Scan Classifier

Scans a feature-map (input_feature_map) and do the classification for each scan-window. More...

Functions
vx_node	vxScanClassifierNode (vx_graph graph, vx_tensor input_feature_map, vx_classifier_model model, vx_int32 scanwindow_width, vx_int32 scanwindow_height, vx_int32 step_x, vx_int32 step_y, vx_array object_confidences, vx_array object_rectangles, vx_scalar num_objects)
	[Graph] Scans a feature-map (input_feature_map) and detect the classification for each scan-window. More...

Detailed Description

Scans a feature-map (input_feature_map) and do the classification for each scan-window.

This function scans a feature-map. Each window in the feature map is classified by a classification model. The classification models are loadable by undefined binary format see vxImportClassifierModel. Extensions will be added to the specification, to support a defined binary format. Classification models can be any machine learning classification method. Examples are Cascade, SVM, and Neural Networks.

Function Documentation

vxScanClassifierNode()

vx_node vxScanClassifierNode	(	vx_graph	graph,
		vx_tensor	input_feature_map,
		vx_classifier_model	model,
		vx_int32	scanwindow_width,
		vx_int32	scanwindow_height,
		vx_int32	step_x,
		vx_int32	step_y,
		vx_array	object_confidences,
		vx_array	object_rectangles,
		vx_scalar	num_objects
	)

[Graph] Scans a feature-map (input_feature_map) and detect the classification for each scan-window.

Parameters

[in]	graph	The reference to the graph
[in]	input_feature_map	The Feature-map, example is the output of vxHOGFeaturesNode.
[in]	model	The pre-trained model loaded. Loaded using vxImportClassifierModel
[in]	scan_window_width	Width of the scan window
[in]	scan_window_height	Height of the scan window
[in]	step_x	Horizontal step-size (along x-axis)
[in]	step_y	Vertical step-size (along y-axis)
[out]	object_confidences	[Optional] An array of confidences measure, the measure is of type VX_TYPE_UINT16. The confidence measure is defined by the extensions which define classification model with defined binary format. This output can be used as class index as well. In case we detect several different classes in single execution. The output will be an array of indexes of the classes.
[out]	object_rectangles	An array of object positions, in VX_TYPE_RECTANGLE
[out]	num_objects	[optional] The number of object detected in a VX_SIZE scalar

Note

The border mode VX_NODE_BORDER value VX_BORDER_UNDEFINED is supported.

Returns

vx_node.

Return values

vx_node

A node reference. Any possible errors preventing a successful creation should be checked using vxGetStatus