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| # <u>Data Preprocessing Pipeline</u> by *Helios* | |
| This repository describes the data preprocessing pipeline used in the [Helios](https://arxiv.org/abs/2603.04379) paper. And we prepare a toy training data [here](https://huggingface.co/BestWishYsh/HeliosBench-Weights/tree/main/demo_data). | |
| ## ⚙️ Requirements and Installation | |
| ### Environment | |
| ```bash | |
| # Activate conda environment | |
| conda activate helios | |
| ``` | |
| ## 🗝️ Usage | |
| ### Step 1 - Prepare Metadata and Organize Videos | |
| To train your own video generation model, create JSON files following this [format](./example/toy_data/toy_filter.json): | |
| ``` | |
| [ | |
| { | |
| "cut": [0, 81], | |
| "crop": [0, 832, 0, 480], | |
| "fps": 24.0, | |
| "num_frames": 81, | |
| "resolution": { | |
| "height": 480, | |
| "width": 832 | |
| }, | |
| "cap": [ | |
| "A stunning mid-afternoon ..." | |
| ], | |
| "path": "videos/2_240_ori81.mp4" | |
| }, | |
| { | |
| "cut": [0, 81], | |
| ... | |
| } | |
| ... | |
| ] | |
| ``` | |
| and arrange video files following this [structure](./example): | |
| ``` | |
| 📦 example/ | |
| ├── 📂 toy_data/ | |
| │ ├── 📂 videos | |
| │ │ ├── 2_240_ori81.mp4 | |
| │ │ ├── 239_120_ori129.mp4.mp4 | |
| │ │ └── ... | |
| │ └── 📄 toy_data_1.json | |
| │ | |
| ├── 📂 toy_data_2/ | |
| │ │ ├── A.mp4 | |
| │ │ ├── B.mp4 | |
| │ │ └── ... | |
| │ └── 📄 toy_data_2.json | |
| ... | |
| ``` | |
| ### Step 2 - Prepare Autoregressive Real Data | |
| These data can be used for training Stage-1, Stage-2, and Stage-3. | |
| ```bash | |
| # Remember to modify the input and output paths before running | |
| bash get_short-latents.py | |
| ``` | |
| ### Step 3 - Prepare Autoregressive ODE Data | |
| These data can only be used for training Stage-3. | |
| ```bash | |
| # Remember to modify the input and output paths before running | |
| bash get_ode-pairs.sh | |
| ``` | |
| ### (Optional) Step 4 - Prepare Text Data | |
| If you want to use the [Self-Forcing](https://github.com/guandeh17/Self-Forcing) training approach, prepare text embeddings: | |
| ```bash | |
| # Remember to modify the input and output paths before running | |
| bash get_text-embedding.sh | |
| ``` | |
| ## 🔒 Acknowledgement | |
| * This project wouldn't be possible without the following open-sourced repositories: [OpenSora Plan](https://github.com/PKU-YuanGroup/Open-Sora-Plan), [OpenSora](https://github.com/hpcaitech/Open-Sora), [Video-Dataset-Scripts](https://github.com/huggingface/video-dataset-scripts) |