518 | 79.930 | 91.431 | 87.005 | 84.334 | 93.711 | 85.954 | 87.564 | +2023-01-14 18:20:42,573 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:20:56,391 Epoch: [114][0/214] Time 12.073s (12.073s) Speed 2.7 samples/s Data 11.326s (11.326s) Loss 0.00021 (0.00021) Accuracy 0.890 (0.890) +2023-01-14 18:22:14,855 Epoch: [114][100/214] Time 0.784s (0.896s) Speed 40.8 samples/s Data 0.000s (0.127s) Loss 0.00021 (0.00020) Accuracy 0.913 (0.916) +2023-01-14 18:23:34,108 Epoch: [114][200/214] Time 0.783s (0.845s) Speed 40.9 samples/s Data 0.000s (0.072s) Loss 0.00018 (0.00020) Accuracy 0.931 (0.920) +2023-01-14 18:23:57,115 Test: [0/54] Time 11.372 (11.372) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:24:22,794 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:24:22,795 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:24:22,795 | pose_hrnet | 91.034 | 86.744 | 78.194 | 79.706 | 91.310 | 87.584 | 83.881 | 93.478 | 86.260 | 87.722 | +2023-01-14 18:24:22,798 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:24:36,957 Epoch: [115][0/214] Time 12.582s (12.582s) Speed 2.5 samples/s Data 11.829s (11.829s) Loss 0.00020 (0.00020) Accuracy 0.914 (0.914) +2023-01-14 18:25:55,562 Epoch: [115][100/214] Time 0.816s (0.903s) Speed 39.2 samples/s Data 0.000s (0.133s) Loss 0.00018 (0.00021) Accuracy 0.949 (0.918) +2023-01-14 18:27:14,904 Epoch: [115][200/214] Time 0.778s (0.848s) Speed 41.1 samples/s Data 0.000s (0.075s) Loss 0.00019 (0.00020) Accuracy 0.935 (0.919) +2023-01-14 18:27:38,078 Test: [0/54] Time 11.478 (11.478) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:28:03,554 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:28:03,554 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:28:03,555 | pose_hrnet | 91.333 | 86.885 | 77.393 | 78.615 | 92.880 | 88.219 | 85.701 | 93.111 | 86.739 | 87.930 | +2023-01-14 18:28:03,557 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:28:17,784 Epoch: [116][0/214] Time 12.498s (12.498s) Speed 2.6 samples/s Data 11.749s (11.749s) Loss 0.00021 (0.00021) Accuracy 0.925 (0.925) +2023-01-14 18:29:36,350 Epoch: [116][100/214] Time 0.818s (0.902s) Speed 39.1 samples/s Data 0.000s (0.132s) Loss 0.00020 (0.00020) Accuracy 0.928 (0.919) +2023-01-14 18:30:55,941 Epoch: [116][200/214] Time 0.770s (0.849s) Speed 41.6 samples/s Data 0.000s (0.074s) Loss 0.00020 (0.00020) Accuracy 0.889 (0.921) +2023-01-14 18:31:18,967 Test: [0/54] Time 11.254 (11.254) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:31:44,659 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:31:44,659 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:31:44,660 | pose_hrnet | 90.436 | 87.196 | 77.035 | 79.571 | 92.154 | 88.791 | 86.905 | 93.979 | 86.572 | 88.152 | +2023-01-14 18:31:44,662 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:31:58,732 Epoch: [117][0/214] Time 12.406s (12.406s) Speed 2.6 samples/s Data 11.656s (11.656s) Loss 0.00019 (0.00019) Accuracy 0.909 (0.909) +2023-01-14 18:33:17,369 Epoch: [117][100/214] Time 0.761s (0.901s) Speed 42.0 samples/s Data 0.001s (0.132s) Loss 0.00020 (0.00020) Accuracy 0.887 (0.915) +2023-01-14 18:34:36,951 Epoch: [117][200/214] Time 0.777s (0.849s) Speed 41.2 samples/s Data 0.000s (0.074s) Loss 0.00016 (0.00020) Accuracy 0.937 (0.919) +2023-01-14 18:35:00,129 Test: [0/54] Time 11.461 (11.461) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:35:25,865 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:35:25,865 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:35:25,866 | pose_hrnet | 91.632 | 87.516 | 77.140 | 80.448 | 92.998 | 88.536 | 86.982 | 93.545 | 86.807 | 88.332 | +2023-01-14 18:35:25,868 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:35:39,897 Epoch: [118][0/214] Time 12.444s (12.444s) Speed 2.6 samples/s Data 11.703s (11.703s) Loss 0.00018 (0.00018) Accuracy 0.958 (0.958) +2023-01-14 18:36:58,242 Epoch: [118][100/214] Time 0.781s (0.899s) Speed 41.0 samples/s Data 0.000s (0.132s) Loss 0.00015 (0.00019) Accuracy 0.952 (0.924) +2023-01-14 18:38:17,459 Epoch: [118][200/214] Time 0.809s (0.846s) Speed 39.6 samples/s Data 0.001s (0.074s) Loss 0.00018 (0.00019) Accuracy 0.948 (0.924) +2023-01-14 18:38:40,400 Test: [0/54] Time 11.350 (11.350) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:39:06,017 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:39:06,017 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:39:06,018 | pose_hrnet | 91.154 | 86.683 | 77.832 | 80.537 | 93.180 | 89.174 | 87.439 | 94.001 | 87.295 | 88.481 | +2023-01-14 18:39:06,020 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:39:20,072 Epoch: [119][0/214] Time 12.395s (12.395s) Speed 2.6 samples/s Data 11.665s (11.665s) Loss 0.00021 (0.00021) Accuracy 0.900 (0.900) +2023-01-14 18:40:38,519 Epoch: [119][100/214] Time 0.798s (0.899s) Speed 40.1 samples/s Data 0.000s (0.131s) Loss 0.00019 (0.00019) Accuracy 0.935 (0.923) +2023-01-14 18:41:57,650 Epoch: [119][200/214] Time 0.771s (0.846s) Speed 41.5 samples/s Data 0.000s (0.074s) Loss 0.00021 (0.00019) Accuracy 0.942 (0.925) +2023-01-14 18:42:20,819 Test: [0/54] Time 11.559 (11.559) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:42:46,446 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:42:46,446 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:42:46,447 | pose_hrnet | 91.871 | 87.108 | 78.630 | 80.251 | 94.326 | 90.255 | 