FisFilter_DL_DetectAnomalies2

Header:	FIL.h
Namespace:	fil
Module:	DL_DA

Executes a Detect Anomalies 2 model on a single input image.

Syntax

void fil::FisFilter_DL_DetectAnomalies2
(
	const fil::Image& inImage,
	const fil::DetectAnomalies2ModelId& inModelId,
	const float inScoreScale,
	fil::Heatmap& outHeatmap,
	bool& outIsValid,
	float& outScore,
	bool& outIsConfident,
	float& outT1,
	float& outT2,
	ftl::Conditional<fil::Region>& outRoi
)

Parameters

Name	Type	Range	Default	Description
inImage	const Image&			Input image
inModelId	const DetectAnomalies2ModelId&			Identifier of a Detect Anomalies 2 model
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
outT1	float&			Returns T1 'Good' threshold value
outT2	float&			Returns T2 'Bad' threshold value
outRoi	Conditional<Region>&			ROI used in training

Requirements

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

Read more about pixel formats in Image documentation.

Hints

It is recommended that the deep learning model is deployed with DL_DetectAnomalies2_Deploy first and connected through the inModelId input.
If one decides not to use DL_DetectAnomalies2_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.

Remarks

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 FisFilter_DL_DetectAnomalies2. Supported formats: 1xUInt8, 3xUInt8.