DeepLearning_ClassifyObject


Header:AVLDL.h
Namespace:avl

Performs whole image classification using a trained deep-learning model.

Syntax

void avl::DeepLearning_ClassifyObject
(
	const avl::Image& inImage,
	atl::Optional<const avl::Rectangle2D&> inRoi,
	atl::Optional<const avl::CoordinateSystem2D&> inRoiAlignment,
	const avl::DeepModel_Classification& inDeepModel,
	const bool inCreateRelevanceHeatmap,
	atl::Array<avl::ClassConfidence>& outConfidences,
	atl::String& outClassName,
	int& outClassIndex,
	float& outScore,
	avl::Image& outRelevanceHeatmap
)

Parameters

Name Type Default Description
inImage const Image& Input image
inRoi Optional<const Rectangle2D&> NIL Area of interest
inRoiAlignment Optional<const CoordinateSystem2D&> NIL
inDeepModel const DeepModel_Classification& Trained model
inCreateRelevanceHeatmap const bool False Enable-Disable create relevance heatmap
outConfidences Array<ClassConfidence>& Returns confidences for all classes
outClassName String& Returns name of the class with highest confidence
outClassIndex int& Returns the index of the class with highest confidence
outScore float& Returns the value of the highest confidence
outRelevanceHeatmap Image& Returns heatmap indicating how strong specific parts of image influenced classification result

Requirements

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

Read more about pixel formats in Image documentation.

Hints

Loading Deep Learning Model may take longer timer. Consider using DeepLearning_LoadModel_Classification 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.

See Also

  • Models for Deep Learning may be created using Adaptive Vision Deep Learning Editor or using Training Api.