| --- |
| license: mit |
| task_categories: |
| - robotics |
| tags: |
| - push-t |
| - diffusion-policy |
| - imitation-learning |
| - teleoperation |
| size_categories: |
| - n<1K |
| --- |
| |
| # Push-T: 200 Teleoperated Demonstrations |
|
|
| 200 demonstrations of the 2D Push-T task (push a T-shaped block onto a fixed target pose), collected by mouse teleoperation with `demo_pusht.py` from the [Diffusion Policy](https://github.com/real-stanford/diffusion_policy) codebase. Collected for a study of how Diffusion Policy performance scales with the number of demonstrations. |
|
|
| - Code and write-up: https://github.com/manhasv/pusht200 |
| - Trained checkpoints (50/100/150/200 demos): https://huggingface.co/manhasv/diffusion-policy-pusht200 |
|
|
| ## Contents |
|
|
| | | | |
| |---|---| |
| | Episodes | 200 (episode *i* starts from env seed *i*, seeds 0–199) | |
| | Total steps | 25,269 at 10 Hz | |
| | Episode length | 126 ± 46 steps (min 31, median 119, max 275) | |
| | Outcome | every episode ends in success: `demo_pusht.py` stops an episode automatically once the T covers > 95% of the target | |
| | Demonstrator | a single person, mouse teleoperation | |
|
|
| ## Format |
|
|
| A zarr `ReplayBuffer` (the format used throughout the Diffusion Policy repo). All episodes are concatenated along the first axis; `meta/episode_ends` gives the end index of each episode. |
|
|
| | Key | Shape | Type | Description | |
| |---|---|---|---| |
| | `data/action` | (T, 2) | float32 | target position of the agent, in pixels (0–512) | |
| | `data/state` | (T, 5) | float32 | `[agent_x, agent_y, block_x, block_y, block_angle]` | |
| | `data/keypoint` | (T, 9, 2) | float32 | 9 keypoints of the T block, in pixels | |
| | `data/img` | (T, 96, 96, 3) | uint8 | rendered RGB observation | |
| | `data/n_contacts` | (T, 1) | float32 | number of agent–block contacts | |
| | `meta/episode_ends` | (200,) | int64 | cumulative episode end indices | |
|
|
| ## Download |
|
|
| ```bash |
| hf download manhasv/pusht-200-data pusht_200.zarr.tar.gz --repo-type dataset --local-dir . |
| mkdir -p data && tar xzf pusht_200.zarr.tar.gz -C data/ # -> data/pusht_200.zarr |
| ``` |
|
|
| ## Notes |
|
|
| - This dataset is for demo purpose only. Compared with the original paper's Push-T demonstrations, this dataset have similar episode lengths but more idle frames (13% vs. 3%), jerkier motion, and ~27% longer agent paths. Policies trained on this data scored lower than the authors' results at similar dataset sizes. |
|
|
| ## License |
|
|
| MIT, following the upstream Diffusion Policy repository. |
