| ---
|
| license: apache-2.0
|
| authors:
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| - 356c
|
| task_categories:
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| - robotics
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| tags:
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| - tsfile
|
| - timeseries
|
| - tabular
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| modality:
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| - timeseries
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| - tabular
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| pretty_name: SO100 Nut Test 11 TsFile
|
| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: data/356c_so100_nut_test_11.tsfile
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| size_categories:
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| - 10K<n<100K
|
| ---
|
|
|
| # SO100 Nut Test 11 TsFile
|
|
|
| This dataset is an Apache TsFile conversion of
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| [`356c/so100_nut_test_11`](https://huggingface.co/datasets/356c/so100_nut_test_11), a LeRobot v2.1 SO100
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| robot-manipulation dataset for picking up a nut and dropping it in a cup.
|
|
|
| ## Source Dataset and Attribution
|
|
|
| - Original dataset: [`356c/so100_nut_test_11`](https://huggingface.co/datasets/356c/so100_nut_test_11)
|
| - Original author, repository owner, uploader, and sole contributor:
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| [356c](https://huggingface.co/356c)
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| - License: Apache-2.0
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| - Task: "Pick up nut and drop in cup."
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| - Robot: `so100`; LeRobot version: `v2.1`
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| - Split: `train`; sampling rate: 30 fps
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| - Scale: 100 episodes, 38,691 frames, 1 task
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| - Source shards: 100 Parquet files totaling 2,190,148 bytes
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| - Source layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
|
| - The source card provides no paper, external homepage, or completed citation.
|
|
|
| ## TsFile Data
|
|
|
| - Path: `data/356c_so100_nut_test_11.tsfile`
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| - Table: `356c_so100_nut_test_11`
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| - Rows: 38,691; episodes/devices: 100; tasks: 1
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| - Time precision: milliseconds
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| - TsFile/source-Parquet size ratio: 0.330
|
|
|
| ## Schema and Mapping
|
|
|
| `Time = round(timestamp * 1000)` milliseconds. Time starts at zero and is
|
| strictly increasing in every episode. The source `timestamp` is omitted after
|
| conversion because it is recoverable as `Time / 1000` seconds.
|
|
|
| | TsFile column | Role | Type | Source mapping |
|
| |---|---|---|---|
|
| | `Time` | TIME | TIMESTAMP | `round(timestamp * 1000)` ms |
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| | `episode_index` | TAG | STRING | Original INT64 episode index |
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| | `task_index` | TAG | STRING | Original INT64 task index |
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| | `frame_index` | FIELD | INT64 | Preserved |
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| | `sample_index` | FIELD | INT64 | Renamed from `index` |
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| | `action_0` ... `action_5` | FIELD | FLOAT | Flattened from `action[6]` |
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| | `observation_state_0` ... `observation_state_5` | FIELD | FLOAT | Flattened from `observation.state[6]` |
|
|
|
| The six vector dimensions are `main_shoulder_pan`, `main_shoulder_lift`,
|
| `main_elbow_flex`, `main_wrist_flex`, `main_wrist_roll`, and `main_gripper`.
|
| Dots in source names are replaced by underscores. No numeric row, episode,
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| task, action dimension, or state dimension is dropped.
|
|
|
| ## Encodings and Compression
|
|
|
| - FLOAT/DOUBLE: GORILLA + LZ4
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| - INT32/INT64: TS_2DIFF + LZ4
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| - Time: TS_2DIFF + LZ4
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| - BOOLEAN: RLE + LZ4 (the source has no BOOLEAN field)
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| - TAG: TsFile table/device TAG storage
|
|
|
| ## Videos
|
|
|
| Videos are not included in this TsFile dataset. The 300 original AV1 MP4 files
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| remain in the source repository, 640x480 at 30 fps with no audio, in three
|
| streams with 100 episode files each:
|
|
|
| - [`observation.images.body`](https://huggingface.co/datasets/356c/so100_nut_test_11/tree/main/videos/chunk-000/observation.images.body)
|
| - [`observation.images.overhead`](https://huggingface.co/datasets/356c/so100_nut_test_11/tree/main/videos/chunk-000/observation.images.overhead)
|
| - [`observation.images.side`](https://huggingface.co/datasets/356c/so100_nut_test_11/tree/main/videos/chunk-000/observation.images.side)
|
|
|
| The source layout is
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| `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`.
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| Use `episode_index` and `frame_index` to align numeric rows with video frames.
|
|
|
| ## Minimal Read Example
|
|
|
| ```python
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| from tsfile import TsFileReader
|
|
|
| reader = TsFileReader("data/356c_so100_nut_test_11.tsfile")
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| with reader.query_table(
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| "356c_so100_nut_test_11",
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| ["episode_index", "task_index", "frame_index", "sample_index",
|
| "action_0", "observation_state_0"],
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| batch_size=65536,
|
| ) as result:
|
| batch = result.read_arrow_batch()
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| print(batch.to_pandas().head())
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| reader.close()
|
| ```
|
|
|
| ## Citation
|
|
|
| The source card supplies no paper or completed citation. Cite the original
|
| Hugging Face dataset and its publisher, `356c`, when using this conversion.
|
|
|
