# Cameras LeRobot offers multiple options for video capture, including phone cameras, built-in laptop cameras, external webcams, and Intel RealSense cameras. To efficiently record frames from most cameras, you can use either the `OpenCVCamera` or `RealSenseCamera` class. For additional compatibility details on the `OpenCVCamera` class, refer to the [Video I/O with OpenCV Overview](https://docs.opencv.org/4.x/d0/da7/videoio_overview.html). ### Finding your camera To instantiate a camera, you need a camera identifier. This identifier might change if you reboot your computer or re-plug your camera, a behavior mostly dependant on your operating system. To find the camera indices of the cameras plugged into your system, run the following script: ```bash lerobot-find-cameras opencv # or realsense for Intel Realsense cameras ``` The output will look something like this if you have two cameras connected: ``` --- Detected Cameras --- Camera #0: Name: OpenCV Camera @ 0 Type: OpenCV Id: 0 Backend api: AVFOUNDATION Default stream profile: Format: 16.0 Width: 1920 Height: 1080 Fps: 15.0 -------------------- (more cameras ...) ``` > [!WARNING] > When using Intel RealSense cameras in `macOS`, you could get this [error](https://github.com/IntelRealSense/librealsense/issues/12307): `Error finding RealSense cameras: failed to set power state`, this can be solved by running the same command with `sudo` permissions. Note that using RealSense cameras in `macOS` is unstable. ## Use Cameras Below are two examples, demonstrating how to work with the API. - **Asynchronous frame capture** using an OpenCV-based camera - **Color and depth capture** using an Intel RealSense camera ```python from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig from lerobot.cameras.opencv.camera_opencv import OpenCVCamera from lerobot.cameras.configs import ColorMode, Cv2Rotation # Construct an `OpenCVCameraConfig` with your desired FPS, resolution, color mode, and rotation. config = OpenCVCameraConfig( index_or_path=0, fps=15, width=1920, height=1080, color_mode=ColorMode.RGB, rotation=Cv2Rotation.NO_ROTATION ) # Instantiate and connect an `OpenCVCamera`, performing a warm-up read (default). camera = OpenCVCamera(config) camera.connect() # Read frames asynchronously in a loop via `async_read(timeout_ms)` try: for i in range(10): frame = camera.async_read(timeout_ms=200) print(f"Async frame {i} shape:", frame.shape) finally: camera.disconnect() ``` ```python from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig from lerobot.cameras.realsense.camera_realsense import RealSenseCamera from lerobot.cameras.configs import ColorMode, Cv2Rotation # Create a `RealSenseCameraConfig` specifying your camera’s serial number and enabling depth. config = RealSenseCameraConfig( serial_number_or_name="233522074606", fps=15, width=640, height=480, color_mode=ColorMode.RGB, use_depth=True, rotation=Cv2Rotation.NO_ROTATION ) # Instantiate and connect a `RealSenseCamera` with warm-up read (default). camera = RealSenseCamera(config) camera.connect() # Capture a color frame via `read()` and a depth map via `read_depth()`. try: color_frame = camera.read() depth_map = camera.read_depth() print("Color frame shape:", color_frame.shape) print("Depth map shape:", depth_map.shape) finally: camera.disconnect() ``` ## Use your phone To use your iPhone as a camera on macOS, enable the Continuity Camera feature: - Ensure your Mac is running macOS 13 or later, and your iPhone is on iOS 16 or later. - Sign in both devices with the same Apple ID. - Connect your devices with a USB cable or turn on Wi-Fi and Bluetooth for a wireless connection. For more details, visit [Apple support](https://support.apple.com/en-gb/guide/mac-help/mchl77879b8a/mac). Your iPhone should be detected automatically when running the camera setup script in the next section. If you want to use your phone as a camera on Linux, follow these steps to set up a virtual camera 1. _Install `v4l2loopback-dkms` and `v4l-utils`_. Those packages are required to create virtual camera devices (`v4l2loopback`) and verify their settings with the `v4l2-ctl` utility from `v4l-utils`. Install them using: ```python sudo apt install v4l2loopback-dkms v4l-utils ``` 2. _Install [DroidCam](https://droidcam.app) on your phone_. This app is available for both iOS and Android. 3. _Install [OBS Studio](https://obsproject.com)_. This software will help you manage the camera feed. Install it using [Flatpak](https://flatpak.org): ```python flatpak install flathub com.obsproject.Studio ``` 4. _Install the DroidCam OBS plugin_. This plugin integrates DroidCam with OBS Studio. Install it with: ```python flatpak install flathub com.obsproject.Studio.Plugin.DroidCam ``` 5. _Start OBS Studio_. Launch with: ```python flatpak run com.obsproject.Studio ``` 6. _Add your phone as a source_. Follow the instructions [here](https://droidcam.app/obs/usage). Be sure to set the resolution to `640x480`. 7. _Adjust resolution settings_. In OBS Studio, go to `File > Settings > Video`. Change the `Base(Canvas) Resolution` and the `Output(Scaled) Resolution` to `640x480` by manually typing it in. 8. _Start virtual camera_. In OBS Studio, follow the instructions [here](https://obsproject.com/kb/virtual-camera-guide). 9. _Verify the virtual camera setup_. Use `v4l2-ctl` to list the devices: ```python v4l2-ctl --list-devices ``` You should see an entry like: ``` VirtualCam (platform:v4l2loopback-000): /dev/video1 ``` 10. _Check the camera resolution_. Use `v4l2-ctl` to ensure that the virtual camera output resolution is `640x480`. Change `/dev/video1` to the port of your virtual camera from the output of `v4l2-ctl --list-devices`. ```python v4l2-ctl -d /dev/video1 --get-fmt-video ``` You should see an entry like: ``` >>> Format Video Capture: >>> Width/Height : 640/480 >>> Pixel Format : 'YUYV' (YUYV 4:2:2) ``` Troubleshooting: If the resolution is not correct you will have to delete the Virtual Camera port and try again as it cannot be changed. If everything is set up correctly, you can proceed with the rest of the tutorial.