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| 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).
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| 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.
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| To find the camera indices of the cameras plugged into your system, run the following script:
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| ```bash
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| lerobot-find-cameras opencv
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| ```
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| The output will look something like this if you have two cameras connected:
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| ```
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| Camera
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| Name: OpenCV Camera @ 0
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| Type: OpenCV
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| Id: 0
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| Backend api: AVFOUNDATION
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| Default stream profile:
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| Format: 16.0
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| Width: 1920
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| Height: 1080
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| Fps: 15.0
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|
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| (more cameras ...)
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| ```
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| > [!WARNING]
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| > 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.
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| Below are two examples, demonstrating how to work with the API.
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| - **Asynchronous frame capture** using an OpenCV-based camera
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| - **Color and depth capture** using an Intel RealSense camera
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| <hfoptions id="shell_restart">
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| <hfoption id="Open CV Camera">
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|
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| <!
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| ```python
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| from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
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| from lerobot.cameras.opencv.camera_opencv import OpenCVCamera
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| from lerobot.cameras.configs import ColorMode, Cv2Rotation
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| config = OpenCVCameraConfig(
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| index_or_path=0,
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| fps=15,
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| width=1920,
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| height=1080,
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| color_mode=ColorMode.RGB,
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| rotation=Cv2Rotation.NO_ROTATION
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| )
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| camera = OpenCVCamera(config)
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| camera.connect()
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| try:
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| for i in range(10):
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| frame = camera.async_read(timeout_ms=200)
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| print(f"Async frame {i} shape:", frame.shape)
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| finally:
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| camera.disconnect()
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| ```
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| <!
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| </hfoption>
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| <hfoption id="Intel Realsense Camera">
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|
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| <!
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| ```python
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| from lerobot.cameras.realsense.configuration_realsense import RealSenseCameraConfig
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| from lerobot.cameras.realsense.camera_realsense import RealSenseCamera
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| from lerobot.cameras.configs import ColorMode, Cv2Rotation
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| config = RealSenseCameraConfig(
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| serial_number_or_name="233522074606",
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| fps=15,
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| width=640,
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| height=480,
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| color_mode=ColorMode.RGB,
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| use_depth=True,
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| rotation=Cv2Rotation.NO_ROTATION
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| )
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| camera = RealSenseCamera(config)
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| camera.connect()
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| try:
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| color_frame = camera.read()
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| depth_map = camera.read_depth()
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| print("Color frame shape:", color_frame.shape)
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| print("Depth map shape:", depth_map.shape)
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| finally:
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| camera.disconnect()
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| ```
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| <!
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|
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| </hfoption>
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| </hfoptions>
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| <hfoptions id="use phone">
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| <hfoption id="Mac">
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| To use your iPhone as a camera on macOS, enable the Continuity Camera feature:
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| - Ensure your Mac is running macOS 13 or later, and your iPhone is on iOS 16 or later.
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| - Sign in both devices with the same Apple ID.
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| - Connect your devices with a USB cable or turn on Wi-Fi and Bluetooth for a wireless connection.
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| For more details, visit [Apple support](https://support.apple.com/en-gb/guide/mac-help/mchl77879b8a/mac).
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| Your iPhone should be detected automatically when running the camera setup script in the next section.
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| </hfoption>
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| <hfoption id="Linux">
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| If you want to use your phone as a camera on Linux, follow these steps to set up a virtual camera
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| 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:
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|
|
| <!
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| ```python
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| sudo apt install v4l2loopback-dkms v4l-utils
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| ```
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| <!
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|
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| 2. _Install [DroidCam](https://droidcam.app) on your phone_. This app is available for both iOS and Android.
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| 3. _Install [OBS Studio](https://obsproject.com)_. This software will help you manage the camera feed. Install it using [Flatpak](https://flatpak.org):
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|
|
| <!
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| ```python
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| flatpak install flathub com.obsproject.Studio
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| ```
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| <!
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| 4. _Install the DroidCam OBS plugin_. This plugin integrates DroidCam with OBS Studio. Install it with:
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|
| <!
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| ```python
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| flatpak install flathub com.obsproject.Studio.Plugin.DroidCam
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| ```
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| <!
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| 5. _Start OBS Studio_. Launch with:
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| <!
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| ```python
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| flatpak run com.obsproject.Studio
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| ```
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| <!
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| 6. _Add your phone as a source_. Follow the instructions [here](https://droidcam.app/obs/usage). Be sure to set the resolution to `640x480`.
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| 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.
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| 8. _Start virtual camera_. In OBS Studio, follow the instructions [here](https://obsproject.com/kb/virtual-camera-guide).
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| 9. _Verify the virtual camera setup_. Use `v4l2-ctl` to list the devices:
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|
|
| <!
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| ```python
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| v4l2-ctl
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| ```
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| <!
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| You should see an entry like:
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| ```
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| VirtualCam (platform:v4l2loopback-000):
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| /dev/video1
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| ```
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| 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
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|
|
| <!
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| ```python
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| v4l2-ctl -d /dev/video1
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| ```
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| <!
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|
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| You should see an entry like:
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|
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| ```
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| >>> Format Video Capture:
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| >>> Width/Height : 640/480
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| >>> Pixel Format : 'YUYV' (YUYV 4:2:2)
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| ```
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|
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| Troubleshooting: If the resolution is not correct you will have to delete the Virtual Camera port and try again as it cannot be changed.
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|
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| If everything is set up correctly, you can proceed with the rest of the tutorial.
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|
|
| </hfoption>
|
| </hfoptions>
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|