117 lines
3.1 KiB
Objective-C
117 lines
3.1 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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NS_ASSUME_NONNULL_BEGIN
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// C++: class ClassificationModel
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/**
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* This class represents high-level API for classification models.
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*
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* ClassificationModel allows to set params for preprocessing input image.
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* ClassificationModel creates net from file with trained weights and config,
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* sets preprocessing input, runs forward pass and return top-1 prediction.
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*
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* Member of `Dnn`
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*/
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CV_EXPORTS @interface ClassificationModel : Model
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::dnn::ClassificationModel> nativePtrClassificationModel;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::dnn::ClassificationModel>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::dnn::ClassificationModel>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// cv::dnn::ClassificationModel::ClassificationModel(String model, String config = "")
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//
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/**
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* Create classification 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 classification 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::ClassificationModel::ClassificationModel(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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// ClassificationModel cv::dnn::ClassificationModel::setEnableSoftmaxPostProcessing(bool enable)
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//
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/**
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* Set enable/disable softmax post processing option.
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*
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* If this option is true, softmax is applied after forward inference within the classify() function
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* to convert the confidences range to [0.0-1.0].
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* This function allows you to toggle this behavior.
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* Please turn true when not contain softmax layer in model.
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* @param enable Set enable softmax post processing within the classify() function.
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*/
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- (ClassificationModel*)setEnableSoftmaxPostProcessing:(BOOL)enable NS_SWIFT_NAME(setEnableSoftmaxPostProcessing(enable:));
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//
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// bool cv::dnn::ClassificationModel::getEnableSoftmaxPostProcessing()
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//
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/**
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* Get enable/disable softmax post processing option.
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*
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* This option defaults to false, softmax post processing is not applied within the classify() function.
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*/
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- (BOOL)getEnableSoftmaxPostProcessing NS_SWIFT_NAME(getEnableSoftmaxPostProcessing());
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//
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// void cv::dnn::ClassificationModel::classify(Mat frame, int& classId, float& conf)
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//
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- (void)classify:(Mat*)frame classId:(int*)classId conf:(float*)conf NS_SWIFT_NAME(classify(frame:classId:conf:));
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@end
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NS_ASSUME_NONNULL_END
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