ROI Descriptor is the descriptor of the region of interest specifying the location of the sample in the image. The ROI must be one or more closed contours. If ROI Descriptor is empty or not connected, the entire image is considered to be the region.

Tip  For best performance, use only one rectangle or one rotated rectangle per sample.

	Global Rectangle contains the coordinates of the bounding rectangle.
	Contours are each of the individual shapes that define an ROI. ID refers to whether the contour is the external or internal edge of an ROI. Type is the shape type of the contour. Coordinates indicates the relative position of the contour.

Classifier Session is the reference to the classifier session on which this VI operates.

Image is a reference to the source image.

error in (no error) describes the error status before this VI or function runs. The default is no error. If an error occurred before this VI or function runs, the VI or function passes the error in value to error out. This VI or function runs normally only if no error occurred before this VI or function runs. If an error occurs while this VI or function runs, it runs normally and sets its own error status in error out. Use the Simple Error Handler or General Error Handler VIs to display the description of the error code. Use error in and error out to check errors and to specify execution order by wiring error out from one node to error in of the next node.

	status is TRUE (X) if an error occurred before this VI or function ran or FALSE (checkmark) to indicate a warning or that no error occurred before this VI or function ran. The default is FALSE.
	code is the error or warning code. If status is TRUE, code is a nonzero error code. If status is FALSE, code is 0 or a warning code.
	source describes the origin of the error or warning and is, in most cases, the name of the VI or function that produced the error or warning. The default is an empty string.

Class Results is an array with one element for every class in the classifier session.

	Class is one of the classes in Classifier Session.
	Distance is the distance from the closest sample in Class to the input sample when performing Nearest Neighbor and K-Nearest Neighbor classification. Distance is the distance between the input sample and the center of each class when performing Minimum Mean Distance classification.

Classifier Session (dup) is a reference to the session referenced by Classifier Session.

Image (dup) is a reference to the connected input Image.

Class is the class into which the classifier session categorizes the input sample.

error out contains error information. If error in indicates that an error occurred before this VI or function ran, error out contains the same error information. Otherwise, it describes the error status that this VI or function produces. Right-click the error out indicator on the front panel and select Explain Error from the shortcut menu for more information about the error.

	status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred.
	code is the error or warning code. If status is TRUE, code is a nonzero error code. If status is FALSE, code is 0 or a warning code.
	source describes the origin of the error or warning and is, in most cases, the name of the VI or function that produced the error or warning. The default is an empty string.

Scores returns estimations of how well the classifier session classified the input. The score can vary from 0 to 1000, where 1000 represents the best possible score.

	Classification Score indicates how much better the assigned class represents the input sample than other classes represent the input.
	Identification Score indicates the similarity of the input and the assigned class. Use Identification Score only when you cannot reach a decision about the class of a sample using Classification Score alone.