88.120 | 94.079 | 88.436 | 89.216 | +2023-01-14 18:42:46,449 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:43:00,226 Epoch: [120][0/214] Time 12.201s (12.201s) Speed 2.6 samples/s Data 11.474s (11.474s) Loss 0.00019 (0.00019) Accuracy 0.932 (0.932) +2023-01-14 18:44:19,081 Epoch: [120][100/214] Time 0.775s (0.902s) Speed 41.3 samples/s Data 0.000s (0.129s) Loss 0.00022 (0.00019) Accuracy 0.879 (0.922) +2023-01-14 18:45:38,616 Epoch: [120][200/214] Time 0.779s (0.849s) Speed 41.1 samples/s Data 0.000s (0.073s) Loss 0.00022 (0.00019) Accuracy 0.887 (0.922) +2023-01-14 18:46:01,772 Test: [0/54] Time 11.472 (11.472) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:46:27,353 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:46:27,353 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:46:27,354 | pose_hrnet | 91.692 | 87.449 | 78.995 | 81.280 | 94.568 | 90.767 | 86.911 | 95.245 | 87.459 | 89.291 | +2023-01-14 18:46:27,356 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:46:41,175 Epoch: [121][0/214] Time 12.207s (12.207s) Speed 2.6 samples/s Data 11.481s (11.481s) Loss 0.00019 (0.00019) Accuracy 0.934 (0.934) +2023-01-14 18:47:59,810 Epoch: [121][100/214] Time 0.809s (0.899s) Speed 39.6 samples/s Data 0.000s (0.129s) Loss 0.00022 (0.00019) Accuracy 0.908 (0.927) +2023-01-14 18:49:19,523 Epoch: [121][200/214] Time 0.791s (0.849s) Speed 40.5 samples/s Data 0.000s (0.073s) Loss 0.00019 (0.00019) Accuracy 0.940 (0.926) +2023-01-14 18:49:42,728 Test: [0/54] Time 11.449 (11.449) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:50:08,382 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:50:08,383 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:50:08,383 | pose_hrnet | 90.616 | 86.910 | 77.600 | 81.756 | 94.085 | 89.617 | 87.740 | 94.297 | 88.258 | 89.004 | +2023-01-14 18:50:08,385 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:50:22,356 Epoch: [122][0/214] Time 12.427s (12.427s) Speed 2.6 samples/s Data 11.680s (11.680s) Loss 0.00017 (0.00017) Accuracy 0.961 (0.961) +2023-01-14 18:51:41,071 Epoch: [122][100/214] Time 0.803s (0.902s) Speed 39.9 samples/s Data 0.000s (0.132s) Loss 0.00018 (0.00020) Accuracy 0.938 (0.921) +2023-01-14 18:53:00,267 Epoch: [122][200/214] Time 0.787s (0.847s) Speed 40.7 samples/s Data 0.000s (0.074s) Loss 0.00021 (0.00020) Accuracy 0.907 (0.924) +2023-01-14 18:53:23,165 Test: [0/54] Time 11.358 (11.358) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:53:48,785 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:53:48,785 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:53:48,786 | pose_hrnet | 91.333 | 86.489 | 77.830 | 79.803 | 93.543 | 89.743 | 85.394 | 94.487 | 87.357 | 88.592 | +2023-01-14 18:53:48,788 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:54:02,813 Epoch: [123][0/214] Time 12.402s (12.402s) Speed 2.6 samples/s Data 11.655s (11.655s) Loss 0.00022 (0.00022) Accuracy 0.870 (0.870) +2023-01-14 18:55:21,064 Epoch: [123][100/214] Time 0.777s (0.898s) Speed 41.2 samples/s Data 0.001s (0.131s) Loss 0.00022 (0.00019) Accuracy 0.920 (0.926) +2023-01-14 18:56:40,173 Epoch: [123][200/214] Time 0.783s (0.845s) Speed 40.9 samples/s Data 0.000s (0.074s) Loss 0.00020 (0.00019) Accuracy 0.911 (0.925) +2023-01-14 18:57:03,261 Test: [0/54] Time 11.535 (11.535) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 18:57:28,880 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 18:57:28,881 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 18:57:28,881 | pose_hrnet | 91.512 | 87.523 | 79.117 | 81.420 | 94.508 | 90.255 | 86.829 | 95.008 | 87.881 | 89.300 | +2023-01-14 18:57:28,883 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 18:57:42,571 Epoch: [124][0/214] Time 12.116s (12.116s) Speed 2.6 samples/s Data 11.382s (11.382s) Loss 0.00019 (0.00019) Accuracy 0.937 (0.937) +2023-01-14 18:59:01,162 Epoch: [124][100/214] Time 0.791s (0.898s) Speed 40.5 samples/s Data 0.000s (0.129s) Loss 0.00021 (0.00020) Accuracy 0.910 (0.923) +2023-01-14 19:00:20,608 Epoch: [124][200/214] Time 0.771s (0.847s) Speed 41.5 samples/s Data 0.000s (0.073s) Loss 0.00020 (0.00019) Accuracy 0.929 (0.925) +2023-01-14 19:00:44,032 Test: [0/54] Time 11.632 (11.632) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:01:09,727 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:01:09,728 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:01:09,728 | pose_hrnet | 90.855 | 86.024 | 79.683 | 81.177 | 93.482 | 89.432 | 85.092 | 93.814 | 87.332 | 88.439 | +2023-01-14 19:01:09,731 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:01:23,786 Epoch: [125][0/214] Time 12.368s (12.368s) Speed 2.6 samples/s Data 11.632s (11.632s) Loss 0.00019 (0.00019) Accuracy 0.934 (0.934) +2023-01-14 19:02:42,659 Epoch: [125][100/214] Time 0.770s (0.903s) Speed 41.6 samples/s Data 0.000s (0.132s) Loss 0.00016 (0.00020) Accuracy 0.940 (0.922) +2023-01-14 19:04:01,982 Epoch: [125][200/214] Time 0.778s (0.849s) Speed 41.1 samples/s Data 0.000s (0.074s) Loss 0.00016 (0.00019) Accuracy 0.943 (0.925) +2023-01-14 19:04:24,985 Test: [0/54] Time 11.354 (11.354) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:04:50,509 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:04:50,510 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:04:50,510 | pose_hrnet | 90.436 | 84.887 | 77.401 | 80.116 | 94.026 | 90.322 | 87.133 | 92.915 | 86.983 | 88.022 | +2023-01-14 19:04:50,512 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:05:04,122 Epoch: [126][0/214] Time 12.011s (12.011s) Speed 2.7 samples/s Data 11.268s (11.268s) Loss 0.00016 (0.00016) Accuracy 0.953 (0.953) +2023-01-14 19:06:22,679 Epoch: [126][100/214] Time 0.779s (0.897s) Speed 41.1 samples/s Data 0.000s (0.127s) Loss 0.00014 (0.00018) Accuracy 0.951 (0.931) +2023-01-14 19:07:41,990 Epoch: [126][200/214] Time 0.776s (0.845s) Speed 41.2 samples/s Data 0.000s (0.072s) Loss 0.00018 (0.00018) Accuracy 0.959 (0.930) +2023-01-14 19:08:04,913 Test: [0/54] Time 11.268 (11.268) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:08:30,531 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:08:30,532 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:08:30,533 | pose_hrnet | 91.751 | 87.255 | 80.178 | 81.152 | 93.542 | 91.017 | 86.831 | 94.414 | 89.050 | 89.568 | +2023-01-14 19:08:30,535 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:08:44,428 Epoch: [127][0/214] Time 12.235s (12.235s) Speed 2.6 samples/s Data 11.495s (11.495s) Loss 0.00017 (0.00017) Accuracy 0.933 (0.933) +2023-01-14 19:10:03,260 Epoch: [127][100/214] Time 0.776s (0.902s) Speed 41.2 samples/s Data 0.000s (0.130s) Loss 0.00021 (0.00018) Accuracy 0.887 (0.930) +2023-01-14 19:11:22,714 Epoch: [127][200/214] Time 0.789s (0.848s) Speed 40.6 samples/s Data 0.000s (0.073s) Loss 0.00018 (0.00018) Accuracy 0.925 (0.931) +2023-01-14 19:11:45,845 Test: [0/54] Time 11.474 (11.474) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:12:11,601 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:12:11,601 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:12:11,602 | pose_hrnet | 90.855 | 87.874 | 78.817 | 82.063 | 93.843 | 91.403 | 87.285 | 94.826 | 88.384 | 89.476 | +2023-01-14 19:12:11,604 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:12:25,506 Epoch: [128][0/214] Time 12.356s (12.356s) Speed 2.6 samples/s Data 11.609s (11.609s) Loss 0.00020 (0.00020) Accuracy 0.917 (0.917) +2023-01-14 19:13:44,097 Epoch: [128][100/214] Time 0.778s (0.900s) Speed 41.1 samples/s Data 0.000s (0.131s) Loss 0.00019 (0.00019) Accuracy 0.927 (0.927) +2023-01-14 19:15:03,475 Epoch: [128][200/214] Time 0.784s (0.847s) Speed 40.8 samples/s Data 0.000s (0.074s) Loss 0.00019 (0.00019) Accuracy 0.941 (0.928) +2023-01-14 19:15:26,275 Test: [0/54] Time 11.269 (11.269) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:15:51,818 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:15:51,819 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:15:51,819 | pose_hrnet | 92.289 | 87.716 | 78.874 | 82.079 | 93.543 | 90.575 | 86.912 | 95.579 | 89.185 | 89.790 | +2023-01-14 19:15:51,822 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:16:06,143 Epoch: [129][0/214] Time 12.079s (12.079s) Speed 2.6 samples/s Data 11.336s (11.336s) Loss 0.00021 (0.00021) Accuracy 0.896 (0.896) +2023-01-14 19:17:24,841 Epoch: [129][100/214] Time 0.790s (0.899s) Speed 40.5 samples/s Data 0.000s (0.128s) Loss 0.00017 (0.00019) Accuracy 0.910 (0.929) +2023-01-14 19:18:44,331 Epoch: [129][200/214] Time 0.774s (0.847s) Speed 41.3 samples/s Data 0.000s (0.072s) Loss 0.00018 (0.00018) Accuracy 0.930 (0.930) +2023-01-14 19:19:07,584 Test: [0/54] Time 11.554 (11.554) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:19:33,120 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:19:33,121 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:19:33,121 | pose_hrnet | 69.994 | 69.430 | 60.642 | 60.992 | 74.292 | 71.521 | 64.646 | 72.029 | 68.183 | 68.635 | +2023-01-14 19:19:33,123 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:19:46,749 Epoch: [130][0/214] Time 11.909s (11.909s) Speed 2.7 samples/s Data 11.169s (11.169s) Loss 0.00017 (0.00017) Accuracy 0.899 (0.899) +2023-01-14 19:21:05,433 Epoch: [130][100/214] Time 0.783s (0.897s) Speed 40.9 samples/s Data 0.000s (0.126s) Loss 0.00024 (0.00020) Accuracy 0.830 (0.918) +2023-01-14 19:22:24,624 Epoch: [130][200/214] Time 0.774s (0.845s) Speed 41.3 samples/s Data 0.000s (0.071s) Loss 0.00021 (0.00020) Accuracy 0.939 (0.921) +2023-01-14 19:22:47,695 Test: [0/54] Time 11.446 (11.446) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:23:13,376 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:23:13,377 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:23:13,377 | pose_hrnet | 93.007 | 86.900 | 79.003 | 82.396 | 94.449 | 90.956 | 88.194 | 96.178 | 88.713 | 90.059 | +2023-01-14 19:23:13,379 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:23:27,757 Epoch: [131][0/214] Time 12.235s (12.235s) Speed 2.6 samples/s Data 11.494s (11.494s) Loss 0.00020 (0.00020) Accuracy 0.887 (0.887) +2023-01-14 19:24:46,540 Epoch: [131][100/214] Time 0.789s (0.901s) Speed 40.6 samples/s Data 0.000s (0.130s) Loss 0.00021 (0.00019) Accuracy 0.942 (0.931) +2023-01-14 19:26:06,166 Epoch: [131][200/214] Time 0.789s (0.849s) Speed 40.6 samples/s Data 0.000s (0.074s) Loss 0.00019 (0.00018) Accuracy 0.921 (0.932) +2023-01-14 19:26:29,281 Test: [0/54] Time 11.426 (11.426) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:26:54,940 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:26:54,941 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:26:54,942 | pose_hrnet | 92.767 | 87.237 | 78.875 | 82.449 | 94.207 | 91.657 | 87.969 | 95.333 | 88.641 | 89.975 | +2023-01-14 19:26:54,944 