105 lines
2.5 KiB
Objective-C
105 lines
2.5 KiB
Objective-C
//
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// This file is auto-generated. Please don't modify it!
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//
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#pragma once
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#ifdef __cplusplus
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//#import "opencv.hpp"
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#import "opencv2/dnn.hpp"
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#import "opencv2/dnn/dnn.hpp"
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#else
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#define CV_EXPORTS
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#endif
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#import <Foundation/Foundation.h>
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#import "Model.h"
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@class Mat;
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@class Net;
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@class Point2f;
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NS_ASSUME_NONNULL_BEGIN
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// C++: class KeypointsModel
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/**
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* This class represents high-level API for keypoints models
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*
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* KeypointsModel allows to set params for preprocessing input image.
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* KeypointsModel creates net from file with trained weights and config,
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* sets preprocessing input, runs forward pass and returns the x and y coordinates of each detected keypoint
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*
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* Member of `Dnn`
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*/
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CV_EXPORTS @interface KeypointsModel : Model
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::dnn::KeypointsModel> nativePtrKeypointsModel;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::dnn::KeypointsModel>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::dnn::KeypointsModel>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// cv::dnn::KeypointsModel::KeypointsModel(String model, String config = "")
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//
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/**
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* Create keypoints model from network represented in one of the supported formats.
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* An order of @p model and @p config arguments does not matter.
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* @param model Binary file contains trained weights.
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* @param config Text file contains network configuration.
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*/
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- (instancetype)initWithModel:(NSString*)model config:(NSString*)config;
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/**
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* Create keypoints model from network represented in one of the supported formats.
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* An order of @p model and @p config arguments does not matter.
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* @param model Binary file contains trained weights.
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*/
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- (instancetype)initWithModel:(NSString*)model;
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//
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// cv::dnn::KeypointsModel::KeypointsModel(Net network)
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//
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/**
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* Create model from deep learning network.
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* @param network Net object.
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*/
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- (instancetype)initWithNetwork:(Net*)network;
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//
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// vector_Point2f cv::dnn::KeypointsModel::estimate(Mat frame, float thresh = 0.5)
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//
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/**
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* Given the @p input frame, create input blob, run net
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* @param thresh minimum confidence threshold to select a keypoint
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* @return a vector holding the x and y coordinates of each detected keypoint
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*
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*/
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- (NSArray<Point2f*>*)estimate:(Mat*)frame thresh:(float)thresh NS_SWIFT_NAME(estimate(frame:thresh:));
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/**
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* Given the @p input frame, create input blob, run net
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* @return a vector holding the x and y coordinates of each detected keypoint
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*
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*/
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- (NSArray<Point2f*>*)estimate:(Mat*)frame NS_SWIFT_NAME(estimate(frame:));
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@end
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NS_ASSUME_NONNULL_END
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