// // 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 #import "TextDetectionModel.h" @class Net; NS_ASSUME_NONNULL_BEGIN // C++: class TextDetectionModel_DB /** * This class represents high-level API for text detection DL networks compatible with DB model. * * Related publications: CITE: liao2020real * Paper: https://arxiv.org/abs/1911.08947 * For more information about the hyper-parameters setting, please refer to https://github.com/MhLiao/DB * * Configurable parameters: * - (float) binaryThreshold - The threshold of the binary map. It is usually set to 0.3. * - (float) polygonThreshold - The threshold of text polygons. It is usually set to 0.5, 0.6, and 0.7. Default is 0.5f * - (double) unclipRatio - The unclip ratio of the detected text region, which determines the output size. It is usually set to 2.0. * - (int) maxCandidates - The max number of the output results. * * Member of `Dnn` */ CV_EXPORTS @interface TextDetectionModel_DB : TextDetectionModel #ifdef __cplusplus @property(readonly)cv::Ptr nativePtrTextDetectionModel_DB; #endif #ifdef __cplusplus - (instancetype)initWithNativePtr:(cv::Ptr)nativePtr; + (instancetype)fromNative:(cv::Ptr)nativePtr; #endif #pragma mark - Methods // // cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(Net network) // /** * Create text detection algorithm from deep learning network. * @param network Net object. */ - (instancetype)initWithNetwork:(Net*)network; // // cv::dnn::TextDetectionModel_DB::TextDetectionModel_DB(string model, string config = "") // /** * Create text detection 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 text detection 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; // // TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setBinaryThreshold(float binaryThreshold) // - (TextDetectionModel_DB*)setBinaryThreshold:(float)binaryThreshold NS_SWIFT_NAME(setBinaryThreshold(binaryThreshold:)); // // float cv::dnn::TextDetectionModel_DB::getBinaryThreshold() // - (float)getBinaryThreshold NS_SWIFT_NAME(getBinaryThreshold()); // // TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setPolygonThreshold(float polygonThreshold) // - (TextDetectionModel_DB*)setPolygonThreshold:(float)polygonThreshold NS_SWIFT_NAME(setPolygonThreshold(polygonThreshold:)); // // float cv::dnn::TextDetectionModel_DB::getPolygonThreshold() // - (float)getPolygonThreshold NS_SWIFT_NAME(getPolygonThreshold()); // // TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setUnclipRatio(double unclipRatio) // - (TextDetectionModel_DB*)setUnclipRatio:(double)unclipRatio NS_SWIFT_NAME(setUnclipRatio(unclipRatio:)); // // double cv::dnn::TextDetectionModel_DB::getUnclipRatio() // - (double)getUnclipRatio NS_SWIFT_NAME(getUnclipRatio()); // // TextDetectionModel_DB cv::dnn::TextDetectionModel_DB::setMaxCandidates(int maxCandidates) // - (TextDetectionModel_DB*)setMaxCandidates:(int)maxCandidates NS_SWIFT_NAME(setMaxCandidates(maxCandidates:)); // // int cv::dnn::TextDetectionModel_DB::getMaxCandidates() // - (int)getMaxCandidates NS_SWIFT_NAME(getMaxCandidates()); @end NS_ASSUME_NONNULL_END