Comments (1)
avinashpaliwal
commented on May 22, 2024
The model accepts dimensions in multiples of a number as it is an encoder decoder architecture with skip connections. Therefore, the images are resized before being passed to the model. The generated images are automatically resized back to the input dimensions by ffpmeg.
Changing the mean values may not create that much of a visual difference but might actually introduce some minor artifacts / a small drop in model's performance.
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Related Issues (20)
- ffmpeg error while running evaluation code. HOT 1
- Output interpolated image frames are of different size then input frames?
- What is the function of transforms.Normalize(mean=negmean, std=std)? Why use a negative mean๏ผ
- Error converting file:D:\Coding\JAVASCRIPT\recless\out\4fpsRecording.mkv. Exiting.
- PackagesNotFoundError: torchvision-cpu==0.2.0 HOT 3
- Runtime Error (Traceback Attached) HOT 23
- Frames are not extracted for any input video
- Differences with butterflow
- Slowdown a point of the video HOT 1
- Why Are fps And sf Setting Separate And Update ReadMe HOT 2
- "index 1 is out of bounds for dimension 0 with size 1" HOT 2
- Reference frames are different from the original ones. HOT 1
- sh: /Users/*/Downloads/ffmpeg/ffmpeg: No such file or directory HOT 2
- Add local file to Google Colab?? Or change length??
- How can I find the dataset of 240-fps video from YouTube HOT 1
- Training
- Objective metrics
- Could be faster by not saving PNG frames
- Image edge flicker
- low rate of utilization in test video
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