search

davide-coccomini / MINTIME-Multi-Identity-size-iNvariant-TIMEsformer-for-Video-Deepfake-Detection

Code for Video Deepfake Detector from "MINTIME: Multi-Identity Size-Invariant Video Deepfake Detection", paper available on IEEE Transactions on Information Forensics and Security.
58 stars 9 forks source link

About the question for poor performance #5

Open lijiayonghere opened 1 year ago

lijiayonghere commented 1 year ago

Hello, you guys did a very good deepfake video detection. But if you encounter some questions, I would like to ask you to help answer them: I successfully ran through, but at the cost of modifying several parts in it

(1. I added torch.backends.cudnn.enabled = false in front of the file. 2, I removed the state_dict in the state_dict = torch.load(pretrain_path),

and the code I run is "python predict.py --video_path examples/fake_1_face_0.mp4 --model_weights models/MINTIME_XCModel checkpoint30 --extractor_weights models/MINTIME_XC_Extractor_checkpoint30 --config config/size_invariant_timesformer.yaml"。 When I use your examples' video test, the results are all tested really, please ask me what to do, what caused it, thank you for your patience

davide-coccomini commented 1 year ago

Hi, are you sure that the weights are loading correctly? Also, I understand why you removed "state_dict" but why did you disabled cudnn?