Comments (1)
The easy way would be to convert the frames in your video from YUV to RGB to process them and then back to YUV once you got the interpolation results. You could alternatively also re-train the network with YUV input frames, which would be more work though.
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Related Issues (20)
- see_you_again_540.mp4 HOT 1
- vaule of interpolation HOT 1
- Make it work with pytorch installations from wheel packages HOT 1
- resolution HOT 1
- test HOT 1
- nn.Upsampling is deprecated. Use nn.functional.interpolate instead. HOT 1
- Flow calculation HOT 3
- Perceptual loss HOT 42
- some question about softmax-splatting HOT 1
- some question about code HOT 1
- Need your help to analyze the reason HOT 8
- Assertion Error in Video Frame interpolation HOT 1
- How to train a model HOT 1
- a question about the loss function LF HOT 1
- A question about the Instance normalization HOT 1
- load_state_dict_from_url() got an unexpected keyword argument 'file_name' HOT 1
- How to understand the meaning of the intIndex in sepconv.py? HOT 1
- AttributeError: 'Tensor' object has no attribute 'clip' HOT 2
- Checkpoint Downloading HOT 8
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