DL_ClassifyObject
Header: | AVLDL.h |
---|---|
Namespace: | avl |
Module: | DeepLearning |
Executes a Classify Object model on a single input image.
Syntax
void avl::DL_ClassifyObject ( const avl::Image& inImage, atl::Optional<const avl::Rectangle2D&> inRoi, atl::Optional<const avl::CoordinateSystem2D&> inRoiAlignment, const avl::ClassifyObjectModelId& inModelId, const bool inCreateHeatmap, atl::Array<avl::ClassConfidence>& outConfidences, atl::String& outClassName, int& outClassIndex, float& outScore, avl::Heatmap& outRelevanceHeatmap )
Parameters
Name | Type | Default | Description | |
---|---|---|---|---|
inImage | const Image& | Input image | ||
inRoi | Optional<const Rectangle2D&> | NIL | Limits the area where a classified object is located | |
inRoiAlignment | Optional<const CoordinateSystem2D&> | NIL | ||
inModelId | const ClassifyObjectModelId& | Identifier of a Classify Object model | ||
inCreateHeatmap | const bool | False | Enables creating a relevance heatmap at the expense of extended execution time | |
outConfidences | Array<ClassConfidence>& | Returns confidences for all classes | ||
outClassName | String& | Returns the name of the class with the highest confidence | ||
outClassIndex | int& | Returns the index of the class with the highest confidence | ||
outScore | float& | Returns the value of the highest confidence | ||
outRelevanceHeatmap | Heatmap& | Returns the heatmap indicating how strong specific parts of image influenced the classification result |
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_ClassifyObject_Deploy first and connected through the inModelId input.
- If one decides not to use DL_ClassifyObject_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 DL_ClassifyObject. |
See Also
Models for Deep Learning may be created using Adaptive Vision Deep Learning Editor or using Training Api.