DetectionModel

Objective-C

@interface DetectionModel : Model

Swift

class DetectionModel : Model

This class represents high-level API for object detection networks.

DetectionModel allows to set params for preprocessing input image. DetectionModel creates net from file with trained weights and config, sets preprocessing input, runs forward pass and return result detections. For DetectionModel SSD, Faster R-CNN, YOLO topologies are supported.

Member of Dnn

Methods


                    
                    
                    -initWithNetwork:

Create model from deep learning network.

Declaration

Objective-C

- (nonnull instancetype)initWithNetwork:(nonnull Net *)network;

Swift

init(network: Net)

Parameters


                                network

Net object.


                    
                    
                    -initWithModel:config:

Create detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.

Declaration

Objective-C

- (nonnull instancetype)initWithModel:(nonnull NSString *)model
                               config:(nonnull NSString *)config;

Swift

init(model: String, config: String)

Parameters

`model`	Binary file contains trained weights.
`config`	Text file contains network configuration.


                    
                    
                    -initWithModel:

Create detection model from network represented in one of the supported formats. An order of @p model and @p config arguments does not matter.

Declaration

Objective-C

- (nonnull instancetype)initWithModel:(nonnull NSString *)model;

Swift

init(model: String)

Parameters


                                model

Binary file contains trained weights.


                    
                    
                    -detect:classIds:confidences:boxes:confThreshold:nmsThreshold:

Given the @p input frame, create input blob, run net and return result detections.

Declaration

Objective-C

- (void)detect:(nonnull Mat *)frame
         classIds:(nonnull IntVector *)classIds
      confidences:(nonnull FloatVector *)confidences
            boxes:(nonnull NSMutableArray<Rect2i *> *)boxes
    confThreshold:(float)confThreshold
     nmsThreshold:(float)nmsThreshold;

Swift

func detect(frame: Mat, classIds: IntVector, confidences: FloatVector, boxes: NSMutableArray, confThreshold: Float, nmsThreshold: Float)

Parameters

`classIds`	Class indexes in result detection.
`confidences`	A set of corresponding confidences.
`boxes`	A set of bounding boxes.
`confThreshold`	A threshold used to filter boxes by confidences.
`nmsThreshold`	A threshold used in non maximum suppression.


                    
                    
                    -detect:classIds:confidences:boxes:confThreshold:

Given the @p input frame, create input blob, run net and return result detections.

Declaration

Objective-C

- (void)detect:(nonnull Mat *)frame
         classIds:(nonnull IntVector *)classIds
      confidences:(nonnull FloatVector *)confidences
            boxes:(nonnull NSMutableArray<Rect2i *> *)boxes
    confThreshold:(float)confThreshold;

Swift

func detect(frame: Mat, classIds: IntVector, confidences: FloatVector, boxes: NSMutableArray, confThreshold: Float)

Parameters

`classIds`	Class indexes in result detection.
`confidences`	A set of corresponding confidences.
`boxes`	A set of bounding boxes.
`confThreshold`	A threshold used to filter boxes by confidences.


                    
                    
                    -detect:classIds:confidences:boxes:

Given the @p input frame, create input blob, run net and return result detections.

Declaration

Objective-C

- (void)detect:(nonnull Mat *)frame
       classIds:(nonnull IntVector *)classIds
    confidences:(nonnull FloatVector *)confidences
          boxes:(nonnull NSMutableArray<Rect2i *> *)boxes;

Swift

func detect(frame: Mat, classIds: IntVector, confidences: FloatVector, boxes: NSMutableArray)

Parameters

`classIds`	Class indexes in result detection.
`confidences`	A set of corresponding confidences.
`boxes`	A set of bounding boxes.