AvsFilter_DL_LocatePoints
Header: | AVL.h |
---|---|
Namespace: | avl |
Module: | DL_LP |
Executes a Locate Points model on a single input image.
Syntax
void avl::AvsFilter_DL_LocatePoints ( const avl::Image& inImage, atl::Optional<const avl::Region&> inRoi, const avl::LocatePointsModelId& inModelId, 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 )
Parameters
Name | Type | Range | Default | Description | |
---|---|---|---|---|---|
inImage | const Image& | Input image | |||
inRoi | Optional<const Region&> | NIL | Limits the area where points may be located | ||
inModelId | const LocatePointsModelId& | Identifier of a Locate Points model | |||
inMinDetectionScore | const float | 0.0 - 1.0 | 0.5f | Sets a minimum required score for a point to be returned | |
inMinDistanceRatio | const Optional<float>& | 0.01 - 1.0 | NIL | Sets a minimum distance between the returned points defined as a portion of the Feature Size. If not set, a value determined during the training is used | |
inOverlap | const bool | True | Cuts the image into more overlapping tiles, which improves results quality at the expense of extended execution time | ||
outLocations | Array<Location>& | Returns location of the found points | |||
outClassIds | Array<int>& | Returns ids of the found point classes | |||
outClassNames | Array<String>& | Returns names of the found point classes | |||
outScores | Array<float>& | Returns scores of the found points |
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 AvsFilter_DL_LocatePoints_Deploy first and connected through the inModelId input.
- If one decides not to use AvsFilter_DL_LocatePoints_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_LocatePoints. 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.