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how to place and preprocess these datasets #78

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renyuanzhe opened this issue May 8, 2024 · 7 comments
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how to place and preprocess these datasets #78

renyuanzhe opened this issue May 8, 2024 · 7 comments
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automatic-stale question Further information is requested

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@renyuanzhe
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renyuanzhe commented May 8, 2024

FaceForensics, SkyTimelapse, UCF101, and Taichi-HD

@maxin-cn
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maxin-cn commented May 8, 2024

FaceForensics, SkyTimelapse, UCF101, and Taichi-HD

You can refer to #35. If it's still not clear, I'll give you a data structure.

@maxin-cn maxin-cn added the question Further information is requested label May 8, 2024
@renyuanzhe
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FaceForensics, SkyTimelapse, UCF101, and Taichi-HD

You can refer to #35. If it's still not clear, I'll give you a data structure.

should i write the preprocess code by myself, or is your repository contains the needed code?

@renyuanzhe
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and could you offer these datasets' structure in the project, I wonder if the structure is modified when preprocessing

@maxin-cn
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maxin-cn commented May 13, 2024

and could you offer these datasets' structure in the project, I wonder if the structure is modified when preprocessing

All datasets have this dataset structure following their original structure, and no additional operations are required.

ROOT:
├── train
    ├── video1.mp4
    ├── video2.mp4
├── test
    ├── video1.mp4
    ├── video2.mp4

or

ROOT:
├── train
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png
├── test
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png

@renyuanzhe
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and could you offer these datasets' structure in the project, I wonder if the structure is modified when preprocessing

All datasets have this dataset structure following their original structure, and no additional operations are required.

ROOT:
├── train
    ├── video1.mp4
    ├── video2.mp4
├── test
    ├── video1.mp4
    ├── video2.mp4

or

ROOT:
├── train
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png
├── test
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png

thankyou, I have preprocessed the dataset.however I find that the input img size is 32 inthe code,this is different with 256 in the paper. Is there something wrong?

@maxin-cn
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and could you offer these datasets' structure in the project, I wonder if the structure is modified when preprocessing

All datasets have this dataset structure following their original structure, and no additional operations are required.

ROOT:
├── train
    ├── video1.mp4
    ├── video2.mp4
├── test
    ├── video1.mp4
    ├── video2.mp4

or

ROOT:
├── train
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png
├── test
    ├── video1.mp4
        ├── frame_0001.png
        ├── frame_0002.png
    ├── video2.mp4
        ├── frame_0001.png
        ├── frame_0002.png

thankyou, I have preprocessed the dataset.however I find that the input img size is 32 inthe code,this is different with 256 in the paper. Is there something wrong?

The encoder will downsample video from 256 to 32.

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Hi There! 👋

This issue has been marked as stale due to inactivity for 60 days.

We would like to inquire if you still have the same problem or if it has been resolved.

If you need further assistance, please feel free to respond to this comment within the next 7 days. Otherwise, the issue will be automatically closed.

We appreciate your understanding and would like to express our gratitude for your contribution to Latte. Thank you for your support. 🙏

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