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
.
Navigate to the Config tab of your robot’s page in the Viam app.
Click on the Components subtab and navigate to the Create component menu.
Enter a name for your camera, select the type camera
, and select the transform
model.
Click Create component.
Edit and fill in the attributes as applicable.
{
"name": "<your-camera-name>",
"type": "camera",
"model": "transform",
"attributes" : {
"intrinsic_parameters": {
"width_px": <int>,
"height_px": <int>,
"fx": <float>,
"fy": <float>,
"ppx": <float>,
"ppy": <float>
},
"distortion_parameters": {
"rk1": <float>,
"rk2": <float>,
"rk3": <float>,
"tp1": <float>,
"tp2": <float>
},
"debug": <boolean>,
"source" : "<your-camera-name>",
"pipeline": [
{ "type": "<transformation-type>", "attributes": { ... } },
...
]
}
}
The following attributes are available for transform
views:
Name | Type | Inclusion | Description |
---|---|---|---|
source | string | Required | name of the camera to transform. |
pipeline | array | Required | Specify an array of transformation objects. |
intrinsic_parameters | object | Optional | The intrinsic parameters of the camera used to do 2D <-> 3D projections:
|
distortion_parameters | object | Optional | Modified Brown-Conrady parameters used to correct for distortions caused by the shape of the camera lens:
|
debug | boolean | Optional | Enables the debug outputs from the camera if true .Default: false |
The following are the transformation objects available for the pipeline
:
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.
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 value: between 0.0 - 1.0.low_threshold_pct
: The low threshold value: 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.
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.
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 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
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 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 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 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.
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 configured and connected, go to the Control tab, and click on the camera’s dropdown menu. Then toggle the camera or the Point Cloud Data view to ON. If everything is configured correctly, you will see the live video feed from your camera. You can change the refresh frequency as needed to change bandwidth.
Next Steps
Have questions, or want to meet other people working on robots? Join our Community Discord.
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