Executes a Detect Features model on a single input image.
|Limits an area where features may be detected
|Identifier of a Detect Features model
|Cuts the image into more overlapping tiles, which improves results quality at the expense of extended execution time
|Returns heatmaps for all classes defined in the model
|Returns the heatmap for the first feature class
|Returns the heatmap for the second feature class or an empty image if the model does not define more than one class
|Returns the heatmap for the third feature class or an empty image if the model does not define more than two classes
|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:
|Not supported inImage pixel format in FisFilter_DL_DetectFeatures. Supported formats: 1xUInt8, 3xUInt8.
This filter is available on Basic Complexity Level.