# DL_SegmentInstances

Executes a Segment Instances model on a single input image.

### Syntax

void avl::DL_SegmentInstances
(
const avl::Image& inImage,
atl::Optional<const avl::Region&> inRoi,
const avl::SegmentInstancesModelDirectory& inModelDirectory,
const atl::Optional<float>& inMinDetectionScore,
const atl::Optional<int>& inMaxObjectsCount,
atl::Array<avl::Box>& outBoundingBoxes,
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 objects may be located
inModelDirectory const SegmentInstancesModelDirectory& A Segment Instances model stored in a specific disk directory
inMinDetectionScore const Optional<float>& 0.0 - 1.0 NIL Sets a minimum required score for an object to be returned. If not set, a value determined during the training is used
inMaxObjectsCount const Optional<int>& 1 - NIL Limits maximum number of returned objects. If not set, a value determined during the training is used
outBoundingBoxes Array<Box>& Returns bounding boxes of the found objects
outClassIds Array<int>& Returns ids of the found object classes
outClassNames Array<String>& Returns names of the found objects classes
outScores Array<float>& Returns scores of the found objects

### Requirements

For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.

### Hints

• It is recommended that the deep learning model is deployed with DL_SegmentInstances_Deploy first and connected through the inModelDirectory 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 filters only communicates with service and cannot be used for a parallel computation.

### Errors

List of possible exceptions:

Error type Description
DomainError Not supported inImage pixel format in DL_SegmentInstances.