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Retina-Blood-Vessel-Segmentation-Using-UNET-In-Pytorch

sample_result

Dataset Link:- https://www.kaggle.com/datasets/andrewmvd/drive-digital-retinal-images-for-vessel-extraction?resource=download.

I have dropped 1st_manual folder from training directory and only using images and masks folder for both training and test directory.

How to Run:-

  1. Download the weights file from here:- https://drive.google.com/file/d/1FUnCgGrdL_o9B9etGYSmMFpURMVq4ZJi/view?usp=sharing

  2. Put the downloaded weights file in files directory.

  3. Clone the Repo/Download the Repo

Option 4.1:- If you have bash shell or git bash then you can download using running init_setup.sh file by running a following command. After running this you can directly jump to 4th point that is running the app.py

bash init_setup.sh

Option 4.2:- If you dont have bash shell or git bash then you can directly download requirements.txt file so that you can use this app.

pip install -r requirements.txt
  1. Run app.py
python app.py
  1. Now you will get a link in your terminal, open it or copy it and paste it in your browser, click on choose file, give the input image of Retina Images. You can find Retina Images in directory sample_image_inputs_to_app, and then click submit button, you will get your segmented output image.

If you have any doubt you can DM me on Instagram. My Insta ID:- https://www.instagram.com/developer_ashish.py

Lets connect on LinkedIn:- https://www.linkedin.com/in/ashish-kushwaha-45201b179

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