This is my codes that can visualize the psnr image in testing videos.

Future Frame Prediction for Anomaly Detection – A New Baseline

This is a fantastic work in Video-level Anomaly Detection, published in CVPR2018. ShanghaiTech svip-lab has given their work in [Github]. Moreover, this work also have an interesting video in [YouTube]. And we can see that when anomaly examples happened, PSNR images will have a low response. Such is an example in avenue dataset.


Testing images through PSNR image on your saved models

After you have trained you pre-trained model, you need to make sure that you have done every step under the instruction of authors. You need to put into Codes folder. Running the sript (as avenue datasets and video04 for examples), make sure cd into Codes folder at first.

python --dataset avenue
                         --test_folder ../Data/avenue/testing/frames
                         --gpu 0
                         --snapshot_dir checkpoints/pretrains/avenue
                         --video_num 4

After you have run this script, just need to wait a few minutes, you can have an image just like this.

**Notes : ** I don't specify folder saving testing_psnr images in my code. But I think this is an easy work.