https://github.com/giansimone/unet-pytorch

PyTorch implementation of a convolutional neural network (U-Net) for semantic segmentation of biomedical images.
https://github.com/giansimone/unet-pytorch

pytorch semantic-segmentation unet unet-pytorch unet-segmentation

Last synced: 2 months ago
JSON representation

PyTorch implementation of a convolutional neural network (U-Net) for semantic segmentation of biomedical images.

• Host: GitHub
• URL: https://github.com/giansimone/unet-pytorch
• Owner: giansimone
• License: mit
• Created: 2025-04-01T15:52:39.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-04-10T13:04:14.000Z (6 months ago)
• Last Synced: 2025-04-13T11:14:35.094Z (6 months ago)
• Topics: pytorch, semantic-segmentation, unet, unet-pytorch, unet-segmentation
• Language: Python
• Homepage:
• Size: 85.9 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
[![Python](https://img.shields.io/pypi/pyversions/unet-pytorch.svg)](https://badge.fury.io/py/unet-pytorch)

[![PyPI](https://badge.fury.io/py/unet-pytorch.svg)](https://badge.fury.io/py/unet-pytorch)

[![License](https://img.shields.io/github/license/giansimone/unet-pytorch)](https://github.com/giansimone/unet-pytorch/blob/main/LICENSE)

# unet-pytorch

PyTorch implementation of a convolutional neural network (U-Net) for semantic segmentation of biomedical images.

## Overview

This repository contains a PyTorch implementation of the U-Net architecture for semantic segmentation tasks.

U-Net is a convolutional neural network architecture that was originally designed for biomedical image segmentation.

## Installation

You can install the U-Net model using pip.

```bash

pip install unet-pytorch

```

We recommend using Python 3.11 or later and PyTorch 2.6 or later.

You can also clone the repository and install it in local development mode using poetry.

```bash

git clone https://github.com/giansimone/unet-pytorch.git

cd unet-pytorch

pip install poetry

poetry install

```

## Usage

To use the U-Net model, you can import the `UNet` class from the `unet_pytorch.model` module and create an instance of the model.

```python

import torch

from unet_pytorch.model import UNet

model = UNet(in_channels=1, out_channels=2)

input_tensor = torch.randn(1, 1, 512, 512)

output_tensor = model(input_tensor)

print(output_tensor.shape)  # Should be (1, 2, 512, 512)

```

## Training

To train the U-Net model, you can use the `unet_pytorch.train` module.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.