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 FisFilter_DL_DetectFeatures. Supported formats: 1xUInt8, 3xUInt8.|
This filter is available on Basic Complexity Level.
Disabled in Lite Edition
This filter is disabled in Lite Edition. It is available only in full, FabImage Studio Professional version.
Models for Deep Learning may be created using FabImage Deep Learning Editor.
For more information, see Machine Vision Guide.