docs/source/cameras.mdx

# 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
python lerobot/find_cameras.py 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


<hfoptions id="shell_restart">
<hfoption id="Open CV Camera">

```python
from lerobot.common.cameras.opencv.configuration_opencv import OpenCVCameraConfig
from lerobot.common.cameras.opencv.camera_opencv import OpenCVCamera
from lerobot.common.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()
```

</hfoption>
<hfoption id="Intel Realsense Camera">

```python
from lerobot.common.cameras.realsense.configuration_realsense import RealSenseCameraConfig
from lerobot.common.cameras.realsense.camera_realsense import RealSenseCamera
from lerobot.common.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()
```
</hfoption>
</hfoptions>


## Use your phone
<hfoptions id="use phone">
<hfoption id="Mac">

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.

</hfoption>
<hfoption id="Linux">

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.

</hfoption>
</hfoptions>