Transform a Camera
Use the transform model to apply transformations to input source images. The transformations are applied in the order they are written in the pipeline.
On the COMPONENTS subtab, navigate to the Create Component menu.
Enter a name for your camera, select the type camera, and select the transform model.
Fill in the attributes for your transform view:
{
"name": "<camera_name>",
"type": "camera",
"model": "transform",
"attributes" : {
"intrinsic_parameters": {
"width_px": <integer>,
"height_px": <integer>,
"fx": <float64>,
"fy": <float64>,
"ppx": <float64>,
"ppy": <float64>
},
"distortion_parameters": {
"rk1": <float64>,
"rk2": <float64>,
"rk3": <float64>,
"tp1": <float64>,
"tp2": <float64>
},
"debug": <boolean>,
"source" : "<camera_name>",
"pipeline": [
{ "type": "<transformation_type>", "attributes": { ... } },
...
]
}
}
The following attributes are available for transform views:
| Name | Inclusion | Description |
|---|---|---|
intrinsic_parameters | Optional | The intrinsic parameters of the camera used to do 2D <-> 3D projections:
|
distortion_parameters | Optional | Modified Brown-Conrady parameters used to correct for distortions caused by the shape of the camera lens:
|
debug | Optional | Enables the debug outputs from the camera if true. Defaults to false. |
source | Required | Specify the name of the camera to transform. |
pipeline | Required | Specify and array of transformation objects. |
The following are the available transformations:
The Identity transform does nothing to the image. You can use this transform to change the underlying camera source’s intrinsic parameters or stream type, for example.
{
"type": "identity"
}
Attributes:
- None
The Rotate transformation rotates the image by 180 degrees. This feature is useful for when the camera is installed upside down on your robot.
{
"type": "rotate",
"attributes": { }
}
Attributes:
- None
The Resize transform resizes the image to the specified height and width.
{
"type": "resize",
"attributes": {
"width_px": int,
"height_px": int
}
}
Attributes:
width_px: Specify the expected width for the aligned image.height_px: Specify the expected width for the aligned image.
The Depth-to-Pretty transform takes a depth image and turns it into a colorful image, with blue indicating distant points and red indicating nearby points. The actual depth information is lost in the transform.
{
"type": "depth_to_pretty",
"attributes": { }
}
Attributes:
- None.
Overlays the depth and the color 2D images. Useful to debug the alignment of the two images.
{
"type": "overlay",
"attributes": {
"intrinsic_parameters": {
"width_px": int,
"height_px": int,
"ppx": float,
"ppy": float,
"fx": float,
"fy": float,
}
}
}
Attributes:
intrinsic_parameters: The intrinsic parameters of the camera used to do 2D <-> 3D projections.width_px: The width of the image in pixels.height_px: The height of the image in pixels.ppx: The image center x point.ppy: The image center y point.fx: The image focal x.fy: The image focal y.
The Undistort transform undistorts the input image according to the intrinsics and distortion parameters specified within the camera parameters. Currently only supports a Brown-Conrady model of distortion (20 September 2022). For further information, please refer to the OpenCV docs.
{
"type": "undistort",
"attributes": {
"intrinsic_parameters": {
"width_px": int,
"height_px": int,
"ppx": float,
"ppy": float,
"fx": float,
"fy": float
},
"distortion_parameters": {
"rk1": float,
"rk2": float,
"rk3": float,
"tp1": float,
"tp2": float
}
}
}
Attributes:
intrinsic_parameters: The intrinsic parameters of the camera used to do 2D <-> 3D projections.width_px: The expected width of the aligned image in pixels.height_px: The expected height of the aligned image in pixels.ppx: The image center x point.ppy: The image center y point.fx: The image focal x.fy: The image focal y.
distortion_parameters: Modified Brown-Conrady parameters used to correct for distortions caused by the shape of the camera lens.rk1: The radial distortion x.rk2: The radial distortion y.rk3: The radial distortion z.tp1: The tangential distortion x.tp2: The tangential distortion y.
The Detections transform takes the input image and overlays the detections from a given detector configured within the Vision Service.
{
"type": "detections",
"attributes": {
"detector_name": string,
"confidence_threshold": float
}
}
Attributes:
detector_name: The name of the detector configured in the Vision Service.confidence_threshold: Specify to only display detections above the specified threshold (decimal between 0 and 1).
The Depth Edges transform creates a canny edge detector to detect edges on an input depth map.
{
"type": "depth_edges",
"attributes": {
"high_threshold_pct": float,
"low_threshold_pct": float,
"blur_radius_px": float
}
}
Attributes:
high_threshold_pct: The high threshold of ??? : between 0.0 - 1.0.low_threshold_pct: The low threshold of ??? : between 0.0 - 1.0.blur_radius_px: The blur radius used to smooth the image before applying the filter.
Depth Preprocessing applies some basic hole-filling and edge smoothing to a depth map.
{
"type": "depth_preprocess",
"attributes": { }
}
Attributes:
- None.
Classifications overlay text from the GetClassifications method of the Vision Service onto the image.
{
"type": "classifications",
"attributes": {
"classifier_name": string,
"confidence_threshold": float
}
}
Attributes:
classifier_name: The name of the classifier in the Vision Service.confidence_threshold: The threshold above which to display classifications.
Example
{
"name": "camera_name",
"type": "camera",
"model": "transform",
"attributes" : {
"source" : "physical_cam",
"pipeline": [
{ "type": "rotate", "attributes": { } },
{ "type": "resize", "attributes": {"width_px":200, "height_px" 100} }
]
}
}
View the camera stream
Once your camera is connected, go to the CONTROL tab, and click on the camera’s dropdown menu. Toggle “View Camera”. If everything is configured correctly, you will see the live video feed from your camera.
