DeepLearning_DetectFeatures

Header:	AVLDL.h
Namespace:	avl

Performs feature classification using trained deep-learning model.

Syntax

void avl::DeepLearning_DetectFeatures
(
	const avl::Image& inImage,
	atl::Optional<const avl::Region&> inRoi,
	const avl::DeepModel_FeatureDetection& inDeepModel,
	const bool inOverlap,
	atl::Array<avl::Image>& outHeatmaps,
	atl::Optional<avl::Image&> outFeature1 = atl::NIL,
	atl::Optional<avl::Image&> outFeature2 = atl::NIL,
	atl::Optional<avl::Image&> outFeature3 = atl::NIL,
	atl::Optional<avl::Image&> outFeature4 = atl::NIL
)

Parameters

Name	Type	Default	Description
inImage	const Image&		Input image
inRoi	Optional<const Region&>	NIL	Area of interest
inDeepModel	const DeepModel_FeatureDetection&		Trained model
inOverlap	const bool	True	Add tiles overlapping to improve results quality
outHeatmaps	Array<Image>&		Returns heatmaps for all classes
outFeature1	Optional<Image&>	NIL	Returns heatmap for first feature class
outFeature2	Optional<Image&>	NIL	Returns heatmap for second feature class or empty image if class is not specified
outFeature3	Optional<Image&>	NIL	Returns heatmap for third feature class or empty image if class is not specified
outFeature4	Optional<Image&>	NIL	Returns heatmap for fourth feature class or empty image if class is not specified

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: outFeature1, outFeature2, outFeature3, outFeature4.

Hints

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

Remarks

Model provided on inDeepModel input will be loaded automatically on first usage of this filter.
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. However, if stopping Deep Learning Service is not an option (e.g. program uses other Deep Learning filters) it is advised that this filter should be executed before other Deep Learning filters. Such "warm up" execution does not have to use real image or roi as long as provided image and roi have similar size.

Multithreaded environment

This function is not guaranteed to be thread-safe. When used in multithreaded environment, it has to be manually synchronized.

Errors

List of possible exceptions:

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