DL_LocatePoints

Header:	AVLDL.h
Namespace:	avl
Module:	DeepLearning

Executes a Locate Points model on a single input image.

Syntax

void avl::DL_LocatePoints
(
	const avl::Image& inImage,
	atl::Optional<const avl::Region&> inRoi,
	const avl::LocatePointsModelId& inModelId,
	const float inMinDetectionScore,
	const atl::Optional<float>& inMinDistanceRatio,
	const bool inOverlap,
	atl::Array<avl::Location>& outLocations,
	atl::Array<int>& outClassIds,
	atl::Array<atl::String>& outClassNames,
	atl::Array<float>& outScores
)

Parameters

Name	Type	Range	Default	Description
inImage	const Image&			Input image
inRoi	Optional<const Region&>		NIL	Limits the area where points may be located
inModelId	const LocatePointsModelId&			Identifier of a Locate Points model
inMinDetectionScore	const float	0.0 - 1.0	0.5f	Sets a minimum required score for a point to be returned
inMinDistanceRatio	const Optional<float>&	0.01 - 1.0	NIL	Sets a minimum distance between the returned points defined as a portion of the Feature Size. If not set, a value determined during the training is used
inOverlap	const bool		True	Cuts the image into more overlapping tiles, which improves results quality at the expense of extended execution time
outLocations	Array<Location>&			Returns location of the found points
outClassIds	Array<int>&			Returns ids of the found point classes
outClassNames	Array<String>&			Returns names of the found point classes
outScores	Array<float>&			Returns scores of the found points

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_LocatePoints_Deploy first and connected through the inModelId input.
If one decides not to use DL_LocatePoints_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.
Use inOverlap=False to increase execution speed at a cost of lower precision of results.

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 DL_LocatePoints.