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https://github.com/LiuTingWed/SAM-Not-Perfect
Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-World Application
https://github.com/LiuTingWed/SAM-Not-Perfect
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Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-World Application
- Host: GitHub
- URL: https://github.com/LiuTingWed/SAM-Not-Perfect
- Owner: LiuTingWed
- Created: 2023-05-21T10:20:34.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-01T18:44:28.000Z (about 1 year ago)
- Last Synced: 2024-01-01T19:36:13.808Z (about 1 year ago)
- Language: Python
- Size: 1.03 MB
- Stars: 22
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Segment-Anything - [code
README
# Segment Anything Is Not Always Perfect
Code repository for our paper titled "[Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-World Applications](https://arxiv.org/abs/2304.05750)" (CVPRW Oral).
------
## Updates
+ [x] Another work, [Medical SAM Adapter](https://arxiv.org/abs/2304.12620) which addresses the issue of lacking domain-specific medical knowledge in the SAM, are available now.
+ [x] Long version of this work has been accepted by *Machine Intelligence Research*.
+ [x] This work is awarded as **[Best Paper](https://vision-based-industrial-inspection.github.io/cvpr-2023/)** (Most Insightful Paper) at the *CVPR'23 VISION Workshop*.
+ [x] Evaluation code has been released.
+ [x] This work has been accepted as an *Oral Presentation* at the *CVPR'23 VISION Workshop*.
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## Get Started
### Eval SAM in different dataset
1. Download the **vit_b, vit_h and vim_l** model from https://github.com/facebookresearch/segment-anything then put these models to the **model_ck** folder.
2. Prepared own datasets put into the **datasets** folder.
3. Set right path in /scripts/amg.py, then:
> run amg.py
### Chosen best results form the sam_output folder
1. After inferring, the SAM model generates predicted maps from a singer RGB image (**multimask_output=True**). Check right path in **sam_dice_f1_mae.py** or **sam_f1_dice_mae.py** to decide the best map selected by Dice or F1 metrics.
### Eval other methods in different dataset
1. Prepared these methods predicted maps to put into the **other_methods_output** folder.
2. Check right path in /scripts/other_methods_dice_mae.py, then:
> run other_methods_dice_mae.py
-------
## Datasets
The download links of the dataset involved in our work are provided below.
DUTS | COME15K | VT1000 | DIS | COD10K | SBU | CDS2K | ColonDB
:-: | :-: | :-: | :-: | :-: | :-: | :-: | :-:
[Link](http://saliencydetection.net/duts/) | [Link](https://github.com/jingzhang617/cascaded_rgbd_sod) | [Link](https://github.com/lz118/RGBT-Salient-Object-Detection) | [Link](https://xuebinqin.github.io/dis/index.html) | [Link](https://dengpingfan.github.io/pages/COD.html) | [Link](https://www3.cs.stonybrook.edu/~cvl/projects/shadow_noisy_label/index.html) | [Link](https://github.com/DengPingFan/CSU) | [Link](http://vi.cvc.uab.es/colon-qa/cvccolondb/)
-------
## Citation
If you find our work useful for your research or applications, please cite using this BibTeX:
```bibtex
@article{Jisam2024,
author={Ji, Wei and Li, Jingjing and Bi, Qi and Liu, Tingwei and Li, Wenbo and Cheng, Li},
journal={Machine Intelligence Research},
title={Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications},
year={2024},
volume={21},
pages={617--630},
publisher={Springer}
}
@misc{wu2023medical,
title={Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation},
author={Junde Wu and Wei Ji and Yuanpei Liu and Huazhu Fu and Min Xu and Yanwu Xu and Yueming Jin},
year={2023},
eprint={2304.12620},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
## Acknowledgement
Thanks for the efforts of the authors involved in the [Segment Anything](https://github.com/facebookresearch/segment-anything).