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RetinalNet

Semantic segmentation describes the process of associating every pixel of an image with a class label, such as person, animal and in our case artery or vein. This repository provides DeepLab-Resnet model trained on retinal images for sematic segmentation of arteries and veins .

Requirements

Python3 Tensorflow Numpy PIL

Trained model

Download trained model from here and put it in trained_model folder.

Inference

To perform inference over your own images, use the following command:

python inference.py /path/to/your/image /path/to/ckpt/file

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