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AVLDL.DeepLearning_ClassifyObject Method

Namespace:AvlNet.DeepLearning
Assembly:AvlDl.Net.dll

Syntax

public static void DeepLearning_ClassifyObject
(
	AvlNet.Image inImage,
	AvlNet.Rectangle2D? inRoi,
	AvlNet.CoordinateSystem2D? inRoiAlignment,
	string inDeepModel,
	bool inCreateRelevanceHeatmap,
	IList<AvlNet.ClassConfidence> outConfidences,
	out string outClassName,
	out int outClassIndex,
	out float outScore,
	AvlNet.Image outRelevanceHeatmap
)

Parameters

Name Type Range Default Description
inImageAvlNet.ImageInput image
inRoiAvlNet.Rectangle2D?Area of interest
inRoiAlignmentAvlNet.CoordinateSystem2D?
inDeepModelstringTrained model
inCreateRelevanceHeatmapboolFalseEnable-Disable create relevance heatmap
outConfidencesSystem.Collections.Generic.IList<AvlNet.ClassConfidence>Returns confidences for all classes
outClassNamestringReturns name of the class with highest confidence
outClassIndexintReturns the index of the class with highest confidence
outScorefloatReturns the value of the highest confidence
outRelevanceHeatmapAvlNet.ImageReturns heatmap indicating how strong specific parts of image influenced classification result

Remarks

  • Model provided on inDeepModel input will be loaded automatically on first usage of this filter.
  • This filter should not be executed along with running Deep Learning Service as it may result in degraded performance or even out-of-memory errors. However, if stopping Deep Learning Service is not an option (e.g. program uses other Deep Learning filters related to Anomaly Detection or Instances Segmentation) it is advised that this filter should be executed before other Deep Learning filters. Such "warm up" execution does not have to use real image or roi as long as provided image and roi have similar size.

Errors

List of possible exceptions:

Error type Description
DomainError Not supported inImage pixel format in DeepLearning_ClassifyObject.

Function Overrides

See also