lerobot/docs/source/cameras.mdx

# Cameras

LeRobot offers multiple options for video capture:

| Class             | Supported Cameras                   |
| ----------------- | ----------------------------------- |
| `OpenCVCamera`    | Phone, built-in laptop, USB webcams |
| `ZMQCamera`       | Network-connected cameras           |
| `RealSenseCamera` | Intel RealSense (with depth)        |
| `Reachy2Camera`   | Reachy 2 robot cameras              |

> [!TIP]
> For `OpenCVCamera` compatibility details, see the [Video I/O with OpenCV Overview](https://docs.opencv.org/4.x/d0/da7/videoio_overview.html).

### Find your camera

Every camera requires a unique identifier to be instantiated, allowing you to distinguish between multiple connected devices.

`OpenCVCamera` and `RealSenseCamera` support auto-discovery. Run the command below to list available devices and their identifiers. Note that these identifiers may change after rebooting your computer or re-plugging the camera, depending on your operating system.

```bash
lerobot-find-cameras opencv # or realsense for Intel Realsense cameras
```

The output will look something like this if you have two cameras connected:

```bash
--- 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.

`ZMQCamera` and `Reachy2Camera` do not support auto-discovery. They must be configured manually by providing their network address and port or robot SDK settings.

## Use cameras

### Frame access modes

All camera classes implement three access modes for capturing frames:

| Method                    | Behavior                                                                                                                                                   | Blocks?        | Best For                                 |
| ------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------- | ---------------------------------------- |
| `read()`                  | Waits for the camera hardware to return a frame. May block for a long time depending on the camera and SDK.                                                | Yes            | Simple scripts, sequential capture       |
| `async_read(timeout_ms)`  | Returns the latest unconsumed frame from background thread. Blocks only if buffer is empty, up to `timeout_ms`. Raises `TimeoutError` if no frame arrives. | With a timeout | Control loops synchronized to camera FPS |
| `read_latest(max_age_ms)` | Peeks at the most recent frame in buffer (may be stale). Raises `TimeoutError` if frame is older than `max_age_ms`.                                        | No             | UI visualization, logging, monitoring    |

### Usage examples

The following examples show how to use the camera API to configure and capture frames from different camera types.

- **Blocking and non-blocking frame capture** using an OpenCV-based camera
- **Color and depth capture** using an Intel RealSense camera

> [!WARNING]
> Failing to cleanly disconnect cameras can cause resource leaks. Use the context manager protocol to ensure automatic cleanup:
>
> ```python
> with OpenCVCamera(config) as camera:
>     ...
> ```
>
> You can also call `connect()` and `disconnect()` manually, but always use a `finally` block for the latter.

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

<!-- prettier-ignore-start -->
```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).
with OpenCVCamera(config) as camera:

    # Read a frame synchronously — blocks until hardware delivers a new frame
    frame = camera.read()
    print(f"read() call returned frame with shape:", frame.shape)

    # Read a frame asynchronously with a timeout — returns the latest unconsumed frame or waits up to timeout_ms for a new one
    try:
        for i in range(10):
            frame = camera.async_read(timeout_ms=200)
            print(f"async_read call returned frame {i} with shape:", frame.shape)
    except TimeoutError as e:
        print(f"No frame received within timeout: {e}")

    # Instantly return a frame - returns the most recent frame captured by the camera
    try:
        initial_frame = camera.read_latest(max_age_ms=1000)
        for i in range(10):
            frame = camera.read_latest(max_age_ms=1000)
            print(f"read_latest call returned frame {i} with shape:", frame.shape)
            print(f"Was a new frame received by the camera? {not (initial_frame == frame).any()}")
    except TimeoutError as e:
        print(f"Frame too old: {e}")

```
<!-- prettier-ignore-end -->

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

<!-- prettier-ignore-start -->
```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()
```
<!-- prettier-ignore-end -->

</hfoption>
</hfoptions>

## Use your phone's camera

<hfoptions id="use phone">
<hfoption id="iPhone & macOS">

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).

</hfoption>
<hfoption id="OBS virtual camera">

If you want to use your phone as a camera using OBS, follow these steps to set up a virtual camera.

1. _(Linux only) Install `v4l2loopback-dkms` and `v4l-utils`_. These packages create virtual camera devices and verify their settings. Install with:

```bash
sudo apt install v4l2loopback-dkms v4l-utils
```

2. _Install the [DroidCam app](https://droidcam.app) on your phone_. This app is available for both iOS and Android.
3. _Download and install [OBS Studio](https://obsproject.com)_.
4. _Download and install the [DroidCam OBS plugin](https://droidcam.app/obs)_.
5. _Start OBS 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` to avoid the watermarks.
7. _Adjust resolution settings_. In OBS Studio, go to `File > Settings > Video` or `OBS > Preferences... > Video`. Change the `Base(Canvas) Resolution` and the `Output(Scaled) Resolution` to `640x480` by manually typing it.
8. _Start virtual camera_. In OBS Studio, follow the instructions [here](https://obsproject.com/kb/virtual-camera-guide).
9. _Verify the virtual camera setup and resolution_.
   - **Linux**: Use `v4l2-ctl` to list devices and check resolution:
     ```bash
     v4l2-ctl --list-devices  # find VirtualCam and note its /dev/videoX path
     v4l2-ctl -d /dev/videoX --get-fmt-video  # replace with your VirtualCam path
     ```
     You should see `VirtualCam` listed and resolution `640x480`.
   - **macOS**: Open Photo Booth or FaceTime and select "OBS Virtual Camera" as the input.
   - **Windows**: The native Camera app doesn't support virtual cameras. Use a video conferencing app (Zoom, Teams) or run `lerobot-find-cameras opencv` directly to verify.

<details>
<summary><strong>Troubleshooting</strong></summary>

> The virtual camera resolution is incorrect.

Delete the virtual camera source and recreate it. The resolution cannot be changed after creation.

> Error reading frame in background thread for OpenCVCamera(X): OpenCVCamera(X) frame width=640 or height=480 do not match configured width=1920 or height=1080.

This error is caused by OBS Virtual Camera advertising a `1920x1080` resolution despite rescaling. The only fix for now is to comment out the width and height check in `_postprocess_image()`.

</details>

</hfoption>
</hfoptions>

If everything is set up correctly, your phone will appear as a standard OpenCV camera and can be used with `OpenCVCamera`.