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--- |
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license: mit |
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task_categories: |
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- robotics |
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tags: |
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- trajectory-prediction |
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- mouse-control |
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- computer-control |
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- quick-draw |
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- diffusion |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Quick, Draw! Circles - Trajectory Dataset |
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Dataset for training trajectory prediction models, specifically designed for the [Qwen-DiT-Draw](https://github.com/HusseinLezzaik/qwen-dit-draw) project. |
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## Dataset Description |
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This dataset contains chunked trajectory data from the [Quick, Draw!](https://quickdraw.withgoogle.com/data) circle category, formatted for training diffusion-based trajectory prediction models. |
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### Key Features |
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- **Variable-length trajectories** with stop signals (GR00T-style) |
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- **16-point chunks** with (x, y, state) format |
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- **Loss masking** for handling variable-length final chunks |
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- **512×512 canvas images** showing drawing progression |
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## Dataset Statistics |
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| Metric | Value | |
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|--------|-------| |
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| Total samples | 21207 | |
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| Source circles | 10000 | |
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| Chunk size | 16 points | |
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| Canvas size | 512×512 | |
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| Avg chunks/circle | 2.1 | |
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## Data Format |
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Each sample contains: |
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```python |
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{ |
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"image": Image, # 512×512 canvas (white for first chunk, partial drawing for rest) |
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"instruction": str, # "draw a circle" |
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"trajectory": [[x, y, state], ...], # 16 points, normalized [0, 1] |
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"mask": [1, 1, ..., 0, 0], # 1=real point, 0=ignore in loss |
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"is_last": bool, # True if final chunk of trajectory |
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"n_real_points": int, # Number of real points in this chunk (1-16) |
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"circle_idx": int, # Source circle index |
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"chunk_idx": int, # Chunk index within circle |
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} |
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``` |
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### State Signal |
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- `state = 0`: Continue drawing |
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- `state = 1`: Stroke complete (STOP) |
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The model learns WHERE to place the stop signal, not a fixed position. |
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### Loss Masking |
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For final chunks with fewer than 16 real points: |
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``` |
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mask = [1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0] |
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↑ real points (count in loss) ↑ ignored |
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``` |
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## Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("TESS-Computer/quickdraw-circles") |
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# Access a sample |
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sample = dataset["train"][0] |
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image = sample["image"] # PIL Image |
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trajectory = sample["trajectory"] # List of [x, y, state] |
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mask = sample["mask"] # Loss mask |
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``` |
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## Source |
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Data sourced from [Google Quick, Draw! Dataset](https://github.com/googlecreativelab/quickdraw-dataset) (circle category only). |
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## License |
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MIT License |
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## Citation |
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```bibtex |
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@misc{quickdraw-circles-trajectory, |
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title={Quick, Draw! Circles Trajectory Dataset}, |
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author={TESS Computer}, |
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year={2025}, |
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url={https://huggingface.co/datasets/TESS-Computer/quickdraw-circles} |
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} |
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``` |
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