/Tissue-Image-Segmentation

Re-implementation of popular tissue image segmentation models

Primary LanguagePython

Tissue-Image-Segmentation

unofficial re-implementation of popular tissue image segmentation models

Support Model:

  • UNet
  • Dist
  • DCAN
  • MicroNet
  • FullNet
  • CDNet

Dataset Prepare

Please check this doc

Supported Dataset:

  • MoNuSeg;
  • CoNSeP;
  • CPM17;
  • CoNIC;

Installation

  1. Install MMCV-full (Linux recommend): pip install MMCV-full==1.3.13;
  2. Install requirements package: pip install -r requirements.txt;
  3. Download tiseg: git clone https://github.com/sennnnn/Torch-Image-Segmentation;
  4. Install tiseg: pip install -e .;

Usage

Training

# single gpu training
python tools/train.py [config_path]
# multiple gpu training
./tools/dist_train.sh [config_path] [num_gpu]
# demo (cdnet for CPM17 dataset on 1 gpu)
python tools/train.py configs/unet/unet_vgg16_radam-lr5e-4_bs16_256x256_7k_cpm17.py
# demo (unet for CPM17 dataset on 4 gpu)
./tools/dist_train.py configs/unet/unet_vgg16_radam-lr5e-4_bs16_256x256_7k_cpm17.py 4

Evaluation

# single gpu evaluation
python tools/test.py [config_path]
# multiple gpu evaluation
./tools/dist_test.py [config_path] [num_gpu]

Thanks

This repo follow the design mode of mmsegmentation & detectron2.