---
title: wantrack-synth-toy-720p
canonical_url: "https://www.modelscope.cn/datasets/FastVideo/wantrack-synth-toy-720p"
md_url: "https://www.modelscope.cn/datasets/FastVideo/wantrack-synth-toy-720p.md"
repository: FastVideo/wantrack-synth-toy-720p
last_updated: 2026-08-06
license: apache-2.0
downloads: 188
stars: 0
---

# wantrack-synth-toy-720p

> wantrack-synth-toy-720p - FastVideo 在 ModelScope 开源的数据集。WanTrack synth toy — 720p

FastVideo/wantrack-synth-toy-720p 是 ModelScope 魔搭社区上的数据集，采用 apache-2.0 许可。

- **Repository**: FastVideo/wantrack-synth-toy-720p
- **License**: apache-2.0
- **Downloads**: 188
- **Stars**: 0
- **Last updated**: 2026-08-06

Source: https://www.modelscope.cn/datasets/FastVideo/wantrack-synth-toy-720p

---

# 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.