.gitignore

@@ -35,3 +35,5 @@ datasets/vg/
 # MacOS
 .DS_Store
 
+# slurm
+slurm-output/

configs/e2e_relation_X_101_32_8_FPN_1x.yaml

@@ -120,6 +120,7 @@ SOLVER:
     FACTOR: 0.1
     MAX_DECAY_STEP: 3
 OUTPUT_DIR: './output/relation_baseline'
+DATA_STAT_DIR: './output/relation_baseline'
 TEST:
   ALLOW_LOAD_FROM_CACHE: False
   RELATION:
@@ -128,3 +129,11 @@ TEST:
     LATER_NMS_PREDICTION_THRES: 0.5
   CUSTUM_EVAL: False       # eval SGDet model on custum images, output a json
   CUSTUM_PATH: '.'         # the folder that contains the custum images, only jpg files are allowed  
+GEN_IMG: # Generated images eval options
+  EVAL: False
+  ANNO_DIR: ""
+  ANNO_FILE: ""
+  BASE_DIR: ""
+  FOLDER_NAME: ""
+  NUM_ROUNDS: 1
+  RESOLUTION: 256

maskrcnn_benchmark/config/defaults.py

@@ -584,6 +584,7 @@
 # Misc options
 # ---------------------------------------------------------------------------- #
 _C.OUTPUT_DIR = "."
+_C.DATA_STAT_DIR = "."
 _C.DETECTED_SGG_DIR = "."
 _C.GLOVE_DIR = "."
 
@@ -599,3 +600,16 @@
 
 # Enable verbosity in apex.amp
 _C.AMP_VERBOSE = False
+
+# ---------------------------------------------------------------------------- #
+# Generated images eval options
+# ---------------------------------------------------------------------------- #
+_C.GEN_IMG = CN()
+
+_C.GEN_IMG.EVAL = False
+_C.GEN_IMG.ANNO_DIR = ""
+_C.GEN_IMG.ANNO_FILE = ""
+_C.GEN_IMG.BASE_DIR = ""
+_C.GEN_IMG.FOLDER_NAME = ""
+_C.GEN_IMG.NUM_ROUNDS = 1
+_C.GEN_IMG.RESOLUTION = 256

maskrcnn_benchmark/config/paths_catalog.py

@@ -7,7 +7,7 @@
 
 class DatasetCatalog(object):
     #DATA_DIR = "/home/users/alatif/data/ImageCorpora/"
-    DATA_DIR = "/media/rafi/Samsung_T5/_DATASETS/"
+    DATA_DIR = "datasets"
     DATASETS = {
         "coco_2017_train": {
             "img_dir": "coco/train2017",
@@ -107,14 +107,14 @@ class DatasetCatalog(object):
             "ann_file": "cityscapes/annotations/instancesonly_filtered_gtFine_test.json"
         },
         "VG_stanford_filtered": {
-            "img_dir": "vg/VG_100K",
+            "img_dir": "/h/bichengx/site-pkgs/VG-SGG/VG_100K_3",
             "roidb_file": "vg/VG-SGG.h5",
             "dict_file": "vg/VG-SGG-dicts.json",
             "image_file": "vg/image_data.json",
         },
         "VG_stanford_filtered_with_attribute": {
-            "img_dir": "vg/VG_100K",
-            "roidb_file": "vg/VG-SGG-with-attri.h5",
+            "img_dir": "/h/bichengx/site-pkgs/VG-SGG/VG_100K_3",
+            "roidb_file": "/h/bichengx/site-pkgs/VG-SGG/VG-SGG-with-attri.h5",
             "dict_file": "vg/VG-SGG-dicts-with-attri.json",
             "image_file": "vg/image_data.json",
             "capgraphs_file": "vg/vg_capgraphs_anno.json",

maskrcnn_benchmark/data/build.py

@@ -16,6 +16,7 @@
 
 from .collate_batch import BatchCollator, BBoxAugCollator
 from .transforms import build_transforms
+from maskrcnn_benchmark.data.datasets.vg_gen_img import build_gen_img_dataset
 
 # by Jiaxin
 def get_dataset_statistics(cfg):
@@ -33,7 +34,8 @@ def get_dataset_statistics(cfg):
     dataset_names = cfg.DATASETS.TRAIN
 
     data_statistics_name = ''.join(dataset_names) + '_statistics'
-    save_file = os.path.join(cfg.OUTPUT_DIR, "{}.cache".format(data_statistics_name))
+    # save_file = os.path.join(cfg.OUTPUT_DIR, "{}.cache".format(data_statistics_name))
+    save_file = os.path.join(cfg.DATA_STAT_DIR, "{}.cache".format(data_statistics_name))
 
     if os.path.exists(save_file):
         logger.info('Loading data statistics from: ' + str(save_file))
@@ -224,7 +226,12 @@ def make_data_loader(cfg, mode='train', is_distributed=False, start_iter=0, data
 
     # If bbox aug is enabled in testing, simply set transforms to None and we will apply transforms later
     transforms = None if not is_train and cfg.TEST.BBOX_AUG.ENABLED else build_transforms(cfg, is_train)
-    datasets = build_dataset(cfg, dataset_list, transforms, DatasetCatalog, is_train)
+
+    if cfg.GEN_IMG.EVAL:
+        assert (aspect_grouping == [])
+        datasets = build_gen_img_dataset(cfg, transforms)
+    else:
+        datasets = build_dataset(cfg, dataset_list, transforms, DatasetCatalog, is_train)
 
     if is_train:
         # save category_id to label name mapping

maskrcnn_benchmark/data/datasets/__init__.py

@@ -3,5 +3,6 @@
 from .voc import PascalVOCDataset
 from .concat_dataset import ConcatDataset
 from .visual_genome import VGDataset
+from .vg_gen_img import VG_Gen_Img_Dataset
 
-__all__ = ["COCODataset", "ConcatDataset", "PascalVOCDataset", "VGDataset"]
+__all__ = ["COCODataset", "ConcatDataset", "PascalVOCDataset", "VGDataset", "VG_Gen_Img_Dataset"]

maskrcnn_benchmark/data/datasets/evaluation/__init__.py

@@ -25,6 +25,8 @@ def evaluate(cfg, dataset, predictions, output_folder, logger, **kwargs):
         return voc_evaluation(**args)
     elif isinstance(dataset, datasets.VGDataset):
         return vg_evaluation(**args)
+    elif isinstance(dataset, datasets.VG_Gen_Img_Dataset):
+        return vg_evaluation(**args)
     else:
         dataset_name = dataset.__class__.__name__
         raise NotImplementedError("Unsupported dataset type {}.".format(dataset_name))