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Binary Segmentation - PraNet-V2

📌 Overview

Welcome to the binary segmentation hub of PraNet-V2! 🏥✨

This directory contains everything you need for training, testing, and inference on polyp segmentation tasks. If you're looking for accurate medical image segmentation, you're in the right place! 💪🎉

📂 Directory Structure

binary/
├── models/                  # Pre-trained models
├── data/                    # Datasets (see the main README for details)
├── snapshots/               # Checkpoints saved during training
├── MyTrain_med.py           # Training script
├── MyTest_med.py            # Testing/inference script
├── eval.py                  # Evaluation script
├── utils/                   # Utility functions
└── README.md                # This file

🚀 How to Run

Training

python -W ignore MyTrain_med.py --model_type PraNet-V2

Inference

python -W ignore MyTest_med.py

Evaluation

python -W ignore eval.py

📥 Dataset Download

To get started, download the dataset by following the instructions in the main README and place it in binary/data/.

🏆 Citation

If you find our work useful, please consider citing us! 🏆👇

@article{hu2025pranet2,
  title={PraNet-V2: Dual-Supervised Reverse Attention for Medical Image Segmentation},
  author={Hu, Bo-Cheng and Ji, Ge-Peng and Shao, Dian and Fan, Deng-Ping},
  journal   = {arXiv preprint arXiv:2504.10986},
  year={2025},
  url       = {https://arxiv.org/abs/2504.10986}
}