Installation

pip install lerobot

lerobot-info

pip install lerobot

pip install lerobot[all]

# Clone the repository
git clone https://github.com/huggingface/lerobot.git
cd lerobot

# Install in editable mode with development tools
pip install -e .[dev]

# Set up pre-commit hooks
pre-commit install

import lerobot
print(lerobot.__version__)

import lerobot
from pprint import pprint

# Available environments
print("Environments:", lerobot.available_envs)

# Available policies
print("Policies:", lerobot.available_policies)

# Available robots
print("Robots:", lerobot.available_robots)

# Available cameras
print("Cameras:", lerobot.available_cameras)

# Available motors
print("Motors:", lerobot.available_motors)

# Available datasets
print(f"Total datasets: {len(lerobot.available_datasets)}")

import torch

print(f"PyTorch version: {torch.__version__}")
print(f"CUDA available: {torch.cuda.is_available()}")
if torch.cuda.is_available():
    print(f"CUDA version: {torch.version.cuda}")
    print(f"GPU: {torch.cuda.get_device_name(0)}")

print(f"MPS (Apple Silicon) available: {torch.backends.mps.is_available()}")

# System information
lerobot-info

# Hardware utilities
lerobot-find-cameras      # Detect connected cameras
lerobot-find-port         # Find robot serial ports
lerobot-calibrate         # Calibrate robot motors
lerobot-setup-motors      # Configure motor settings
lerobot-find-joint-limits # Determine robot joint limits
lerobot-setup-can         # Configure CAN bus for certain motors

# Data collection
lerobot-teleoperate       # Teleoperate robot
lerobot-record            # Record robot demonstrations
lerobot-replay            # Replay recorded episodes

# Training and evaluation
lerobot-train             # Train a policy
lerobot-eval              # Evaluate a policy

# Dataset tools
lerobot-dataset-viz       # Visualize datasets
lerobot-edit-dataset      # Edit dataset episodes
lerobot-imgtransform-viz  # Visualize image transformations

# Advanced
lerobot-train-tokenizer   # Train custom tokenizers

# Check CUDA version compatibility
nvidia-smi

# Install specific PyTorch version for your CUDA
# Visit: https://pytorch.org/get-started/locally/
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118

# Install the specific extra you need
pip install lerobot[<extra_name>]

# Create a fresh virtual environment
python -m venv lerobot_env
source lerobot_env/bin/activate  # On Windows: lerobot_env\Scripts\activate
pip install lerobot

import torch

# Use MPS device on Apple Silicon
device = torch.device("mps") if torch.backends.mps.is_available() else torch.device("cpu")
print(f"Using device: {device}")

# Install system dependencies
sudo apt-get install librealsense2-dkms librealsense2-utils

# Then install Python package
pip install lerobot[intelrealsense]

# Create conda environment
conda create -n lerobot python=3.12
conda activate lerobot

# Install PyTorch (adjust for your system)
conda install pytorch torchvision pytorch-cuda=11.8 -c pytorch -c nvidia

# Install LeRobot
pip install lerobot