# Camera

```{currentmodule} embodichain.lab.sim.sensors
```

## Configuration

The {class}`CameraCfg` class defines the configuration for camera sensors. It inherits from {class}`~SensorCfg` and controls resolution, clipping planes, intrinsics, and active data modalities.

| Parameter | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `width` | `int` | `640` | Width of the captured image. |
| `height` | `int` | `480` | Height of the captured image. |
| `intrinsics` | `tuple` | `(600, 600, 320.0, 240.0)` | Camera intrinsics `(fx, fy, cx, cy)`. |
| `extrinsics` | `ExtrinsicsCfg` | `ExtrinsicsCfg()` | Pose configuration (see below). |
| `near` | `float` | `0.005` | Near clipping plane distance. |
| `far` | `float` | `100.0` | Far clipping plane distance. |
| `enable_color` | `bool` | `True` | Enable RGBA image capture. |
| `enable_depth` | `bool` | `False` | Enable depth map capture. |
| `enable_mask` | `bool` | `False` | Enable segmentation mask capture. |
| `enable_normal` | `bool` | `False` | Enable surface normal capture. |
| `enable_position` | `bool` | `False` | Enable 3D position map capture. |

## Camera Extrinsics

The `ExtrinsicsCfg` class defines the position and orientation of the camera.

| Parameter | Type | Default | Description |
| :--- | :--- | :--- | :--- |
| `parent` | `str` | `None` | Name of the link to attach to (e.g., `"ee_link"`). If `None`, camera is fixed in world. |
| `pos` | `list` | `[0.0, 0.0, 0.0]` | Position offset `[x, y, z]`. |
| `quat` | `list` | `[0.0, 0.0, 0.0, 1.0]` | Orientation quaternion `[x, y, z, w]`. |
| `eye` | `tuple` | `None` | (Optional) Camera eye position for look-at mode. |
| `target` | `tuple` | `None` | (Optional) Target position for look-at mode. |
| `up` | `tuple` | `None` | (Optional) Up vector for look-at mode. |

## Usage

You can create a camera sensor using `sim.add_sensor()` with a `CameraCfg` object.

### Code Example

```python
from embodichain.lab.sim.sensors import Camera, CameraCfg

# 1. Define Configuration
camera_cfg = CameraCfg(
    width=640,
    height=480,
    intrinsics=(600, 600, 320.0, 240.0),
    extrinsics=CameraCfg.ExtrinsicsCfg(
        parent="ee_link",        # Attach to robot end-effector
        pos=[0.09, 0.05, 0.04],  # Relative position
        quat=[0, 0, 0, 1],       # Relative rotation [x, y, z, w]
    ),
    enable_color=True,
    enable_depth=True,
)

# 2. Add Sensor to Simulation
camera: Camera = sim.add_sensor(sensor_cfg=camera_cfg)
```
## Observation Data
Retrieve sensor data using camera.get_data(). The data is returned as a dictionary of tensors on the specified device.

| Key | Data Type | Shape | Description |
| :--- | :--- | :--- | :--- |
| `color` | `torch.uint8` | `(B, H, W, 4)` | RGBA image data. |
| `depth` | `torch.float32` | `(B, H, W)` | Depth map in meters. |
| `mask` | `torch.int32` | `(B, H, W)` | Segmentation mask / Instance IDs. |
| `normal` | `torch.float32` | `(B, H, W, 3)` | Surface normal vectors. |
| `position` | `torch.float32` | `(B, H, W, 3)` | 3D Position map (OpenGL coords). |

*Note: `B` represents the number of environments (batch size).*