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Gello Dataset - LeRobot v2.1 Format (10Hz)
This dataset contains robotic manipulation demonstrations converted to the LeRobot v2.1 data format, matching the structure of the berkeley_autolab_ur5 dataset. This version captures data at 10Hz for efficient storage and processing.
Dataset Overview
- Task: Pick up the hard drives out of the grey bin and put them on the wooden board.
- Total Episodes: 50
- Total Frames: 6,586
- Total Videos: 100 (2 video types per episode)
- Format: LeRobot v2.1
- FPS: 10
- Video Resolution: 640x480
Directory Structure
gello_lerobot_v21_zed_10hz_test/
βββ data/
β βββ chunk-000/
β βββ episode_000000.parquet
β βββ episode_000001.parquet
β βββ ... (50 episodes total)
βββ meta/
β βββ episodes_stats.jsonl # Per-episode statistics
β βββ episodes.jsonl # Episode metadata
β βββ info.json # Dataset metadata
β βββ tasks.jsonl # Task descriptions
βββ videos/
βββ chunk-000/
βββ observation.images.hand_image/
β βββ episode_000000.mp4
β βββ ... (50 videos)
βββ observation.images.image/
βββ episode_000000.mp4
βββ ... (50 videos)
Data Fields
Observation Fields
observation.state: Robot joint positions and gripper state (7D float32)observation.images.hand_image: Wrist camera view (640x480x3 video)observation.images.image: Base camera view (640x480x3 video)
Action Fields
action: Robot actions (7D float32)
Metadata Fields
timestamp: Time step in seconds (float32)episode_index: Episode identifier (int64)frame_index: Frame index within episode (int64)next.reward: Reward signal (float32)next.done: Episode termination flag (bool)index: Global frame index (int64)task_index: Task identifier (int64)
Usage with LeRobot
This dataset is compatible with LeRobot v2.1 tools and can be loaded using:
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
# Load the dataset
dataset = LeRobotDataset("/path/to/gello_lerobot_v21_zed_10hz_test")
# Access episodes
for episode in dataset:
print(f"Episode {episode['episode_index']}: {episode['total_frames']} frames")
Video Format
- Codec: AV1
- Resolution: 640x480 pixels
- Channels: 3 (RGB)
- Pixel Format: YUV420p
- Frame Rate: 10 FPS
Task Description
All episodes in this dataset demonstrate the same task:
"Pick up the hard drives out of the grey bin and put them on the wooden board."
Dataset Statistics
- Average Episode Length: ~132 frames
- Average Episode Duration: ~13.2 seconds
File Formats
Parquet Files
Each episode is stored as a Parquet file containing all the data fields with proper data types.
JSONL Files
episodes_stats.jsonl: Detailed statistics for each episodeepisodes.jsonl: Episode metadata including task assignmentstasks.jsonl: Task definitions
JSON Files
info.json: Dataset metadata including feature specifications, splits, and paths
Conversion Notes
This dataset was converted from raw Gello pickle files using the gello_to_lerobot.py script. The conversion process:
- Loads raw demonstration data from pickle files
- Processes images (resize to 640x480, convert to videos)
- Creates LeRobot v2.1 directory structure
- Saves episodes as individual Parquet files
- Generates metadata files in the required format
- Captures data at 10Hz for efficient storage and processing
Compatibility
This dataset follows the same structure as the berkeley_autolab_ur5 dataset and is fully compatible with:
- LeRobot v2.1 data loading utilities
- HuggingFace datasets library
- Standard machine learning frameworks (PyTorch, TensorFlow)
License
This dataset is provided for research and educational purposes. Please refer to the original Gello dataset license for usage terms.
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