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:27:08,932 Epoch: [132][0/214] Time 12.296s (12.296s) Speed 2.6 samples/s Data 11.542s (11.542s) Loss 0.00022 (0.00022) Accuracy 0.885 (0.885) +2023-01-14 19:28:27,695 Epoch: [132][100/214] Time 0.817s (0.902s) Speed 39.2 samples/s Data 0.000s (0.130s) Loss 0.00015 (0.00018) Accuracy 0.960 (0.932) +2023-01-14 19:29:47,062 Epoch: [132][200/214] Time 0.774s (0.848s) Speed 41.3 samples/s Data 0.000s (0.073s) Loss 0.00019 (0.00018) Accuracy 0.954 (0.933) +2023-01-14 19:30:10,240 Test: [0/54] Time 11.545 (11.545) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:30:35,926 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:30:35,926 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:30:35,927 | pose_hrnet | 92.708 | 87.722 | 80.046 | 81.481 | 93.784 | 89.871 | 85.628 | 95.034 | 89.200 | 89.628 | +2023-01-14 19:30:35,929 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:30:49,657 Epoch: [133][0/214] Time 12.052s (12.052s) Speed 2.7 samples/s Data 11.331s (11.331s) Loss 0.00017 (0.00017) Accuracy 0.943 (0.943) +2023-01-14 19:32:08,244 Epoch: [133][100/214] Time 0.804s (0.897s) Speed 39.8 samples/s Data 0.000s (0.128s) Loss 0.00020 (0.00018) Accuracy 0.930 (0.933) +2023-01-14 19:33:27,750 Epoch: [133][200/214] Time 0.762s (0.846s) Speed 42.0 samples/s Data 0.000s (0.073s) Loss 0.00018 (0.00018) Accuracy 0.939 (0.933) +2023-01-14 19:33:51,023 Test: [0/54] Time 11.533 (11.533) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:34:16,688 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:34:16,689 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:34:16,689 | pose_hrnet | 93.007 | 87.784 | 78.750 | 81.657 | 93.543 | 89.558 | 87.137 | 95.686 | 88.543 | 89.726 | +2023-01-14 19:34:16,691 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:34:30,493 Epoch: [134][0/214] Time 12.210s (12.210s) Speed 2.6 samples/s Data 11.472s (11.472s) Loss 0.00020 (0.00020) Accuracy 0.944 (0.944) +2023-01-14 19:35:49,342 Epoch: [134][100/214] Time 0.774s (0.902s) Speed 41.3 samples/s Data 0.000s (0.129s) Loss 0.00018 (0.00018) Accuracy 0.952 (0.935) +2023-01-14 19:37:08,756 Epoch: [134][200/214] Time 0.776s (0.848s) Speed 41.2 samples/s Data 0.000s (0.073s) Loss 0.00017 (0.00018) Accuracy 0.950 (0.936) +2023-01-14 19:37:31,776 Test: [0/54] Time 11.337 (11.337) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:37:57,571 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:37:57,572 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:37:57,572 | pose_hrnet | 92.528 | 88.470 | 79.671 | 81.236 | 93.059 | 89.871 | 86.232 | 95.306 | 88.928 | 89.739 | +2023-01-14 19:37:57,575 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:38:11,044 Epoch: [135][0/214] Time 11.722s (11.722s) Speed 2.7 samples/s Data 10.995s (10.995s) Loss 0.00016 (0.00016) Accuracy 0.963 (0.963) +2023-01-14 19:39:29,691 Epoch: [135][100/214] Time 0.787s (0.895s) Speed 40.7 samples/s Data 0.001s (0.125s) Loss 0.00020 (0.00018) Accuracy 0.942 (0.931) +2023-01-14 19:40:49,281 Epoch: [135][200/214] Time 0.777s (0.846s) Speed 41.2 samples/s Data 0.001s (0.071s) Loss 0.00016 (0.00018) Accuracy 0.965 (0.933) +2023-01-14 19:41:12,402 Test: [0/54] Time 11.494 (11.494) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:41:37,977 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:41:37,978 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:41:37,978 | pose_hrnet | 92.767 | 87.535 | 79.250 | 81.703 | 93.423 | 90.450 | 87.437 | 96.377 | 88.986 | 89.994 | +2023-01-14 19:41:37,980 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:41:51,968 Epoch: [136][0/214] Time 12.296s (12.296s) Speed 2.6 samples/s Data 11.557s (11.557s) Loss 0.00017 (0.00017) Accuracy 0.939 (0.939) +2023-01-14 19:43:10,579 Epoch: [136][100/214] Time 0.786s (0.900s) Speed 40.7 samples/s Data 0.001s (0.130s) Loss 0.00021 (0.00018) Accuracy 0.928 (0.934) +2023-01-14 19:44:29,850 Epoch: [136][200/214] Time 0.758s (0.847s) Speed 42.2 samples/s Data 0.000s (0.073s) Loss 0.00017 (0.00018) Accuracy 0.936 (0.935) +2023-01-14 19:44:53,018 Test: [0/54] Time 11.504 (11.504) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:45:18,661 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:45:18,662 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:45:18,662 | pose_hrnet | 92.827 | 88.001 | 80.845 | 81.940 | 93.482 | 91.147 | 89.104 | 95.752 | 88.822 | 90.198 | +2023-01-14 19:45:18,665 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:45:33,534 Epoch: [137][0/214] Time 12.532s (12.532s) Speed 2.6 samples/s Data 11.788s (11.788s) Loss 0.00018 (0.00018) Accuracy 0.941 (0.941) +2023-01-14 19:46:52,040 Epoch: [137][100/214] Time 0.806s (0.901s) Speed 39.7 samples/s Data 0.001s (0.133s) Loss 0.00018 (0.00018) Accuracy 0.933 (0.936) +2023-01-14 19:48:11,016 Epoch: [137][200/214] Time 0.791s (0.846s) Speed 40.5 samples/s Data 0.000s (0.075s) Loss 0.00019 (0.00018) Accuracy 0.914 (0.936) +2023-01-14 19:48:34,145 Test: [0/54] Time 11.378 (11.378) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:48:59,807 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:48:59,807 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:48:59,808 | pose_hrnet | 92.947 | 88.028 | 78.382 | 81.826 | 94.208 | 90.374 | 88.347 | 95.787 | 88.510 | 89.911 | +2023-01-14 19:48:59,811 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:49:13,821 