| --- |
| license: other |
| license_name: videvent-derived-research-only |
| license_link: https://arxiv.org/abs/2506.02448 |
| pretty_name: ShotPilot Stage 1 Training Cache |
| task_categories: |
| - text-to-video |
| language: |
| - en |
| tags: |
| - video-generation |
| - multi-shot |
| - shot-transition |
| - wan2.1 |
| - latents |
| size_categories: |
| - 1K<n<10K |
| viewer: false |
| --- |
| |
| # ShotPilot Stage 1 Training Cache |
|
|
| Precomputed training inputs for the ShotPilot Stage 1 causal multi-shot generator, built from the |
| [ShotPlan](https://huggingface.co/datasets/Pensioner/shotplan) training set: 6,404 clips, each 80 frames |
| (5 s at 16 fps) with one to three hard cuts. Videos were encoded at 480x832 with the |
| [Wan2.1-T2V-1.3B](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B) VAE and prompts with its UMT5-XXL text encoder. |
| No raw video is included. |
|
|
| ## Contents |
|
|
| | Folder | What it holds | Files | Size | |
| |---|---|---:|---:| |
| | `stage1_features_v0/` | Per-clip, per-shot VAE video latents | 6,414 | 26.7 GB | |
| | `stage1_memory_rgb6/` | Per-shot RGB memory: frames from earlier shots, VAE-encoded one at a time | 6,430 | 24.8 GB | |
| | `stage1_text_enriched_v2/` | UMT5-XXL encodings of the enriched global prompts | 6,409 | 12.0 GB | |
|
|
| Each folder has an `index.jsonl` (one line per clip, keyed by `metadata_row`) and a `manifest.json`. |
| Artifact paths in the index files are relative to the index file. Absolute paths inside manifests and |
| artifacts record where the cache was originally built and are not used for loading. |
|
|
| All tensors are `torch.bfloat16` `.pt` files (load with `torch.load(path, weights_only=True)`): |
|
|
| - **features** `rows/row_XXXXXX.pt`: `global_prompt`, `source_relative_path`, and `shots`, a list of |
| `{sample_id, shot_index_in_window, first_chunk_action, latent_frames, latent}` with |
| `latent` shaped `(16, T, 60, 104)`. Each shot was cropped to 4n+1 RGB frames before encoding. |
| - **memory** `shards/worker-XX/rows/row_XXXXXX.pt`: `memory_by_shot`, one entry per shot with |
| `latent` `(16, K, 60, 104)`, `shot_ids` and `rgb_indices` (K is at most 6; the first shot has none). |
| - **text** `rows/row_XXXXXX.pt`: `prompt` and `context` `(tokens, 4096)` (83–474 tokens). |
| `empty_context.pt` is the empty-prompt encoding used for text dropout and classifier-free guidance. |
|
|
| ## Usage |
|
|
| ```bash |
| hf download BlueSourceJY/shotpilot-stage1-data --repo-type dataset --local-dir data |
| ``` |
|
|
| This recreates `data/stage1_features_v0`, `data/stage1_memory_rgb6` and `data/stage1_text_enriched_v2`. |
| The ShotPilot loader checks SHA-256 digests of the index files and text rows, so keep the files byte-identical. |
| Train/validation/test splits are computed at load time from `source_relative_path` and a fixed seed. |
|
|
| ## License and provenance |
|
|
| These caches are derived from ShotPlan, which is derived from [VidEvent](http://www.videvent.top) |
| (Liang et al., 2025). They inherit those terms: **non-commercial research use only**. If you use them, |
| cite ShotPlan and VidEvent and comply with VidEvent's usage terms. |
|
|
| ```bibtex |
| @article{liang2025videvent, |
| title={VidEvent: A Large Dataset for Understanding Dynamic Evolution of Events in Videos}, |
| author={Liang, Baoyu and Su, Qile and Zhu, Shoutai and Liang, Yuchen and Tong, Chao}, |
| journal={arXiv preprint arXiv:2506.02448}, |
| year={2025} |
| } |
| ``` |
|
|
| ShotPlan: <https://github.com/Pensioner-11/ShotPlan> |
|
|
