---
license: apache-2.0
task_categories:
- robotics
tags:
- LeRobot
- robotics
- tsfile
- timeseries
- format:tsfile
pretty_name: SAM Frames5 (TsFile)
size_categories:
- 10K<n<100K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/sam_frames5_train.tsfile
modality:
- tabular
- timeseries
---

# SAM Frames5 (TsFile)

This dataset is an Apache TsFile conversion of the Hugging Face dataset
[`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5).
The source was created with
[LeRobot](https://github.com/huggingface/lerobot) and contains `sam_double`
robot demonstrations for peeling the protective layer from adhesive tape.

Modalities: Time-series. The source repository also contains three synchronized
camera streams; videos are not included in this converted repository.

## Source Dataset

- Original dataset: [`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5)
- License: `apache-2.0`
- LeRobot codebase version: `v2.1`
- Robot type: `sam_double`
- Task: `Peel off the protective layer from the adhesive tape.`
- Split: `train` (`0:51`)
- Scale: `51` episodes, `32,369` frames, `1` task
- Sampling rate: `30` fps
- Source frame files: `51` Parquet files
- Source videos: `153` MP4 files across `3` camera streams
- Source data layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
- Source video layout: `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`

The camera streams are `observation.images.laptop`,
`observation.images.phone`, and `observation.images.side`. Each stream contains
51 videos at 30 fps. Source video frames are 480 x 640 RGB, encoded with AV1,
and contain no audio.

## Converted File

- TsFile: `data/sam_frames5_train.tsfile`
- TsFile table: `sam_frames5_train`
- Converted rows: `32,369`
- Episodes: `51`
- Time precision: milliseconds
- TAG columns: `episode_index`, `task_index`
- File size: `537,440` bytes
- SHA-256: `7415819c4cfe7786f3fe18ff489fe58e8c22abb1c7128c51ebc324c47c4bc788`

All train episodes are merged into one TsFile. The source `episode_index` and
`task_index` columns are retained as TAG columns, so queries can select an
episode without synthetic aliases.

## Schema

`Time` is computed as `Time = round(timestamp * 1000)` in milliseconds and
restarts in each episode. At 30 fps, consecutive frames are approximately
33.333 ms apart. The source `timestamp` column is not retained because it is
redundant with `Time / 1000` seconds. No source rows are dropped.

TAG columns:

- `episode_index`
- `task_index`

FIELD columns:

- `frame_index`
- `sample_index` (renamed from source `index`)
- `action_0` through `action_6` (FLOAT)
- `observation_state_0` through `observation_state_6` (FLOAT)

The seven vector elements use this source order for both `action` and
`observation.state`:

1. `main_shoulder_pan`
2. `main_shoulder_lift`
3. `main_elbow_flex`
4. `main_wrist_flex`
5. `main_wrist_side`
6. `main_wrist_roll`
7. `main_gripper`

Vector column names preserve the complete source feature name: `.` is replaced
with `_`, then the zero-based element index is appended.

## Video Policy

The three source video features are not converted or uploaded. Use the original
dataset for synchronized videos:
[`1g0rrr/sam_frames5/videos`](https://huggingface.co/datasets/1g0rrr/sam_frames5/tree/main/videos).

Each numeric row retains `episode_index`, `frame_index`, `task_index`, and
`sample_index`, preserving alignment with the original per-episode videos.

## Metadata

The source `meta/` files are mirrored in this repository. `meta/info.json` is
updated so `data_path` points to `data/sam_frames5_train.tsfile`. Its
`tsfile_conversion` object records the source and converted file counts, table
name, Time formula, TAG columns, row count, feature mappings, and frame/video
alignment. The converted `total_videos` is `0`; the source count of `153` is
preserved as `tsfile_conversion.source_video_count`.

## Validation

The converted file was compared with all 51 source Parquet files and read back
with the TsFile Python SDK:

- source and staged rows: `32,369`
- duplicate `(episode_index, task_index, Time)` rows: `0`
- maximum action-vector difference: `0`
- maximum observation-state-vector difference: `0`
- source `index` to converted `sample_index` mismatches: `0`

## Usage

```python
from tsfile import TsFileReader

path = "data/sam_frames5_train.tsfile"
with TsFileReader(path) as reader:
    schemas = reader.get_all_table_schemas()
    table = schemas["sam_frames5_train"]
    print([(column.get_column_name(), column.get_category())
           for column in table.get_columns()])
```

## Source & License

The source dataset is maintained at
[`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5) and
is distributed under the Apache License 2.0. The source card does not provide a
paper, author list, or citation entry.