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DeepLearning_ClassifyObject

Performs whole image classification using a trained deep-learning model.

Header:	AVL.h

Syntax

void avl::DeepLearning_ClassifyObject
(
	DeepLearningConnectionState& ioState,
	const avl::Image& inImage,
	const atl::Optional<avl::Region>& inRoi,
	const avl::DeepModel_Classification& inDeepModel,
	atl::Array<avl::ClassConfidence>& outConfidences,
	atl::String& outClassName,
	int& outClassIndex,
	float& outScore,
	avl::Image& diagRelevanceHeatmap
)

void DeepLearning_ClassifyObject
(
	ref DeepLearningConnectionState ioState,
	Image inImage,
	Region? inRoi,
	DeepModel_Classification inDeepModel,
	out ClassConfidence[] outConfidences,
	out System.String outClassName,
	out int outClassIndex,
	out float outScore,
	out Image diagRelevanceHeatmap
)

Parameters

Name	Type	Default	Description
ioState	DeepLearningConnectionState&		Object used to maintain state of the function.
inImage	const Image&		Input image
inRoi	const Optional<Region>&	NIL	Area of interest
inDeepModel	const DeepModel_Classification&		Trained model
outConfidences	Array<ClassConfidence>&		Returns confidences for all classes
outClassName	String&		Returns name of the class with highest confidence
outClassIndex	int&		Returns the index of the class with highest confidence
outScore	float&		Returns the value of the highest confidence
diagRelevanceHeatmap	Image&		Returns heatmap indicating how strong specific parts of image influenced classification result

Requirements

For input inImage only pixel formats are supported: 1xuint8, 3xuint8.

Read more about pixel formats in Image documentation.

Hints

Loading Deep Learning Model may take longer timer. Consider using DeepLearning_LoadModel for pre-loading model before execution starts.

Remarks

Model provided on inDeepModel input will be loaded to service automatically on first usage of Deep Learning filters.
Service automatically releases and loads model into its memory. It may result in releasing model previously loaded using DeepLearning_LoadModel filter.
These filters only communicates with service and cannot be use for parallel computation.

Errors

Error type	Description
DomainError	Empty ROI region in DeepLearning_ClassifyObject
DomainError	Size of ROI differs from size of image in DeepLearning_ClassifyObject
DomainError	Invalid DeepModel in DeepLearning_ClassifyObject.
DomainError	Empty image in DeepLearning_ClassifyObject.
IoError	Missing confidences.
IoError	Received invalid number of heatmaps.