Module: | DL_IS |
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Executes a Segment Instances model on a single input image.
Name | Type | Range | Description | |
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inImage | Image | Input image | ||
inRoi | Region* | Limits the area where objects may be located | ||
inModelId | SegmentInstancesModelId | Segment Instances model stored in a specific disk directory | ||
inMinDetectionScore | Real* | 0.0 - 1.0 | Sets a minimum required score for an object to be returned. If not set, a value determined during the training is used | |
inMaxObjectsCount | Integer* | 1 - | Limits maximum number of returned objects. If not set, a value determined during the training is used | |
outBoundingBoxes | BoxArray | Returns bounding boxes of the found objects | ||
outClassIds | IntegerArray | Returns ids of the found object classes | ||
outClassNames | StringArray | Returns names of the found objects classes | ||
outScores | RealArray | Returns scores of the found objects | ||
outMasks | RegionArray | Returns masks of the found objects |
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 DL_SegmentInstances_Deploy first and connected through the inModelId input.
- If one decides not to use DL_SegmentInstances_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.
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
This filter can throw an exception to report error. Read how to deal with errors in Error Handling.
List of possible exceptions:
Error type | Description |
---|---|
DomainError | Not supported inImage pixel format in AvsFilter_DL_SegmentInstances. Supported formats: 1xUInt8, 3xUInt8. |
Complexity Level
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, Aurora Vision Studio Professional version.
See Also
Models for Deep Learning may be created using Aurora Vision Deep Learning Editor.
For more information, see Machine Vision Guide.