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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-to-video |
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language: |
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- en |
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tags: |
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- text-to-video |
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- Video Generative Model Training |
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- Text-to-Video Diffusion Model Training |
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- prompts |
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pretty_name: OpenVid-1M-mapping |
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size_categories: |
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- 1M<n<10M |
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--- |
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# Summary |
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This is the extent dataset proposed in the paper "[**OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation**](https://arxiv.org/abs/2407.02371)". |
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OpenVid-1M is a high-quality text-to-video dataset designed for research institutions to enhance video quality, featuring high aesthetics, clarity, and resolution. It can be used for direct training or as a quality tuning complement to other video datasets. |
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**New Feature**: Video-ZIP mapping files now available for efficient video lookup (see [Dataset Structure](#dataset-structure) and [Extended Usage](#extended-usage)). |
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# Dataset Structure |
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``` |
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DATA_PATH |
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└── video_mappings (NEW!) |
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├── OpenVid_part0.csv |
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├── OpenVid_part1.csv |
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├── ... |
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└── OpenVid_part185.csv |
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├── README.md |
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└── ... |
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``` |
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# Key Updates |
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1. **Video-ZIP Mapping** |
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We provide 186 mapping files (`OpenVid_part*.csv`) containing: |
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```csv |
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zip_file,video,video_path |
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OpenVid_part0.zip,celebv_--Jiv5iYqT8_0.mp4,OpenVid_part1/celebv_--Jiv5iYqT8_0.mp4 |
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OpenVid_part0.zip,celebv_--Jiv5iYqT8_2.mp4,OpenVid_part1/celebv_--Jiv5iYqT8_2.mp4 |
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OpenVid_part0.zip,celebv_--QCZKgJt6o_0.mp4,OpenVid_part1/celebv_--QCZKgJt6o_0.mp4 |
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OpenVid_part0.zip,celebv_--oCWVOBuvA_0.mp4,OpenVid_part1/celebv_--oCWVOBuvA_0.mp4 |
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... |
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``` |
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- `zip_file`: Source ZIP archive name |
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- `video`: Video filename |
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- `video_path`: Relative path within the ZIP file |
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2. **Mapping Features** |
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- Enables direct video lookup without full ZIP extraction |
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- Contains cross-references between ZIP files and video paths |
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- Split into multiple files for parallel processing |
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# Extended Usage |
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## 1. Video Mapping Access |
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```python |
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import pandas as pd |
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# Load all mapping files |
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mappings = [pd.read_csv(f"video_mappings/OpenVid_part{i}.csv") |
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for i in range(186)] |
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full_mapping = pd.concat(mappings) |
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# Find ZIP location for specific video |
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video_name = "celebv_--Jiv5iYqT8_0.mp4" |
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result = full_mapping[full_mapping.video == video_name] |
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print(f"Video {video_name} is in {result.zip_file.values[0]} at path {result.video_path.values[0]}") |
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``` |
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## 2. Advanced ZIP Handling |
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### Extraction Specific Video from Zip_file |
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```bash |
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# Extract specific video from ZIP without full decompression |
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unzip OpenVid_part0.zip "OpenVid_part1/celebv_--Jiv5iYqT8_0.mp4" -d target_folder |
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# Unzip files (-j flattens directory structure) |
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``` |
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# Citation and Acknowledgments |
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This mapping dataset was developed to enhance **OpenVid-1M** accessibility. Special thanks to the original dataset contributors. |
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```bibtex |
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@article{nan2024openvid, |
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title={OpenVid-1M: A Large-Scale High-Quality Dataset for Text-to-video Generation}, |
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author={Nan, Kepan and Xie, Rui and Zhou, Penghao and Fan, Tiehan and Yang, Zhenheng and Chen, Zhijie and Li, Xiang and Yang, Jian and Tai, Ying}, |
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journal={arXiv preprint arXiv:2407.02371}, |
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year={2024} |
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} |
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``` |
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