Executes a Detect Features model on a single input image.
|inRoi||Region*||Limits an area where features may be detected|
|inModelId||DetectFeaturesModelId||Identifier of a Detect Features model|
|inOverlap||Bool||Cuts the image into more overlapping tiles, which improves results quality at the expense of extended execution time|
|outHeatmaps||HeatmapArray||Returns heatmaps for all classes defined in the model|
|outFeature1||Heatmap||Returns the heatmap for the first feature class|
|outFeature2||Heatmap||Returns the heatmap for the second feature class or an empty image if the model does not define more than one class|
|outFeature3||Heatmap||Returns the heatmap for the third feature class or an empty image if the model does not define more than two classes|
|outFeature4||Heatmap||Returns the heatmap for the fourth feature class or an empty image if the model does not define more than three classes|
For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.
Read more about pixel formats in Image documentation.
- It is recommended that the deep learning model is deployed with DL_DetectFeatures_Deploy first and connected through the inModelId input.
- If one decides not to use 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.
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.
This filter can throw an exception to report error. Read how to deal with errors in Error Handling.
List of possible exceptions:
|DomainError||Not supported inImage pixel format in AvsFilter_DL_DetectFeatures. Supported formats: 1xUInt8, 3xUInt8.|
This filter is available on Basic Complexity Level.
Disabled in Lite Edition
Models for Deep Learning may be created using Aurora Vision Deep Learning Editor.