--- pretty_name: RealDatasets --- # RealDatasets This repository contains the original robot demonstrations and three converted LeRobot v3 datasets. ## Layout ```text raw/ ├── 抓娃娃/ ├── 对折毛巾/ └── 放置绳子/ lerobot/ ├── pack_sloth/ ├── fold_cloth/ └── insert_rope/ ``` Each `lerobot//` directory is an independent LeRobot v3 dataset root. Because the datasets are stored below repository subdirectories, download the selected subdirectory and pass its local path as `root`. ```python from pathlib import Path from huggingface_hub import snapshot_download from lerobot.datasets import LeRobotDataset repo_root = Path( snapshot_download( repo_id="Zili2002/RealDatasets", repo_type="dataset", allow_patterns=["lerobot/pack_sloth/**"], ) ) dataset = LeRobotDataset( repo_id="Zili2002/RealDatasets", root=repo_root / "lerobot" / "pack_sloth", video_backend="pyav", ) ``` ## Converted data - Nominal timeline: 30 Hz - Video resolution: 848x480 - `camera_2`: `observation.images.wrist` - `camera_4`: `observation.images.front` - Original 1920x1080 frames are center-cropped to 1908x1080 and resized without changing the aspect ratio. The source recordings contain timing gaps. Converted datasets preserve every recorded image and expand each episode onto a strict 30 Hz timeline: - real source frame: original image and `*_valid=true` - missing slot: black image and `*_valid=false` - missing slot state/action: NaN with their validity masks set to false - `source.frame_index=-1` identifies an inserted slot Consumers must filter invalid state/action rows before normalization, model input, and loss computation. Multiplying NaN values by a zero mask is not sufficient. Each converted dataset also contains: ```text raw_video/record_NNN/ ├── camera_2_*.mp4 ├── camera_4_*.mp4 ├── frame_timestamps.json └── timeline_30hz.json ``` `timeline_30hz.json` records the source-to-target frame mapping and the complete image-validity mask. LeRobot normalization statistics are computed from valid source rows only. ## Features - `observation.images.wrist`: video `[480, 848, 3]` - `observation.images.front`: video `[480, 848, 3]` - `observation.state`: float32 `[8]` - `action`: float32 `[7]` - `source.timestamp`: nominal 30 Hz Unix timestamp - `source.timestamp_relative`: nominal 30 Hz episode-relative timestamp - `source.original_timestamp`: real source timestamp, NaN for inserted rows - `source.original_timestamp_relative`: real relative timestamp, NaN for inserted rows - `source.frame_index`: source frame index, `-1` for inserted rows - `observation.images.wrist_valid` - `observation.images.front_valid` - `observation.state_valid` - `action_valid`