| --- |
| license: apache-2.0 |
| authors: |
| - Henry-Ellis |
| task_categories: |
| - robotics |
| tags: |
| - tsfile |
| - timeseries |
| - tabular |
| - robotics |
| - lerobot |
| modality: |
| - timeseries |
| - tabular |
| pretty_name: G1 Dex3 Object Placement Dataset TsFile |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/g1_dex3_objectplacement_dataset_train.tsfile |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # G1 Dex3 Object Placement Dataset TsFile |
|
|
| Apache TsFile conversion of [unitreerobotics/G1_Dex3_ObjectPlacement_Dataset](https://huggingface.co/datasets/unitreerobotics/G1_Dex3_ObjectPlacement_Dataset), a LeRobot v3 robot-manipulation dataset. |
|
|
| ## Source and attribution |
|
|
| - Original dataset: https://huggingface.co/datasets/unitreerobotics/G1_Dex3_ObjectPlacement_Dataset |
| - Original uploader/data author shown in the Hugging Face repository history: Henry-Ellis (https://huggingface.co/Henry-Ellis) |
| - Repository owner/organization: unitreerobotics (Unitree Robotics) |
| - License: Apache-2.0; no paper or formal citation is supplied by the source card. |
| - Task: pick up toothpaste and a trash bag and place them into the blue storage container. |
| - Robot: 7-DOF dual-arm Unitree_G1 with three-fingered dexterous hands. |
| - Recording frequency: 30 Hz; source frame resolution 640x480. |
|
|
| ## Source layout and videos |
|
|
| The source train split is one Parquet shard (data/chunk-000/file-000.parquet) with 210 episodes, 98,266 frames, one task, and 30 fps. Source metadata paths: |
|
|
| - Numeric data: data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet |
| - Videos: videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4 |
| - Four camera streams: observation.images.cam_left_high, observation.images.cam_right_high, observation.images.cam_left_wrist, and observation.images.cam_right_wrist. They are listed in the original repository videos tree at https://huggingface.co/datasets/unitreerobotics/G1_Dex3_ObjectPlacement_Dataset/tree/main/videos. |
| - Current source revision contains 9 physical MP4 shards and 840 logical episode videos. |
|
|
| Videos are not included in this TsFile repository. They remain at the original Hugging Face videos paths; episode_index and frame_index preserve frame alignment. |
|
|
| ## Converted artifact |
|
|
| - TsFile: data/g1_dex3_objectplacement_dataset_train.tsfile |
| - Table: g1_dex3_objectplacement_dataset_train |
| - Rows: 98,266; episodes: 210; source split: train |
| - Time precision: milliseconds; Time = round(timestamp * 1000) and restarts from zero for each episode. |
| - Original timestamp is dropped because it is redundant with Time / 1000; source index is renamed to sample_index. |
| |
| ### Schema |
| |
| | Role | Columns | Source / notes | |
| |---|---|---| |
| | TIME | Time | INT64, milliseconds, TS_2DIFF + LZ4 | |
| | TAG | episode_index, task_index | Original source columns; TsFile stores TAG values as strings while source_dtype: int64 is recorded in meta/info.json | |
| | FIELD | frame_index, sample_index | INT64, TS_2DIFF + LZ4; sample_index comes from source index | |
| | FIELD | observation_state_0 ... observation_state_27 | Flattened source observation.state[28], FLOAT, GORILLA + LZ4 | |
| | FIELD | action_0 ... action_27 | Flattened source action[28], FLOAT, GORILLA + LZ4 | |
| |
| All source numeric rows and 28-dimensional state/action elements are retained. The only dropped source column is timestamp; video/image columns are intentionally omitted because videos remain in the original dataset. |
| |
| ## Conversion and validation |
| |
| The dataset-specific converter in conversion_support/scripts/converters/unitreerobotics_g1_dex3_objectplacement.py uses LeRobot normalization rules, sorts by episode_index, task_index, then Time, and writes one merged TsFile for the train split. Encodings/compression are explicit: FLOAT/DOUBLE GORILLA, INT32/INT64/Time TS_2DIFF, BOOLEAN RLE (no boolean field is present), and LZ4 compression. |
|
|
| Local validation passed: source/staged/TsFile row counts are all 98,266; 210 TAG devices are present; Time exactly matches round(timestamp * 1000); vector dimensions round-trip exactly; and the TsFile is non-empty and readable. See VALIDATION.md and validation_report.json. |
| |
| ## Minimal read example |
| |
| from tsfile import TsFileReader |
| path = "data/g1_dex3_objectplacement_dataset_train.tsfile" |
| reader = TsFileReader(path) |
| columns = ["episode_index", "task_index", "frame_index", "sample_index", "action_0", "observation_state_0"] |
| with reader.query_table("g1_dex3_objectplacement_dataset_train", columns, batch_size=65536) as result: |
| batch = result.read_arrow_batch() |
| print(batch.to_pandas().head()) |
| |
