AvsFilter_DL_DetectAnomalies1

Header:	AVL.h
Namespace:	avl
Module:	DL_DA

Executes a Detect Anomalies 1 model on a single input image.

Syntax

void avl::AvsFilter_DL_DetectAnomalies1
(
	const avl::Image& inImage,
	const avl::DetectAnomalies1ModelId& inModelId,
	const bool inReconstruct,
	const float inScoreScale,
	avl::Heatmap& outHeatmap,
	bool& outIsValid,
	float& outScore,
	bool& outIsConfident,
	float& outT1,
	float& outT2,
	atl::Optional<avl::Image&> outReconstructedImage = atl::NIL
)

Parameters

Name	Type	Range	Default	Description
inImage	const Image&			Input image
inModelId	const DetectAnomalies1ModelId&			Identifier of a Detect Anomalies 1 model
inReconstruct	const bool		True	Enables computing a reconstructed image, which may extend execution time
inScoreScale	const float	0.5 - 1.5	1.0f	Scale factor for T1 and T2 (default value results in usage of T1 and T2 from model)
outHeatmap	Heatmap&			Returns a heatmap indicating found anomalies
outIsValid	bool&			Returns true if no anomalies were found
outScore	float&			Returns score of the image
outIsConfident	bool&			Returns false if the score is between T1 and T2 (inclusive)
outT1	float&			Returns T1 'Good' threshold value
outT2	float&			Returns T2 'Bad' threshold value
outReconstructedImage	Optional<Image&>		NIL	Returns the reconstructed image

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

It is recommended that the deep learning model is deployed with AvsFilter_DL_DetectAnomalies1_Deploy first and connected through the inModelId input.
If one decides not to use AvsFilter_DL_DetectAnomalies1_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.

Remarks

This article concerns the functionalities related to another product: Deep Learning Add-on.

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.

Errors

List of possible exceptions:

Error type	Description
DomainError	Not supported inImage pixel format in AvsFilter_DL_DetectAnomalies1. Supported formats: 1xUInt8, 3xUInt8.