Epoch: [138][0/214] Time 12.376s (12.376s) Speed 2.6 samples/s Data 11.606s (11.606s) Loss 0.00020 (0.00020) Accuracy 0.883 (0.883) +2023-01-14 19:50:32,538 Epoch: [138][100/214] Time 0.774s (0.902s) Speed 41.3 samples/s Data 0.000s (0.131s) Loss 0.00019 (0.00017) Accuracy 0.879 (0.937) +2023-01-14 19:51:51,979 Epoch: [138][200/214] Time 0.769s (0.848s) Speed 41.6 samples/s Data 0.000s (0.074s) Loss 0.00016 (0.00017) Accuracy 0.954 (0.940) +2023-01-14 19:52:15,062 Test: [0/54] Time 11.509 (11.509) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:52:40,656 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:52:40,656 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:52:40,657 | pose_hrnet | 91.931 | 87.321 | 79.434 | 81.022 | 93.301 | 90.061 | 87.135 | 95.835 | 89.103 | 89.772 | +2023-01-14 19:52:40,659 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:52:54,042 Epoch: [139][0/214] Time 11.795s (11.795s) Speed 2.7 samples/s Data 11.047s (11.047s) Loss 0.00017 (0.00017) Accuracy 0.952 (0.952) +2023-01-14 19:54:12,621 Epoch: [139][100/214] Time 0.781s (0.895s) Speed 41.0 samples/s Data 0.001s (0.125s) Loss 0.00015 (0.00017) Accuracy 0.955 (0.936) +2023-01-14 19:55:32,014 Epoch: [139][200/214] Time 0.798s (0.845s) Speed 40.1 samples/s Data 0.001s (0.070s) Loss 0.00020 (0.00017) Accuracy 0.923 (0.938) +2023-01-14 19:55:55,178 Test: [0/54] Time 11.415 (11.415) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 19:56:20,934 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 19:56:20,935 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 19:56:20,936 | pose_hrnet | 84.818 | 81.265 | 72.333 | 72.748 | 86.363 | 83.056 | 76.229 | 85.495 | 81.755 | 81.557 | +2023-01-14 19:56:20,938 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 19:56:34,890 Epoch: [140][0/214] Time 12.393s (12.393s) Speed 2.6 samples/s Data 11.649s (11.649s) Loss 0.00015 (0.00015) Accuracy 0.958 (0.958) +2023-01-14 19:57:53,248 Epoch: [140][100/214] Time 0.759s (0.899s) Speed 42.2 samples/s Data 0.000s (0.131s) Loss 0.00017 (0.00017) Accuracy 0.944 (0.941) +2023-01-14 19:59:12,468 Epoch: [140][200/214] Time 0.779s (0.846s) Speed 41.1 samples/s Data 0.001s (0.074s) Loss 0.00017 (0.00017) Accuracy 0.955 (0.940) +2023-01-14 19:59:35,461 Test: [0/54] Time 11.341 (11.341) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:00:01,084 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:00:01,085 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:00:01,085 | pose_hrnet | 92.050 | 87.683 | 79.373 | 82.654 | 94.026 | 90.063 | 87.812 | 95.047 | 89.379 | 89.874 | +2023-01-14 20:00:01,088 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:00:15,103 Epoch: [141][0/214] Time 12.410s (12.410s) Speed 2.6 samples/s Data 11.647s (11.647s) Loss 0.00014 (0.00014) Accuracy 0.958 (0.958) +2023-01-14 20:01:33,857 Epoch: [141][100/214] Time 0.775s (0.903s) Speed 41.3 samples/s Data 0.000s (0.131s) Loss 0.00017 (0.00017) Accuracy 0.933 (0.938) +2023-01-14 20:02:53,179 Epoch: [141][200/214] Time 0.768s (0.848s) Speed 41.7 samples/s Data 0.000s (0.073s) Loss 0.00019 (0.00017) Accuracy 0.906 (0.940) +2023-01-14 20:03:16,569 Test: [0/54] Time 11.681 (11.681) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:03:42,195 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:03:42,196 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:03:42,196 | pose_hrnet | 92.947 | 88.442 | 80.722 | 82.219 | 93.060 | 89.109 | 87.517 | 95.685 | 88.943 | 89.846 | +2023-01-14 20:03:42,199 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:03:57,296 Epoch: [142][0/214] Time 13.486s (13.486s) Speed 2.4 samples/s Data 12.745s (12.745s) Loss 0.00015 (0.00015) Accuracy 0.964 (0.964) +2023-01-14 20:05:15,928 Epoch: [142][100/214] Time 0.791s (0.912s) Speed 40.5 samples/s Data 0.000s (0.142s) Loss 0.00018 (0.00017) Accuracy 0.937 (0.940) +2023-01-14 20:06:35,273 Epoch: [142][200/214] Time 0.778s (0.853s) Speed 41.1 samples/s Data 0.000s (0.079s) Loss 0.00021 (0.00017) Accuracy 0.911 (0.940) +2023-01-14 20:06:58,334 Test: [0/54] Time 11.484 (11.484) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:07:24,037 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:07:24,037 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:07:24,038 | pose_hrnet | 93.126 | 88.444 | 80.546 | 82.396 | 93.181 | 90.184 | 87.287 | 96.157 | 89.052 | 90.174 | +2023-01-14 20:07:24,040 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:07:38,343 Epoch: [143][0/214] Time 12.679s (12.679s) Speed 2.5 samples/s Data 11.947s (11.947s) Loss 0.00015 (0.00015) Accuracy 0.936 (0.936) +2023-01-14 20:08:57,019 Epoch: [143][100/214] Time 0.809s (0.904s) Speed 39.6 samples/s Data 0.000s (0.134s) Loss 0.00019 (0.00017) Accuracy 0.937 (0.942) +2023-01-14 20:10:16,428 Epoch: [143][200/214] Time 0.778s (0.850s) Speed 41.1 samples/s Data 0.001s (0.075s) Loss 0.00014 (0.00017) Accuracy 0.982 (0.942) +2023-01-14 20:10:39,268 Test: [0/54] Time 11.249 (11.249) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:11:04,999 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:11:05,000 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:11:05,000 | pose_hrnet | 92.887 | 87.293 | 80.417 | 82.699 | 93.663 | 90.320 | 87.817 | 95.577 | 89.458 | 90.110 | +2023-01-14 20:11:05,002 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:11:19,052 