https://github.com/theoddysey/image-segmentation-pytorch-transformers
Semantic Segmentation with Segformers
https://github.com/theoddysey/image-segmentation-pytorch-transformers
imageclassification linear-regression machine-learning python
Last synced: 7 months ago
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Semantic Segmentation with Segformers
- Host: GitHub
- URL: https://github.com/theoddysey/image-segmentation-pytorch-transformers
- Owner: TheODDYSEY
- Created: 2023-09-22T18:52:26.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-30T19:41:29.000Z (over 2 years ago)
- Last Synced: 2025-06-04T04:42:16.074Z (12 months ago)
- Topics: imageclassification, linear-regression, machine-learning, python
- Language: Python
- Homepage:
- Size: 12.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Semantic Segmentation with Segformer
Semantic segmentation is a computer vision task that involves classifying each pixel in an image into a specific category. This repository contains code for performing semantic segmentation using the Segformer model, a transformer-based architecture designed for image segmentation tasks.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Installation](#installation)
- [Usage](#usage)
- [Custom Segmentation](#custom-segmentation)
- [Acknowledgments](#acknowledgments)
## Introduction
This project utilizes the Hugging Face Transformers library and Segformer pre-trained models to perform semantic segmentation on images. Semantic segmentation can be used in various applications, including object recognition, autonomous driving, and medical image analysis.
## Features
- Semantic segmentation using Segformer models.
- Integration with the Hugging Face Transformers library.
- Easy-to-use Python API for image segmentation tasks.
## Getting Started
### Prerequisites
Before you begin, ensure you have met the following requirements:
- Python 3.x
- Pip (Python package manager)
- GPU with CUDA support (recommended for faster inference)
### Installation
1. Clone this repository:
```bash
https://github.com/TheODDYSEY/Image-Segmentation-PyTorch-Transformers.git
cd semantic-segmentation
```
2. Install the required Python packages:
```bash
pip install -r requirements.txt
```
3. Download pre-trained Segformer model weights from Hugging Face (if needed):
```bash
python download_model.py
```
## Usage
To perform semantic segmentation on an image, you can use the provided `segment_image.py` script. Here's how to use it:
```bash
python segment_image.py --image_path path/to/your/image.jpg --output_path path/to/output/mask.png
```
This will generate a segmentation mask and save it as a PNG file.
## Custom Segmentation
If you want to perform semantic segmentation with custom Segformer models or train your own models, you can refer to the code in this repository as a starting point. Make sure to explore the Segformer documentation and Hugging Face Transformers documentation for more details on customizing and training models.
## Acknowledgments
- The Segformer model and pre-trained weights are provided by NVIDIA.
- This project is built using the Hugging Face Transformers library.
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