67 lines
2.4 KiB
Markdown
67 lines
2.4 KiB
Markdown
# How to build your own cameras
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### Define your own config for cameras (unitree_deploy/robot_devices/cameras/config.py)
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```python
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@CameraConfig.register_subclass("opencv") # Define and wrap your own cameras. Here use def __init__(self, config: OpenCVCameraConfig):
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@dataclass
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class OpenCVCameraConfig(CameraConfig):
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"""
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Example of tested options for Intel Real Sense D405:
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OpenCVCameraConfig(0, 30, 640, 480)
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OpenCVCameraConfig(0, 60, 640, 480)
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OpenCVCameraConfig(0, 90, 640, 480)
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OpenCVCameraConfig(0, 30, 1280, 720)
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"""
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# Define the required camera parameters
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camera_index: int
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fps: int | None = None
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width: int | None = None
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height: int | None = None
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color_mode: str = "rgb"
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channels: int | None = None
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rotation: int | None = None
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mock: bool = False
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def __post_init__(self):
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if self.color_mode not in ["rgb", "bgr"]:
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raise ValueError(
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f"`color_mode` is expected to be 'rgb' or 'bgr', but {self.color_mode} is provided."
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)
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self.channels = 3
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if self.rotation not in [-90, None, 90, 180]:
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raise ValueError(f"`rotation` must be in [-90, None, 90, 180] (got {self.rotation})")
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# Default parameters go first [parameters that need to be customized],
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# Non-default parameters go later [fixed parameters]
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```
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### Description of methods in your cameras class (unitree_deploy/robot_devices/cameras/utils.py)
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```python
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# Base class for cameras, extensible with required methods
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class Camera(Protocol):
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def connect(self): ...
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def read(self, temporary_color: str | None = None) -> np.ndarray: ... # Single-threaded reading
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def async_read(self) -> np.ndarray: ... # Multi-threaded
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def disconnect(self): ...
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```
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How can external modules implement calls? Use **make_cameras_from_configs [based on configuration files]** to construct the `UnitreeRobot` class.
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**make_camera [based on camera_type]** is generally used for external module loading.
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### Implementation of the `camera` class (unitree_deploy/robot_devices/camera/.../....py)
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```python
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# These need to be completed, focusing on implementing these two parts
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def read(self, temporary_color: str | None = None) -> np.ndarray: ... # Single-threaded reading
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def async_read(self) -> np.ndarray: ... # Multi-threaded
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```
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All cameras use threading to implement `async_read` for internal read and write operations.
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