Epoch: [144][0/214] Time 12.387s (12.387s) Speed 2.6 samples/s Data 11.661s (11.661s) Loss 0.00016 (0.00016) Accuracy 0.964 (0.964) +2023-01-14 20:12:37,824 Epoch: [144][100/214] Time 0.780s (0.903s) Speed 41.0 samples/s Data 0.000s (0.131s) Loss 0.00014 (0.00017) Accuracy 0.979 (0.941) +2023-01-14 20:13:57,361 Epoch: [144][200/214] Time 0.783s (0.849s) Speed 40.9 samples/s Data 0.000s (0.074s) Loss 0.00016 (0.00017) Accuracy 0.944 (0.940) +2023-01-14 20:14:20,409 Test: [0/54] Time 11.528 (11.528) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:14:46,121 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:14:46,121 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:14:46,122 | pose_hrnet | 92.469 | 88.074 | 80.833 | 82.441 | 94.087 | 91.467 | 87.437 | 95.630 | 89.138 | 90.253 | +2023-01-14 20:14:46,123 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:15:00,026 Epoch: [145][0/214] Time 11.693s (11.693s) Speed 2.7 samples/s Data 10.944s (10.944s) Loss 0.00021 (0.00021) Accuracy 0.874 (0.874) +2023-01-14 20:16:18,564 Epoch: [145][100/214] Time 0.775s (0.893s) Speed 41.3 samples/s Data 0.001s (0.124s) Loss 0.00017 (0.00017) Accuracy 0.943 (0.941) +2023-01-14 20:17:38,027 Epoch: [145][200/214] Time 0.795s (0.844s) Speed 40.3 samples/s Data 0.000s (0.070s) Loss 0.00020 (0.00017) Accuracy 0.936 (0.941) +2023-01-14 20:18:01,056 Test: [0/54] Time 11.367 (11.367) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:18:26,636 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:18:26,636 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:18:26,636 | pose_hrnet | 92.170 | 86.746 | 78.878 | 82.367 | 92.879 | 90.002 | 86.603 | 95.254 | 89.568 | 89.601 | +2023-01-14 20:18:26,638 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:18:39,954 Epoch: [146][0/214] Time 11.721s (11.721s) Speed 2.7 samples/s Data 11.007s (11.007s) Loss 0.00020 (0.00020) Accuracy 0.932 (0.932) +2023-01-14 20:19:58,643 Epoch: [146][100/214] Time 0.804s (0.895s) Speed 39.8 samples/s Data 0.001s (0.125s) Loss 0.00018 (0.00017) Accuracy 0.942 (0.944) +2023-01-14 20:21:18,092 Epoch: [146][200/214] Time 0.761s (0.845s) Speed 42.0 samples/s Data 0.000s (0.071s) Loss 0.00017 (0.00017) Accuracy 0.940 (0.941) +2023-01-14 20:21:41,017 Test: [0/54] Time 11.242 (11.242) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:22:06,637 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:22:06,637 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:22:06,638 | pose_hrnet | 85.296 | 86.167 | 76.894 | 80.718 | 89.199 | 86.492 | 82.590 | 92.103 | 88.174 | 86.703 | +2023-01-14 20:22:06,640 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:22:20,913 Epoch: [147][0/214] Time 12.582s (12.582s) Speed 2.5 samples/s Data 11.856s (11.856s) Loss 0.00016 (0.00016) Accuracy 0.948 (0.948) +2023-01-14 20:23:39,832 Epoch: [147][100/214] Time 0.781s (0.906s) Speed 41.0 samples/s Data 0.000s (0.135s) Loss 0.00018 (0.00017) Accuracy 0.942 (0.944) +2023-01-14 20:24:59,160 Epoch: [147][200/214] Time 0.763s (0.850s) Speed 41.9 samples/s Data 0.000s (0.076s) Loss 0.00014 (0.00017) Accuracy 0.963 (0.943) +2023-01-14 20:25:22,306 Test: [0/54] Time 11.317 (11.317) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:25:47,923 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:25:47,923 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:25:47,924 | pose_hrnet | 92.528 | 87.944 | 80.302 | 82.358 | 94.510 | 90.508 | 87.054 | 96.203 | 89.315 | 90.378 | +2023-01-14 20:25:47,926 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:26:02,158 Epoch: [148][0/214] Time 12.106s (12.106s) Speed 2.6 samples/s Data 11.374s (11.374s) Loss 0.00017 (0.00017) Accuracy 0.926 (0.926) +2023-01-14 20:27:20,576 Epoch: [148][100/214] Time 0.776s (0.896s) Speed 41.2 samples/s Data 0.000s (0.128s) Loss 0.00016 (0.00017) Accuracy 0.920 (0.943) +2023-01-14 20:28:40,108 Epoch: [148][200/214] Time 0.794s (0.846s) Speed 40.3 samples/s Data 0.000s (0.072s) Loss 0.00014 (0.00017) Accuracy 0.980 (0.943) +2023-01-14 20:29:03,234 Test: [0/54] Time 11.579 (11.579) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:29:28,730 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:29:28,730 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:29:28,731 | pose_hrnet | 91.273 | 85.719 | 76.356 | 79.226 | 91.431 | 89.300 | 83.650 | 94.443 | 87.617 | 88.180 | +2023-01-14 20:29:28,733 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:29:42,328 Epoch: [149][0/214] Time 12.031s (12.031s) Speed 2.7 samples/s Data 11.305s (11.305s) Loss 0.00019 (0.00019) Accuracy 0.924 (0.924) +2023-01-14 20:31:01,130 Epoch: [149][100/214] Time 0.802s (0.899s) Speed 39.9 samples/s Data 0.001s (0.128s) Loss 0.00012 (0.00017) Accuracy 0.958 (0.939) +2023-01-14 20:32:20,456 Epoch: [149][200/214] Time 0.785s (0.847s) Speed 40.8 samples/s Data 0.000s (0.072s) Loss 0.00016 (0.00017) Accuracy 0.942 (0.941) +2023-01-14 20:32:43,703 Test: [0/54] Time 11.544 (11.544) Loss 0.0000 (0.0000) Accuracy 0.000 (0.000) +2023-01-14 20:33:09,361 | Arch | Head | Shoulder | Elbow | Wrist | Hip | Knee | Ankle | Mouth | Tail | Mean | +2023-01-14 20:33:09,362 |---|---|---|---|---|---|---|---|---|---|---| +2023-01-14 20:33:09,362 | pose_hrnet | 91.990 | 87.211 | 79.689 | 81.739 | 93.904 | 89.875 | 87.737 | 96.065 | 89.030 | 89.925 | +2023-01-14 20:33:09,365 => saving checkpoint to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak +2023-01-14 20:33:10,929 => saving final model state to output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak\final_state.pth diff --git a/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-02-01-23-44_inference.log b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-02-01-23-44_inference.log new file mode 100644 index 00000000..2014cf9e --- /dev/null +++ b/output/ak_P2/ak/pose_hrnet/w32_256x256_adam_lr1e-3_ak/w32_256x256_adam_lr1e-3_ak_2023-02-01-23-44_inference.log @@ -0,0 +1,107 @@ +2023-02-01 23:44:29,860 Namespace(cfg='.