| --- |
| pretty_name: StreamingWAM Real-World Dataset |
| language: |
| - zh |
| tags: |
| - robotics |
| - imitation-learning |
| - real-world |
| - streamingwam |
| - multi-view-video |
| size_categories: |
| - 10GB<n<100GB |
| --- |
| |
| # StreamingWAM Real-World Dataset |
|
|
| This repository contains the raw real-world robot trajectories used for the |
| StreamingWAM experiments. It contains 590 trajectories covering seven semantic |
| tasks. Static and dynamic apple-to-bowl conditions are sampled independently |
| with 50 trajectories each and stored as separate subsets, giving eight |
| top-level task-condition subsets. |
|
|
| ## Dataset summary |
|
|
| - **Trajectories:** 590 |
| - **Semantic tasks:** 7 |
| - **Task-condition subsets:** 8 |
| - **Control/video rate:** 15 Hz |
| - **Camera views:** 3 synchronized MP4 streams per trajectory |
| - **Videos:** 1,770 H.264 files |
| - **Action/state files:** one JSON and one HDF5 file per trajectory |
| - **Timestamp files:** one JSON file per trajectory |
| - **Payload size:** 18,688,099,319 bytes |
|
|
| | Directory | English description | Trajectories | |
| | --- | --- | ---: | |
| | `先称苹果，然后把它放进碗里（统一15Hz版）` | Weigh an apple, then place it in a bowl | 100 | |
| | `关上抽屉（统一15Hz版）` | Close a drawer | 80 | |
| | `打地鼠（统一15Hz版）` | Whack-a-mole | 30 | |
| | `打开抽屉（统一15Hz版）` | Open a drawer | 80 | |
| | `把苹果放进碗里_小车（统一15Hz版）` | Place an apple in a bowl with a moving cart | 100 | |
| | `把苹果放进碗里_静态（统一15Hz版）` | Place an apple in a bowl: static condition | 50 | |
| | `把苹果放进碗里_动态（统一15Hz版）` | Place an apple in a bowl: dynamic condition | 50 | |
| | `搭积木` | Stack blocks | 100 | |
|
|
| ## Record layout |
|
|
| Each trajectory contains one action JSON, one action HDF5, one frame-timestamp |
| JSON, and three synchronized camera MP4 files. The action data include robot |
| joint state, end-effector pose, gripper state, and timestamps. All streams are |
| aligned at 15 Hz. Most videos are 1920×1080; the moving-cart subset uses |
| 1280×720 video. |
|
|
| ## Selection and integrity |
|
|
| Static and dynamic apple-to-bowl records were sampled independently with 50 |
| trajectories each. Other subsets retain the original publication policy of at |
| most 100 trajectories. Sampling is without replacement after sorting record |
| names and uses seed 42. The exact selection is recorded in |
| `SELECTION_MANIFEST.json`. |
|
|
| `SHA256SUMS.tsv` contains the SHA-256 digest, byte size, and repository-relative |
| path of all 3,540 payload files. Every payload file was hashed after the |
| final static/dynamic split. `DATASET_BUILD.md` and each subset's |
| `SOURCE_README.md` document the preparation procedure. |
|
|
| ## Loading |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="rsj2003/StreamingWAM-RealWorld", |
| repo_type="dataset", |
| local_dir="StreamingWAM-RealWorld", |
| ) |
| ``` |
|
|
| This is a raw-data release. Use the 15 Hz timestamps when converting |
| trajectories to a training format, and do not apply a second 30 Hz-to-15 Hz |
| downsampling pass. |
|
|
| ## Privacy and license |
|
|
| The videos were recorded in a laboratory robot workcell. Before making this |
| private repository public, confirm the intended release scope, institutional |
| consent requirements, and any incidental human appearance in the full video |
| collection. No dataset license has been selected yet; external components and |
| benchmark assets retain their respective terms. |
|
|
