Retina blood vessel segmentation This repository contains the implementation of a convolutional neural network used to segment blood vessels in retina fundus images. This is a binary classification ...

About This project implements UNET-based segmentation for retinal vessel extraction using the DRIVE dataset. Built with PyTorch, it includes data preprocessing, model architecture, and training code.

PyTorch is a Python-based tensor computing library with high-level support for neural network architectures. It also supports offloading computation to GPUs.

PyTorch 1.10 is production ready, with a rich ecosystem of tools and libraries for deep learning, computer vision, natural language processing, and more. Here's how to get started with PyTorch.