\\experiments\\mpii\\hrnet\\w32_256x256_adam_lr1e-3_ak.yaml', dataDir='', logDir='', modelDir='', model_file='.\\output\\ak_P2\\ak\\pose_hrnet\\w32_256x256_adam_lr1e-3_ak\\model_best.pth', opts=[], path='C:\\Users\\huaxh\\Desktop\\test.mp4', prevModelDir='', save_batch_images_gt=False, save_heatmaps_gt=False) +2023-02-01 23:44:29,861 AUTO_RESUME: True +CUDNN: + BENCHMARK: True + DETERMINISTIC: False + ENABLED: True +DATASET: + COLOR_RGB: True + DATASET: ak + DATA_FORMAT: jpg + FLIP: True + HYBRID_JOINTS_TYPE: + IMAGE_ROOT: E:/huazhen/dataset/AnimalKingdom-PoseEstimation/dataset/ + NUM_JOINTS_HALF_BODY: 11 + PROB_HALF_BODY: -1.0 + ROOT: data/ak_P2 + ROT_FACTOR: 30 + SCALE_FACTOR: 0.25 + SELECT_DATA: False + TEST_SET: test + TRAIN_SET: train +DATA_DIR: +DEBUG: + DEBUG: True + SAVE_BATCH_IMAGES_GT: False + SAVE_BATCH_IMAGES_PRED: True + SAVE_HEATMAPS_GT: False + SAVE_HEATMAPS_PRED: True +GPUS: (0,) +LOG_DIR: log/ak_P2 +LOSS: + TOPK: 8 + USE_DIFFERENT_JOINTS_WEIGHT: False + USE_OHKM: False + USE_TARGET_WEIGHT: True +MODEL: + EXTRA: + FINAL_CONV_KERNEL: 1 + PRETRAINED_LAYERS: ['conv1', 'bn1', 'conv2', 'bn2', 'layer1', 'transition1', 'stage2', 'transition2', 'stage3', 'transition3', 'stage4'] + STAGE2: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4] + NUM_BRANCHES: 2 + NUM_CHANNELS: [32, 64] + NUM_MODULES: 1 + STAGE3: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4, 4] + NUM_BRANCHES: 3 + NUM_CHANNELS: [32, 64, 128] + NUM_MODULES: 4 + STAGE4: + BLOCK: BASIC + FUSE_METHOD: SUM + NUM_BLOCKS: [4, 4, 4, 4] + NUM_BRANCHES: 4 + NUM_CHANNELS: [32, 64, 128, 256] + NUM_MODULES: 3 + HEATMAP_SIZE: [64, 64] + IMAGE_SIZE: [256, 256] + INIT_WEIGHTS: True + NAME: pose_hrnet + NUM_JOINTS: 23 + PRETRAINED: + SIGMA: 2 + TAG_PER_JOINT: True + TARGET_TYPE: gaussian +OUTPUT_DIR: output/ak_P2 +PIN_MEMORY: True +PRINT_FREQ: 100 +RANK: 0 +TEST: + BATCH_SIZE_PER_GPU: 32 + BBOX_THRE: 1.0 + COCO_BBOX_FILE: + FLIP_TEST: True + IMAGE_THRE: 0.1 + IN_VIS_THRE: 0.0 + MODEL_FILE: .\output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak\model_best.pth + NMS_THRE: 0.6 + OKS_THRE: 0.5 + POST_PROCESS: True + SHIFT_HEATMAP: True + SOFT_NMS: False + USE_GT_BBOX: False +TRAIN: + BATCH_SIZE_PER_GPU: 32 + BEGIN_EPOCH: 0 + CHECKPOINT: + END_EPOCH: 150 + GAMMA1: 0.99 + GAMMA2: 0.0 + LR: 0.001 + LR_FACTOR: 0.1 + LR_STEP: [170, 200] + MOMENTUM: 0.9 + NESTEROV: False + OPTIMIZER: adam + RESUME: False + SHUFFLE: True + WD: 0.0001 +WORKERS: 4 +2023-02-01 23:44:30,034 => loading model from .\output\ak_P2\ak\pose_hrnet\w32_256x256_adam_lr1e-3_ak\model_best.pth +2023-02-01 23:44:32,291 load video: C:\Users\huaxh\Desktop\test.mp4 +2023-02-01 23:44:50,101 Test: [0/5] Time 17.768 (17.768) diff --git a/requirements.txt b/requirements.txt index 14f225c7..da6185c4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,11 +1,2 @@ -EasyDict==1.7 -opencv-python==3.4.1.15 -shapely==1.6.4 -Cython -scipy -pandas -pyyaml -json_tricks -scikit-image -yacs>=0.1.5 -tensorboardX==1.6 +json-tricks +yacs \ No newline at end of file diff --git a/requirements.txt.bak b/requirements.txt.bak new file mode 100644 index 00000000..14f225c7 --- /dev/null +++ b/requirements.txt.bak @@ -0,0 +1,11 @@ +EasyDict==1.7 +opencv-python==3.4.1.15 +shapely==1.6.4 +Cython +scipy +pandas +pyyaml +json_tricks +scikit-image +yacs>=0.1.5 +tensorboardX==1.6 diff --git a/tools/inference_video.py b/tools/inference_video.py new file mode 100644 index 00000000..121307cd --- /dev/null +++ b/tools/inference_video.py @@ -0,0 +1,121 @@ +import argparse +import os +from pathlib import Path +import pprint + +import torch +import torch.nn.parallel +import torch.backends.cudnn as cudnn +import torch.optim +import torch.utils.data +import torch.utils.data.distributed +import torchvision.transforms as transforms + +import _init_paths +from config import cfg +from config import update_config +from core.function import inference +from utils.utils import create_logger + +import models +import dataset + + +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +# device = torch.device('cpu') + + +def parse_args(): + parser = argparse.ArgumentParser(description='Train keypoints network') + # general + parser.add_argument('--cfg', + help='experiment configure file name', + required=True, + type=str) + + parser.add_argument('opts', + help="Modify config options using the command-line", + default=None, + nargs=argparse.REMAINDER) + + parser.add_argument('--modelDir', + help='model directory', + type=str, + default='') + parser.add_argument('--logDir', + help='log directory', + type=str, + default='') + parser.add_argument('--dataDir', + help='data directory', + type=str, + default='') + parser.add_argument('--prevModelDir', + help='prev Model directory', + type=str, + default='') + + parser.add_argument("--save_batch_images_gt", action="store_true") + parser.add_argument("--save_heatmaps_gt", action="store_true") + parser.add_argument("--model_file", help="model file (.pth)", type=str, required=True) + parser.add_argument("--path", help="video path or directory", type=str, required=True) + + args = parser.parse_args() + return args + + +def main(video_path): + + logger.info(pprint.pformat(args)) + logger.info(cfg) + + ### check cudnn related settings + cudnn.benchmark = cfg.CUDNN.BENCHMARK + torch.backends.cudnn.deterministic = cfg.CUDNN.DETERMINISTIC + torch.backends.cudnn.enabled = cfg.CUDNN.ENABLED + + ### load model + model = eval('models.'