Comments (5)
Hi @greggg123! There is no need to preprocess the videos of UCF101. We use decord
to decode the raw videos on the fly.
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@yztongzhan
Where can I get the train.csv, test.csv for UCF101 ?
Can you please provide the csv files you used (as you did for Kinetics) ?
I downloaded the original dataset and it only has these txt files :
classInd.txt
testlist01.txt
testlist02.txt
testlist03.txt
trainlist01.txt
trainlist02.txt
trainlist03.txt
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Hi, have you solved this problem now and what should be done with the UCF101 dataset?
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I believe this dataset has 3 train/test splits.
I don't know which split was used by this repo owners.
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Thank you very much for your reply. I'm trying to randomly select one of the split, but I'm having some problems in generating the csv file , the video is not being read correctly. Have you successfully generate the csv file based on one of the splitting methods? Can you share it? Looking forward to your reply!
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Related Issues (20)
- ModuleNotFoundError: No module named 'petrel_client'
- License of Kinetics-400
- video xxx not correctly load during training
- The GPU memory usage of UCF and Kinetics is different.
- TODO/videomae_pretrain_base_patch16_224_frame_16x4_tube_mask_ratio_0.9_e1600/checkpoint-1599.pth HOT 1
- HMDB checkpoint
- Rebuild Video
- the numberi of rebuild images is too small
- AttributeError: module 'torch._C' has no attribute '_get_privateuse1_backend_name'
- How to obtain the reconstructed image for inference and masked
- How good model handle the different duration of clips?
- How to convert .pth to .bin HOT 1
- KeyError: 'model' HOT 2
- VideoMAE might not be a useful model for video reconstruction? Or perhaps it only learns the most generic distribution within patches? HOT 2
- How to use VideoMAE for video regression task?
- ucf101,hmdb51 HOT 1
- After obtaining the .pth file from training, how do I convert it into a .bin file for performing inference?
- 关于微调损失函数 HOT 1
- How to conduct zero-shot evaluations?
- TypeError: VisionTransformer.__init__() got an unexpected keyword argument 'pretrained_cfg' HOT 1
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