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https://github.com/HuiqianLi/ASPS
[MICCAI 2024] Repository for "ASPS: Augmented Segment Anything Model for Polyp Segmentation"
https://github.com/HuiqianLi/ASPS
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[MICCAI 2024] Repository for "ASPS: Augmented Segment Anything Model for Polyp Segmentation"
- Host: GitHub
- URL: https://github.com/HuiqianLi/ASPS
- Owner: HuiqianLi
- Created: 2024-03-08T03:41:20.000Z (10 months ago)
- Default Branch: master
- Last Pushed: 2024-08-09T07:11:24.000Z (5 months ago)
- Last Synced: 2024-08-09T08:34:38.100Z (5 months ago)
- Language: Python
- Homepage:
- Size: 280 KB
- Stars: 12
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Segment-Anything - [code
README
# [ASPS: Augmented Segment Anything Model for Polyp Segmentation](https://arxiv.org/abs/2407.00718)
### News
2024/6/25: 🎉Our method was accepted by **MICCAI 2024**.
2024/5/21: Add data loader for Skin Lesion Segmentation (ISIC2017).
### Requirements
Install the dependencies of [SAM](https://github.com/facebookresearch/segment-anything).
Install mmcv-full for CNN encoder.
```shell
conda create --name ASPS python=3.8
conda activate ASPS
pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu116
pip install mmcv-full==1.6.2 -f https://download.openmmlab.com/mmcv/dist/cu116/torch1.12/index.html
pip install tqdm
pip install opencv-python
pip install albumentations==1.3.0
```
### Dataset
We conduct extensive experiments on five polyp segmentation datasets
following [PraNet](https://github.com/DengPingFan/PraNet).
> For skin lesion segmentation: following [EGE-UNet](https://github.com/JCruan519/EGE-UNet), needing to modify `from dataset.Segmentation_other` to `from dataset.Segmentation_isic` both in `train.py` and `infer.py`.
### Training
We used `train.py` to train our framework.
The `--exp_name` is the name of the experiment, and `--polyp_dir` is the path to the training dataset.
```bash
python train.py --exp_name '0308_E_L' --polyp_dir "polyp_seg/TrainDataset/"
```
### Evaluating
We used `infer.py` to evaluate our framework.
The `--dataset_name` is the name of the dataset, and `--test_seg_dir` is the path to the testing dataset.
```shell
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-300' --test_seg_dir "polyp_seg/TestDataset/CVC-300/"
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-ClinicDB' --test_seg_dir "polyp_seg/TestDataset/CVC-ClinicDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-ColonDB' --test_seg_dir "polyp_seg/TestDataset/CVC-ColonDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'ETIS-LaribPolypDB' --test_seg_dir "polyp_seg/TestDataset/ETIS-LaribPolypDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'Kvasir' --test_seg_dir "polyp_seg/TestDataset/Kvasir/"
```
You can directly run the `train.sh` to train and evaluate our framework.
**Note**: If using SUN_SEG dataset, the training and evaluating codes are in `'scripts/'`.
### Visualize and Inference
To inference single image or visualize the results, run `vis.py`.
| raw image | pred mask | GT |
| :----------------: | :----------------: | :----------------: |
|  |  |  |
### Checkpoints
| Name | Repo | Download | Password |
| ----------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | -------- |
| MSCAN-B | [SegNeXt](https://github.com/visual-attention-network/segnext) | https://rec.ustc.edu.cn/share/4c1d2ab0-344e-11ef-b416-0bee023cca0f | 31tz |
| MSCAN-L | [SegNeXt](https://github.com/visual-attention-network/segnext) | https://rec.ustc.edu.cn/share/18e3cd80-344e-11ef-bbf4-79b40a1f9d5c | pl1v |
| SAM-B-ASPS | | https://rec.ustc.edu.cn/share/5e9be4b0-344a-11ef-a151-6b2a0b8eedb8 | li92 |
| SAM-H-ASPS | | https://rec.ustc.edu.cn/share/fc3da400-344a-11ef-b1d5-932017a40fd5 | 3w0g |
| EfficientSAM-ASPS | [EfficientSAM](https://github.com/yformer/EfficientSAM) | https://rec.ustc.edu.cn/share/c9696fb0-344a-11ef-b24f-3f1e0faf0fb9 | xoqh |
### Citation
```
@article{li2024asps,
title={ASPS: Augmented Segment Anything Model for Polyp Segmentation},
author={Li, Huiqian and Zhang, Dingwen and Yao, Jieru and Han, Longfei and Li, Zhongyu and Han, Junwei},
journal={arXiv preprint arXiv:2407.00718},
year={2024}
}
```