Health/Assets/OpenCVForUnity/Plugins/iOS/opencv2.framework/Headers/SegmentationModel.h

95 lines
2.2 KiB
Objective-C

//
// This file is auto-generated. Please don't modify it!
//
#pragma once
#ifdef __cplusplus
//#import "opencv.hpp"
#import "opencv2/dnn.hpp"
#import "opencv2/dnn/dnn.hpp"
#else
#define CV_EXPORTS
#endif
#import <Foundation/Foundation.h>
#import "Model.h"
@class Mat;
@class Net;
NS_ASSUME_NONNULL_BEGIN
// C++: class SegmentationModel
/**
* This class represents high-level API for segmentation models
*
* SegmentationModel allows to set params for preprocessing input image.
* SegmentationModel creates net from file with trained weights and config,
* sets preprocessing input, runs forward pass and returns the class prediction for each pixel.
*
* Member of `Dnn`
*/
CV_EXPORTS @interface SegmentationModel : Model
#ifdef __cplusplus
@property(readonly)cv::Ptr<cv::dnn::SegmentationModel> nativePtrSegmentationModel;
#endif
#ifdef __cplusplus
- (instancetype)initWithNativePtr:(cv::Ptr<cv::dnn::SegmentationModel>)nativePtr;
+ (instancetype)fromNative:(cv::Ptr<cv::dnn::SegmentationModel>)nativePtr;
#endif
#pragma mark - Methods
//
// cv::dnn::SegmentationModel::SegmentationModel(String model, String config = "")
//
/**
* Create segmentation model from network represented in one of the supported formats.
* An order of @p model and @p config arguments does not matter.
* @param model Binary file contains trained weights.
* @param config Text file contains network configuration.
*/
- (instancetype)initWithModel:(NSString*)model config:(NSString*)config;
/**
* Create segmentation model from network represented in one of the supported formats.
* An order of @p model and @p config arguments does not matter.
* @param model Binary file contains trained weights.
*/
- (instancetype)initWithModel:(NSString*)model;
//
// cv::dnn::SegmentationModel::SegmentationModel(Net network)
//
/**
* Create model from deep learning network.
* @param network Net object.
*/
- (instancetype)initWithNetwork:(Net*)network;
//
// void cv::dnn::SegmentationModel::segment(Mat frame, Mat& mask)
//
/**
* Given the @p input frame, create input blob, run net
* @param mask Allocated class prediction for each pixel
*/
- (void)segment:(Mat*)frame mask:(Mat*)mask NS_SWIFT_NAME(segment(frame:mask:));
@end
NS_ASSUME_NONNULL_END