semantic image segmentation networks implemented in tensorflow
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datasets FCN Jan 13, 2017
deployment FCN Jan 13, 2017
nets FCN Jan 13, 2017
preprocessing FCN Jan 13, 2017
scripts FCN Jan 13, 2017
.gitignore initial checkin Dec 30, 2016
.pylintrc initial checkin Dec 30, 2016
LICENSES.md FCN Jan 13, 2017
README.md FCN Jan 13, 2017
eval.py FCN Jan 13, 2017
prepare_data.py FCN Jan 13, 2017
train.py FCN Jan 13, 2017

README.md

Summary

⚠️ Work in progress ⚠️

A collection of semantic image segmentation models implemented in TensorFlow. Contains data-loaders for the generic and medical benchmark datasets.

Hopefully this project will enable researchers to spend less time scaffolding and more time building.

Datasets & Benchmarks

Generic

Medical

  • MICCAI - Brain Tumor Image Segmentation Challenge (BRATS)
  • MICCAI - Ischemic Stroke Lesion Segmentation (ISLES)

Networks & Models

Generic

Medical

Usage

See ./scipts/

Requirements

Resources

Learn

  1. TensorFlow Deep Learning Course Get hands on right away with tensorflow and deep learning.
  2. Machine Learning, Andrew Ng Deeper dive into basics, less hands .
  3. Stanford CS231n videos I can't overstate how fantastic the notes, and videos are.
  4. Deep Learning : Book Helpful reference for filling in gaps.
  5. Above papers, starting with Fully Convolutional Networks for Semantic Segmentation and video

Code

Contributing

Please do. PEP-8, google style with 2 space idents 🤦️.