AvsFilter_DL_DetectFeatures
Header: | AVL.h |
---|---|
Namespace: | avl |
Module: | DL_DF |
Executes a Detect Features model on a single input image.
Syntax
void avl::AvsFilter_DL_DetectFeatures ( const avl::Image& inImage, atl::Optional<const avl::Region&> inRoi, const avl::DetectFeaturesModelId& inModelId, const bool inOverlap, atl::Array<avl::Heatmap>& outHeatmaps, atl::Optional<avl::Heatmap&> outFeature1 = atl::NIL, atl::Optional<avl::Heatmap&> outFeature2 = atl::NIL, atl::Optional<avl::Heatmap&> outFeature3 = atl::NIL, atl::Optional<avl::Heatmap&> outFeature4 = atl::NIL )
Parameters
Name | Type | Default | Description | |
---|---|---|---|---|
inImage | const Image& | Input image | ||
inRoi | Optional<const Region&> | NIL | Limits an area where features may be detected | |
inModelId | const DetectFeaturesModelId& | Identifier of a Detect Features model | ||
inOverlap | const bool | True | Cuts the image into more overlapping tiles, which improves results quality at the expense of extended execution time | |
outHeatmaps | Array<Heatmap>& | Returns heatmaps for all classes defined in the model | ||
outFeature1 | Optional<Heatmap&> | NIL | Returns the heatmap for the first feature class | |
outFeature2 | Optional<Heatmap&> | NIL | Returns the heatmap for the second feature class or an empty image if the model does not define more than one class | |
outFeature3 | Optional<Heatmap&> | NIL | Returns the heatmap for the third feature class or an empty image if the model does not define more than two classes | |
outFeature4 | Optional<Heatmap&> | NIL | Returns the heatmap for the fourth feature class or an empty image if the model does not define more than three classes |
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.
Read more about Optional Outputs.
Hints
- It is recommended that the deep learning model is deployed with AvsFilter_DL_DetectFeatures_Deploy first and connected through the inModelId input.
- If one decides not to use AvsFilter_DL_DetectFeatures_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 AvsFilter_DL_DetectFeatures. Supported formats: 1xUInt8, 3xUInt8. |
See Also
Models for Deep Learning may be created using Aurora Vision Deep Learning Editor or using Training Api (C++ based API Training is available in 5.3 and older versions only).
For more information, see Machine Vision Guide.