data-pipeline

# Domain: Data Pipeline > Recording and replaying robot data with dora-rs ## Overview Dora supports data pipelines for: - Recording sensor data for training - Replaying recorded sessions - LeRobot integration for imitation learning - Dataset management ## LeRobot Integration > **Note:** dora-lerobot is from a separate repository, not PyPI. Install from source: > ```bash > git clone https://github.com/dora-rs/dora-lerobot > cd dora-lerobot > pip install -e dora_lerobot > ``` ### Recording Data ```yaml nodes: # Camera - id: camera build: pip install opencv-video-capture path: opencv-video-capture inputs: tick: dora/timer/millis/33 outputs: - image # Robot arm - id: arm build: pip install dora-rustypot path: dora-rustypot inputs: command: teleop/command outputs: - state - feedback # LeRobot recorder (install from dora-lerobot repo first) - id: recorder path: dora-lerobot-recorder inputs: image: camera/image state: arm/state action: teleop/command env: DATASET_NAME: my_robot_dataset EPISODE_INDEX: "0" ``` ### Replaying Data ```yaml nodes: # LeRobot replay (install from dora-lerobot repo first) - id: replay path: dora-lerobot-replay inputs: tick: dora/timer/millis/33 outputs: - image - state - action env: DATASET_NAME: my_robot_dataset EPISODE_INDEX: "0" # Visualization - id: plot build: pip install dora-rerun path: dora-rerun inputs: image: replay/image ``` ## Data Collection Workflow ```bash # 1. Start recording session dora run record_dataflow.yml # 2. Perform teleoperation # 3. Press Ctrl+C to stop and save # 4. Repeat for multiple episodes EPISODE_INDEX=1 dora run record_dataflow.yml EPISODE_INDEX=2 dora run record_dataflow.yml # 5. Train policy python train_policy.py --dataset my_robot_dataset ``` ## Available Hub Nodes | Node | Install | Purpose | |------|---------|---------| | dora-lerobot-recorder | From [dora-lerobot](https://github.com/dora-rs/dora-lerobot) repo | Record data | | dora-lerobot-replay | From [dora-lerobot](https://github.com/dora-rs/dora-lerobot) repo | Replay data | | llama-factory-recorder | `pip install llama-factory-recorder` | Record for LLM/VLM training | | lerobot-dashboard | `pip install lerobot-dashboard` | Pygame recording interface | | dora-rdt-1b | `pip install dora-rdt-1b` | VLA policy inference | ## Training Pipeline ### 1. Collect Demonstrations ```bash # Run teleoperation dataflow dora run record_dataflow.yml # Mark episodes # Press 'n' for new episode, 'f' for failed ``` ### 2. Convert to LeRobot Format ```python # The recorder automatically saves in LeRobot format # Dataset saved to: ~/.lerobot/datasets/<dataset_name> ``` ### 3. Train Policy ```bash # Using LeRobot CLI python lerobot/train.py \ --dataset my_robot_dataset \ --policy diffusion \ --output_dir outputs/my_policy ``` ### 4. Deploy Policy ```yaml nodes: - id: camera path: opencv-video-capture inputs: tick: dora/timer/millis/33 outputs: - image - id: policy build: pip install dora-rdt-1b path: dora-rdt-1b inputs: image: camera/image outputs: - action - id: robot path: dora-piper inputs: joint_positions: policy/action ``` ## Related Skills - **hub-recording** - Detailed recording node documentation - **hub-robot** - Robot control nodes - **domain-robot** - Robot control patterns - **domain-vision** - Visual data processing - **hub-nodes** - All pre-built nodes