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--- |
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license: cc-by-nc-4.0 |
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task_categories: |
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- text-to-video |
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- text-to-image |
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size_categories: |
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- 1M<n<10M |
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tags: |
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- video-editing |
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- image-editing |
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language: |
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- en |
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--- |
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# VIVID-10M |
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[\[project page\]](https://klingteam.github.io/VIVID/) | [\[Paper\]](https://huggingface.co/papers/2411.15260) | [\[arXiv\]](https://arxiv.org/abs/2411.15260) |
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VIVID-10M is the first large-scale hybrid image-video local editing dataset aimed at reducing data construction and model training costs, comprising 9.7M samples that encompass a wide range of video editing tasks. |
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## Data Index |
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The data index is located at four `.csv` files: |
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``` bash |
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vivid-image-change.csv |
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vivid-image-remove.csv |
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vivid-video-change.csv |
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vivid-video-remove.csv |
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``` |
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VIVID-Video splits contains the columns: |
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``` bash |
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local_caption, # caption of masked object |
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source_video_path, # ground-truth video path |
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crop_video_path, # cropped video path (need to synthesize) |
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mask_path, # masked video path |
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editing_mode # change or remove |
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``` |
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VIVID-Image splits contains the columns: |
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``` bash |
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local_caption, # caption of masked object |
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source_image_path, # ground-truth image path |
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crop_image_path, # cropped image path (need to synthesize) |
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mask_path, # masked image path |
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editing_mode # change or remove |
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``` |
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## Get started |
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1. Download all files from this repository. |
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2. Merge split files. |
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```bash |
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cat vivid-video.tar.part-* > vivid-video.tar |
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cat vivid-image.tar.part-* > vivid-image.tar |
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``` |
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3. Expand the `.tar` file. |
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```bash |
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tar -xvf vivid-video.tar |
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tar -xvf vivid-image.tar |
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``` |
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4. (Optional) Synthesize cropped data. |
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``` bash |
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python get_crop_data.py |
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``` |
