https://github.com/anras5/bloodvessels

Detecting Retinal Blood Vessels with Deep Learning
https://github.com/anras5/bloodvessels

deep-learning image-processing opencv python pytorch

Last synced: 2 months ago
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Detecting Retinal Blood Vessels with Deep Learning

• Host: GitHub
• URL: https://github.com/anras5/bloodvessels
• Owner: anras5
• Created: 2023-04-26T15:55:11.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2023-05-05T09:37:18.000Z (about 2 years ago)
• Last Synced: 2025-01-21T17:49:59.060Z (4 months ago)
• Topics: deep-learning, image-processing, opencv, python, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 5.35 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Retinal blood vessels segmentation

Detection of retinal blood vessels using classical methods (edge detection using filters) and deep neural network methods (UNet).

## Web application

Windows-64

1. Download current UNet release from [Releases](https://github.com/anras5/BloodVessels/releases).

2. Place downloaded `.pth` file in `models` folder. 

3. Execute commands:

```commandline

conda create --name  --file .\requirements.txt

conda activate 

python main.py

```

Web application allows the user to upload their own images and see the results.

![img.png](readme-images/main_page.png)

![results.png](readme-images/results.png)

## Jupyter Notebook

All core functionalities of the project are located in the `notebooks` folder.

## Built with

- Python 3.9

- PyTorch

- OpenCV

- Flask

## Contact

[email protected]