Learn Calibration (Learn Calibration Distortion Model) (G Dataflow)

Reference to the source image.

Reference to the image containing calibration information.

Set of reference points to use in learning a calibration. Create the reference points manually or use the Calibration Target to Points - Circular Dots node.

pixel coordinates

Coordinates of 3 reference points in the image, in pixels.

X

X-coordinate of the point.

Y

Y-coordinate of the point.

Real World Coordinates

Relative locations of the dots in the real world.

X

X-coordinate of the point.

Y

Y-coordinate of the point.

Unit

Unit of the Real World Coordinates.

Image Size

Size of the calibration template image.

X

Horizontal size of the image.

Y

Vertical size of the image.

Distortion model settings to use.

Distortion Model

Type of distortion model.

Name	Value	Description
None	-1	Do not learn a distortion model.
Polynomial	0	Learn a polynomial distortion model. Using multiple coefficients increases computation accuracy at the expense of speed.
Division	1	Learn a division distortion model. Use this distortion model when the image contains minimal distortion.

Polynomial Model Setup

Polynomial model configuration.

Radial Coefficient

Number of polynomial coefficients to use.

Tangential Coefficients

Correction for tangential distortion. Correct for tangential distortion when sensor misalignment occurs.

TRUE	Correct for tangential distortion.
FALSE	Do not use correction.

Default: TRUE

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

Boolean value that adds points and learns the distortion model.

Default: TRUE

Reference to the output image.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.