DeepLearning_DetectAnomalies1

Header:	AVLDL.h
Namespace:	avl

Detects anomalies using trained deep-learning model.

Syntax

void avl::DeepLearning_DetectAnomalies1
(
	const avl::Image& inImage,
	const avl::DeepModel_AnomalyDetection1& inDeepModel,
	const bool inComputeReconstruction,
	avl::Image& outHeatmap,
	bool& outIsValid,
	float& outScore,
	bool& outIsConfident,
	atl::Optional<avl::Image&> outReconstructedImage = atl::NIL
)

Parameters

Name	Type	Default	Description
inImage	const Image&		Input image
inDeepModel	const DeepModel_AnomalyDetection1&		Trained model
inComputeReconstruction	const bool	True
outHeatmap	Image&		Image contains heatmaps for each input image channel
outIsValid	bool&		Returns true if anomaly was not found
outScore	float&		Score of classification
outIsConfident	bool&		Returns "false" if score is between T1 and T2
outReconstructedImage	Optional<Image&>	NIL	Returns network answer

Requirements

For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.

Read more about pixel formats in Image documentation.

Optional Outputs

The computation of following outputs can be switched off by passing value atl::NIL to these parameters: outReconstructedImage.

Hints

Loading Deep Learning Model may take longer timer. Consider using DeepLearning_LoadModel_AnomalyDetection1 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.
These filters only communicates with service and cannot be use for parallel computation.

Errors

List of possible exceptions:

Error type	Description
DomainError	Not supported inImage pixel format in DeepLearning_DetectAnomalies1.