Showing content from https://github.com/caoyunkang/WinClip below:
caoyunkang/WinClip: [CVPR 2023] Unofficial re-implementation of "WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation".
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Unofficial implementation of:
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation, CVPR 2023 [Paper]
If you find the code useful, please consider citing our paper using the following BibTeX entry.
@InProceedings{Jeong_2023_CVPR,
author = {Jeong, Jongheon and Zou, Yang and Kim, Taewan and Zhang, Dongqing and Ravichandran, Avinash and Dabeer, Onkar},
title = {WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {19606-19616}
}
@misc{cao2023segment,
title={Segment Any Anomaly without Training via Hybrid Prompt Regularization},
author={Yunkang Cao and Xiaohao Xu and Chen Sun and Yuqi Cheng and Zongwei Du and Liang Gao and Weiming Shen},
year={2023},
eprint={2305.10724},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
- Python 3.7, PyTorch 1.10, and more in install.sh
Install python dependencies Download MVTec-AD dataset
Run run_winclip.py to reproduce the implementation results MVTec-AD Reported Re-implementation i-auroc p-auroc i-max-f1 p-max-f1 i-auroc p-auroc i-max-f1 p-max-f1 carpet 100.00 95.40 99.40 49.70 77.41 88.96 88.44 29.31 grid 98.80 82.20 98.20 18.60 48.87 75.08 85.71 8.40 leather 100.00 96.70 100.00 39.70 97.35 97.35 95.70 29.60 tile 100.00 77.60 99.40 32.60 79.87 75.87 85.25 29.30 wood 99.40 93.40 98.30 51.50 94.74 93.03 92.68 44.65 bottle 99.20 89.50 97.60 58.10 98.65 89.58 96.77 49.36 cable 86.50 77.00 84.50 19.70 53.30 56.23 76.03 10.22 capsule 72.90 86.90 91.40 21.70 62.03 88.56 90.46 9.95 hazelnut 93.90 94.30 89.70 37.60 71.29 94.34 80.00 33.63 metal_nut 97.10 61.00 96.30 32.40 37.59 42.67 89.42 21.67 pill 79.10 80.00 91.60 17.60 73.10 74.67 91.56 11.98 screw 83.30 89.60 87.40 13.50 64.87 90.09 85.61 9.09 toothbrush 87.50 86.90 87.90 17.10 41.94 84.02 84.51 9.26 transistor 88.00 74.70 79.50 30.50 62.25 67.46 60.87 15.95 zipper 91.50 91.60 92.90 34.40 89.31 92.08 90.42 31.48 Average 91.81 85.12 92.94 31.65 70.17 80.67 86.23 22.92 VisA Reported Re-implementation i-auroc p-auroc i-max-f1 p-max-f1 i-auroc p-auroc i-max-f1 p-max-f1 candle 95.40 88.90 89.40 22.50 79.03 86.24 72.36 6.32 capsules 85.00 81.60 83.90 9.20 53.58 62.00 77.22 1.36 cashew 92.10 84.70 88.40 13.20 70.66 79.54 80.99 6.94 chewinggum 96.50 93.30 94.80 41.10 84.94 97.01 83.76 36.17 fryum 80.30 88.50 82.70 22.10 52.60 86.73 80.33 15.17 macaroni1 76.20 70.90 74.20 7.00 49.98 34.37 66.67 0.07 macaroni2 63.70 59.30 69.80 1.00 49.56 31.49 66.67 0.06 pcb1 73.60 61.20 71.00 2.40 55.99 44.04 68.97 0.97 pcb2 51.20 71.60 67.10 4.70 61.58 64.47 69.26 0.70 pcb3 73.40 85.30 71.00 10.30 51.42 68.71 66.45 1.06 pcb4 79.60 94.40 74.90 32.00 78.94 91.86 74.56 22.75 pipe_fryum 69.70 75.40 80.70 12.30 82.80 93.65 83.48 22.45 Average 78.06 79.59 78.99 14.82 64.26 70.01 74.23 9.50
This project borrows some code from OpenCLip and CDO, thanks for their admiring contributions~!
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