Official pytorch implementation for the paper entitled "Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw Puzzles" (ECCV 2022)
Please make sure that you have sufficient storage.
python gen_patches.py --dataset shanghaitech --phase test --filter_ratio 0.8 --sample_num 9
Dataset | # Patch (train) | # Patch (test) | filter ratio | sample num | storage |
---|---|---|---|---|---|
Ped2 | 27660 | 31925 | 0.5 | 7 | 20G |
Avenue | 96000 | 79988 | 0.8 | 7 | 58G |
Shanghaitech | 145766 | 130361 | 0.8 | 9 | 119G |
Train a model:
python main.py --dataset shanghaitech --val_step 100 --print_interval 20 --batch_size 192 --sample_num 9 --epochs 100 --static_threshold 0.2
python main.py --dataset shanghaitech --sample_num 9 --checkpoint xxx.pth