Metadata-Version: 2.1
Name: seg
Version: 0.0.1
Summary: Image segmentation tools specially for blood vessels.
Home-page: http://pypi.python.org/pypi/seg/
Author: Yinsheng Zhang (Ph.D.)
Author-email: oo@zju.edu.cn
License: LICENSE.txt
Description-Content-Type: text/markdown
License-File: LICENCE

# About
This is a collection of image segmentation projects adjusted for fundus blood vessel segmentation.  

## 1. unet_keras result:  
<img src='.\model\unet_keras\final_results.jpg'>


## 2. unet_torch result:  
<img src='.\model\unet_torch\results\SEH\L-20190710105904098.png'>

## 4. mrsg_torch result (sota):  
<img src='.\model\mrsg_torch\results\test\SEH\prediction_.2\1_L-20190710105904098.jpg'>



# Run

Provide four flavors: 

| Module  | How to run | Model weights location | Notebooks |
| ------------ |:-------------------:|:-------------------:|:-------------------:|
| model.unet_keras | run_training.py, run_testing.py | test/test_best_weights.h5 | 1. U-Net - Introduction.ipynb, 2. Fundus Blood Vessel Segmentation.ipynb   |
| model.unet_torch | train.py, test.py | weights/checkpoint.pth | README.md |
| model.multiple_torch | all codes are inside .ipynb files | best_binclass_model.h5, best_multiclass_model.h5 |  1. binary segmentation (camvid).ipynb and 2. multiclass segmentation (camvid).ipynb |
| model.mrsg_torch  | python train.py --cfg lib/All.yaml, python inference.py --lib/DRIVE.yaml | results/test/ALL/model/*.pth | README.md |

# Credits
The following github projects are used:  

| Module  | based on | url |
| ------------ |:-------------------:|:-------------------:|
| model.unet_keras        | Retina blood vessel segmentation with a convolution neural network (U-net)   | https://github.com/orobix/retina-unet        |
| model.unet_torch        | Retina-Blood-Vessel-Segmentation-in-PyTorch | https://github.com/nikhilroxtomar/Retina-Blood-Vessel-Segmentation-in-PyTorch |
| model.multiple_torch        | Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. | https://github.com/qubvel/segmentation_models |  
| model.mrsg_torch        | Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022) | https://github.com/Limingxing00/Retinal-Vessel-Segmentation-ISBI2022/ |


# Todo
make a thorough refactor; vessel region detection