+cfg.MODEL.NAME+'.get_pose_net')(cfg, is_train=False) + if cfg.TEST.MODEL_FILE: + logger.info('=> loading model from {}'.format(cfg.TEST.MODEL_FILE)) + model.load_state_dict(torch.load(cfg.TEST.MODEL_FILE), strict=False) + else: + model_state_file = os.path.join( + final_output_dir, 'final_state.pth' + ) + logger.info('=> loading model from {}'.format(model_state_file)) + model.load_state_dict(torch.load(model_state_file)) + model = torch.nn.DataParallel(model, device_ids=cfg.GPUS).cuda() + + # prepare data loader + normalize = transforms.Normalize( + mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] + ) + transform=transforms.Compose([ + transforms.ToTensor(), + transforms.Resize(cfg.MODEL.IMAGE_SIZE), + normalize, + ]) + dataset = eval('dataset.'+cfg.DATASET.DATASET+"inference")( + cfg, video_path, transform + ) + dataloader = torch.utils.data.DataLoader( + dataset, + batch_size=cfg.TEST.BATCH_SIZE_PER_GPU*len(cfg.GPUS), + shuffle=False, + num_workers=cfg.WORKERS, + pin_memory=True + ) + + ### inference on video file + save_dir = os.path.join("predicted_frames", Path(video_path).stem) + os.makedirs(save_dir, exist_ok=True) + inference(cfg, dataloader, dataset, model, final_output_dir, device, save_dir) + + +if __name__ == '__main__': + ### load configuration + args = parse_args() + update_config(cfg, args) + logger, final_output_dir, tb_log_dir = create_logger(cfg, args.cfg, 'inference') + main(args.path) diff --git a/tools/train.py b/tools/train.py index 039c5487..56204920 100755 --- a/tools/train.py +++ b/tools/train.py @@ -20,7 +20,7 @@ import torch.utils.data import torch.utils.data.distributed import torchvision.transforms as transforms -from tensorboardX import SummaryWriter +# from tensorboardX import SummaryWriter import _init_paths from config import cfg @@ -37,6 +37,10 @@ import models +device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') +# device = torch.device('cpu') + + def parse_args(): parser = argparse.ArgumentParser(description='Train keypoints network') # general @@ -99,40 +103,45 @@ def main(): final_output_dir) # logger.info(pprint.pformat(model)) - writer_dict = { - 'writer': SummaryWriter(log_dir=tb_log_dir), - 'train_global_steps': 0, - 'valid_global_steps': 0, - } + # writer_dict = { + # 'writer': SummaryWriter(log_dir=tb_log_dir), + # 'train_global_steps': 0, + # 'valid_global_steps': 0, + # } dump_input = torch.rand( (1, 3, cfg.MODEL.IMAGE_SIZE[1], cfg.MODEL.IMAGE_SIZE[0]) ) - writer_dict['writer'].add_graph(model, (dump_input, )) + # writer_dict['writer'].add_graph(model, (dump_input, )) logger.info(get_model_summary(model, dump_input)) - model = torch.nn.DataParallel(model, device_ids=cfg.GPUS).cuda() + if device.type == "cuda": + model = torch.nn.DataParallel(model, device_ids=cfg.GPUS).to(device) + else: + model = model.to(device) # define loss function (criterion) and optimizer criterion = JointsMSELoss( use_target_weight=cfg.LOSS.USE_TARGET_WEIGHT - ).cuda() + ).to(device) # Data loading code normalize = transforms.Normalize( mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225] ) train_dataset = eval('dataset.'+cfg.DATASET.DATASET)( - cfg, cfg.DATASET.ROOT, cfg.DATASET.TRAIN_SET, True, - transforms.Compose([ + cfg, cfg.DATASET.ROOT, cfg.DATASET.TRAIN_SET, True, + img_root=cfg.DATASET.IMAGE_ROOT, + transform=transforms.Compose([ transforms.ToTensor(), normalize, ]) ) valid_dataset = eval('dataset.'+cfg.DATASET.DATASET)( cfg, cfg.DATASET.ROOT, cfg.DATASET.TEST_SET, False, - transforms.Compose([ + img_root=cfg.DATASET.IMAGE_ROOT, + transform=transforms.Compose([ transforms.ToTensor(), normalize, ]) @@ -183,15 +192,13 @@ def main(): lr_scheduler.step() # train for one epoch - train(cfg, train_loader, model, criterion, optimizer, epoch, - final_output_dir, tb_log_dir, writer_dict) + # train(cfg, train_loader, model, criterion, optimizer, epoch, final_output_dir, tb_log_dir, writer_dict) + train(cfg, train_loader, model, criterion, optimizer, epoch, final_output_dir, tb_log_dir, device=device) # evaluate on validation set - perf_indicator = validate( - cfg, valid_loader, valid_dataset, model, criterion, - final_output_dir, tb_log_dir, writer_dict - ) + # perf_indicator = validate(cfg, valid_loader, valid_dataset, model, criterion, final_output_dir, tb_log_dir, writer_dict) + perf_indicator = validate(cfg, valid_loader, valid_dataset, model, criterion, final_output_dir, tb_log_dir, device=device) if perf_indicator >= best_perf: best_perf = perf_indicator @@ -216,7 +223,7 @@ def main(): final_model_state_file) ) torch.save(model.module.state_dict(), final_model_state_file) - writer_dict['writer'].close() + # writer_dict['writer'].close() if __name__ == '__main__':