Detects learned objects in the image.
This node provides a reference design to classify an image using the loaded model.
Rectangle region specifying the location of the sample in the image.
If ROI Descriptor is empty, the entire image is considered to be the region.
Coordinates of the bounding rectangle.
Individual shapes that define an ROI.
Object specifying if contour is the external or internal edge of an ROI.
Shape type of the contour.
Relative position of the contour.
Reference to the loaded model file.
Input for model graph Input Node Name.
Image will be converted to multi dimensional tensor based on loaded model.
Name of the Input data node in the loaded model graph.
Name of the Output data node in the loaded model graph.
This requires four node names.
String that specifies output node name for receiving number of detected objects using the loaded model. The corresponding node must output single dimensional tensor.
String to specify the output node name for receiving labels of detected objects. The corresponding node must output double dimensional tensor.
String to specify the output node name for receiving scores for the detected objects. The corresponding node must output double dimensional tensor.
String to specify the output node name for receiving bounding boxes (top, left, bottom, right) of detected objects. The corresponding node must output three dimensional tensor.
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.
Default: No error
Array of clusters containing Class ID and Label..
This is used for constructing detected objects.
Reference to the modified loaded model.
Reference to the source image.
Array of detected objects in the image.
Class label name.
This string is referenced based on Labels input. If Labels is not supplied, the class ID is converted to a string.
Probablity score for the classification result.
Score ranges are based on output of the loaded model. It typically varies between 0 and 1.
Array of points that define the boundary of the detected object.
Typically the model graph outputs unit bounding boxes. They are converted to image dimensions. You can connect this array directly to the Overlay Multiple Lines node to overlay the location of a match on your image.
Number of detected objects in the 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.
Where This Node Can Run:
Desktop OS: Windows
FPGA: Not supported
Web Server: Not supported in VIs that run in a web application