Files

.github
assets
docs
examples
- accelerate-multigpu
- benchmarks
- cli
- image-classifier-finetuning
- nuclei_image_segmentation
  - Nuclei_Image_Segmentation.ipynb
  - README.md
  - dataset.py
  - dl_extract_prepare.sh
  - model.py
  - prepare_dataset.py
  - requirements.txt
  - train_valid_split.json
  - utils.py
- optuna
- rnn_classifer
- translation
- word_language_model
notebooks
scripts
skorch
.coveragerc
.gitignore
.readthedocs.yaml
CHANGES.md
CITATION
CONTRIBUTING.rst
Dockerfile
LICENSE
MANIFEST.in
README.rst
VERSION
pylintrc
requirements-dev.txt
requirements.txt
setup.cfg
setup.py

nuclei_image_segmentation

Update to PyTorch 1.11.0 (#846 )

Apr 24, 2022

fe71e3d · Apr 24, 2022

Name		Name	Last commit message	Last commit date
parent directory ..
Nuclei_Image_Segmentation.ipynb		Nuclei_Image_Segmentation.ipynb	Remove a bunch of "neutral" networks	Jun 6, 2020
README.md		README.md	Update to PyTorch 1.11.0 (#846 )	Apr 24, 2022
dataset.py		dataset.py	MRG: Adds image segmentation example (#303 )	Aug 10, 2018
dl_extract_prepare.sh		dl_extract_prepare.sh	MRG: Adds image segmentation example (#303 )	Aug 10, 2018
model.py		model.py	MRG: Adds image segmentation example (#303 )	Aug 10, 2018
prepare_dataset.py		prepare_dataset.py	MRG: Adds image segmentation example (#303 )	Aug 10, 2018
requirements.txt		requirements.txt	Increase notebook version to >=5.7.8 in nuclei example (#454 )	May 4, 2019
train_valid_split.json		train_valid_split.json	DOC: Updates seg tutorial to use freezer (#359 )	Oct 16, 2018
utils.py		utils.py	MRG: Adds image segmentation example (#303 )	Aug 10, 2018

README.md

Nuclei Image Segmentation With UNets

This tutorial can be viewed at nbviewer.

Setup

To run the notebook locally, please following the following setup procedure:

Install dependencies: python -m pip install -r requirements.txt
Follow Kaggle's installation and configuration documentation to install and configure the kaggle cli
Go to Kaggle's 2018 Data Science Bowl Competition, click on "Late Submission" and accept the terms and conditions to get access to the data.
Run ./dl_extract_prepare.sh to download, extract and prepare the data.

Running notebook

Start jupyter notebook jupyter notebook
Open Nuclei_Image_Segmentation.ipynb