A newer version of the Streamlit SDK is available:
1.54.0
metadata
license: mit
title: PetroSeg
sdk: streamlit
emoji: 👀
colorFrom: red
colorTo: yellow
Unsupervised Segmentation App with Streamlit and PyTorch
Table of Contents
- Introduction
- Acknowledgments
- Requirements
- Installation
- How to Run
- Code Explanation
- Contributing
- License
Introduction 🌟
This project is a web application built using Streamlit and PyTorch. It performs unsupervised segmentation on uploaded images. The segmented image can be downloaded, and the colors of the segments can be customized.
Acknowledgments 🙏
This code is inspired from the project pytorch-unsupervised-segmentation by kanezaki. The original project is based on the paper "Unsupervised Image Segmentation by Backpropagation" presented at IEEE ICASSP 2018. The code is optimized for thin section images and microscopy analysis.
Requirements 📋
- Python 3.x
- Streamlit
- PyTorch
- OpenCV
- NumPy
- scikit-image
- PIL
- base64
Installation 🛠️
- Clone the repository
git clone https://github.com/your-repo/unsupervised-segmentation.git - Navigate to the project directory
cd unsupervised-segmentation - Install the required packages
pip install -r requirements.txt
How to Run 🚀
- Navigate to the project directory
cd unsupervised-segmentation - Run the Streamlit app
streamlit run app.py
Contributing 🤝
Feel free to open issues and pull requests!
License 📜
This project is licensed under the MIT License.