--- license: apache-2.0 task_categories: - text-to-video - image-to-video tags: - wantrack - trackwan - motion-conditioned - point-tracks - synthetic - fastvideo --- # WanTrack synth toy — 720p A 720p/24fps recreation of [`noctuashap/wantrack_synth_toy`](https://huggingface.co/datasets/noctuashap/wantrack_synth_toy): one **shared seed image** + 50 motion captions → 50 I2V clips, each varying only the motion. Used as the overfit set for the bidirectional TrackWan teacher recipe in [FastVideo](https://github.com/hao-ai-lab/FastVideo). ## How it was built 1. **Generation** — Wan2.1-I2V-14B-720P, conditioned on the single `synthetic_seed.png` + each line of `captions.txt`, 720×1280, 121 frames @ 24fps (`gen_synth_i2v_worker.py`). 2. **Tracks** — CoTracker3 on a 50×50 grid + SAM object segmentation (`extract_tracks.py --segment`). 3. **Preprocess (Stage 5)** — VAE latents + T5 text embeds + CLIP frame-0 + track points/visibility baked into parquet (`v1_preprocess --preprocess_task i2v_track`, `train_fps 24`). ## Layout | path | what | |---|---| | `videos/vid_000000..000049.mp4` | 50 generated clips, 720×1280 @ 24fps, 121 frames | | `tracks/*.npz` | CoTracker+SAM tracks (points, visibility, object_ids, weights) | | `videos2caption.json` | manifest: caption, fps, duration, resolution, `points_path` | | `preprocessed_i2v_track/combined_parquet_dataset/` | **training-ready** parquet (1 file, 50 rows) | | `synthetic_seed.png` | the shared 480p seed frame (I2V resizes to 720p) | | `captions.txt` | the 50 source motion captions | ## Parquet schema (per row, `pyarrow_schema_i2v_track`) `vae_latent`/`first_frame_latent` `[16, 31, 90, 160]` (float32) · `clip_feature` `[257, 1280]` · `track_points` `[121, 2500, 2]` · `track_visibility` `[121, 2500]` · `object_ids`, `track_weights` · `text_embedding`. Point the trainer's `data_path` at `preprocessed_i2v_track/combined_parquet_dataset`. ## Notes - ~1 in 5 captions involve a **human hand** manipulating objects — carried over from the original toy set (a deliberate "external agent" motion category), not a generation artifact. - All clips share one seed frame, so appearance is fixed and only motion varies — ideal for overfitting/validating a point-track conditioning pathway.