arrowluo / videofeatureextractor Goto Github PK

Hello,

Thanks for the great work. Can I know what is the difference between this processed output and the official S3D features (https://www.di.ens.fr/willow/research/howto100m/)?

Thanks

thank you for your work！
when i run the extract.py in command
`python extract.py --csv=./input.csv --type=s3dg --batch_size=64 --num_decoding_thread=1
D:\Github\VideoFeatureExtractor
Loading S3DG ...
Weights from pretrained model not used in S3D:
text_module.word_embd.weight
text_module.fc1.weight
text_module.fc1.bias
text_module.fc2.weight
text_module.fc2.bias
loaded
D:\Github\VideoFeatureExtractor
Decoding video: D:/Github/VideoFeatureExtractor/data/1.mp4
ffprobe failed at: D:/Github/VideoFeatureExtractor/data/1.mp4
Video D:/Github/VideoFeatureExtractor/data/1.mp4 already processed.Decoding video: D:/Github/VideoFeatureExtractor/data/2.mp4

ffprobe failed at: D:/Github/VideoFeatureExtractor/data/2.mp4
Video D:/Github/VideoFeatureExtractor/data/2.mp4 already processed.`
Could you check with it?

@ArrowLuo
Hi! As you mentioned in the README,

And modified from https://github.com/antoine77340/video_feature_extractor.

Can I use multiple GPU to speed up feature extraction, just like https://github.com/antoine77340/video_feature_extractor#can-i-use-multiple-gpu-to-speed-up-feature-extraction-?

CUDA_VISIBLE_DEVICES=0 python extract.py --csv=./input.csv --type=s3dg --batch_size=64 --num_decoding_thread=4
CUDA_VISIBLE_DEVICES=1 python extract.py --csv=./input.csv --type=s3dg --batch_size=64 --num_decoding_thread=4
CUDA_VISIBLE_DEVICES=2 python extract.py --csv=./input.csv --type=s3dg --batch_size=64 --num_decoding_thread=4
CUDA_VISIBLE_DEVICES=3 python extract.py --csv=./input.csv --type=s3dg --batch_size=64 --num_decoding_thread=4