Performs points localization using a trained deep-learning model.


void avl::DeepLearning_LocatePoints
	const avl::Image& inImage,
	atl::Optional<const avl::Region&> inRoi,
	const avl::DeepModel_PointLocation& inDeepModel,
	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


Name Type Range Default Description
inImage const Image& Input image
inRoi Optional<const Region&> NIL Area of interest
inDeepModel const DeepModel_PointLocation& Trained model
inMinDetectionScore const float 0.0 - 1.0 0.5f Minimal score of found points
inMinDistanceRatio const Optional<float>& 0.01 - 1.0 NIL Minimal distance between found points defined as portion of Feature Size
inOverlap const bool True Add tiles overlapping to improve results quality
outLocations Array<Location>& Locations of found points
outClassIds Array<int>& Ids of found point classes
outClassNames Array<String>& Names of found point classes
outScores Array<float>& Scores of found points


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

Read more about pixel formats in Image documentation.


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


  • 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.