108 lines
3.7 KiB
Objective-C
108 lines
3.7 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/xfeatures2d.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 "Feature2D.h"
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// C++: enum TeblidSize (cv.xfeatures2d.TEBLID.TeblidSize)
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typedef NS_ENUM(int, TeblidSize) {
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TEBLID_SIZE_256_BITS NS_SWIFT_NAME(SIZE_256_BITS) = 102,
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TEBLID_SIZE_512_BITS NS_SWIFT_NAME(SIZE_512_BITS) = 103
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};
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NS_ASSUME_NONNULL_BEGIN
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// C++: class TEBLID
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/**
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* Class implementing TEBLID (Triplet-based Efficient Binary Local Image Descriptor),
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* described in CITE: Suarez2021TEBLID.
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*
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* TEBLID stands for Triplet-based Efficient Binary Local Image Descriptor, although originally it was called BAD
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* \cite Suarez2021TEBLID. It is an improvement over BEBLID \cite Suarez2020BEBLID, that uses triplet loss,
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* hard negative mining, and anchor swap to improve the image matching results.
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* It is able to describe keypoints from any detector just by changing the scale_factor parameter.
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* TEBLID is as efficient as ORB, BEBLID or BRISK, but the triplet-based training objective selected more
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* discriminative features that explain the accuracy gain. It is also more compact than BEBLID,
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* when running the [AKAZE example](https://github.com/opencv/opencv/blob/4.x/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
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* with 10000 keypoints detected by ORB, BEBLID obtains 561 inliers (75%) with 512 bits, whereas
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* TEBLID obtains 621 (75.2%) with 256 bits. ORB obtains only 493 inliers (63%).
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*
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* If you find this code useful, please add a reference to the following paper:
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* <BLOCKQUOTE> Iago Suárez, José M. Buenaposada, and Luis Baumela.
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* Revisiting Binary Local Image Description for Resource Limited Devices.
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* IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8317-8324, Oct. 2021. </BLOCKQUOTE>
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*
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* The descriptor was trained in Liberty split of the UBC datasets \cite winder2007learning .
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*
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* Member of `Xfeatures2d`
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*/
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CV_EXPORTS @interface TEBLID : Feature2D
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::xfeatures2d::TEBLID> nativePtrTEBLID;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::xfeatures2d::TEBLID>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::xfeatures2d::TEBLID>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// static Ptr_TEBLID cv::xfeatures2d::TEBLID::create(float scale_factor, int n_bits = TEBLID::SIZE_256_BITS)
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//
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/**
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* Creates the TEBLID descriptor.
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* @param scale_factor Adjust the sampling window around detected keypoints:
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* - <b> 1.00f </b> should be the scale for ORB keypoints
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* - <b> 6.75f </b> should be the scale for SIFT detected keypoints
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* - <b> 6.25f </b> is default and fits for KAZE, SURF detected keypoints
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* - <b> 5.00f </b> should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints
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* @param n_bits Determine the number of bits in the descriptor. Should be either
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* TEBLID::SIZE_256_BITS or TEBLID::SIZE_512_BITS.
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*/
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+ (TEBLID*)create:(float)scale_factor n_bits:(int)n_bits NS_SWIFT_NAME(create(scale_factor:n_bits:));
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/**
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* Creates the TEBLID descriptor.
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* @param scale_factor Adjust the sampling window around detected keypoints:
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* - <b> 1.00f </b> should be the scale for ORB keypoints
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* - <b> 6.75f </b> should be the scale for SIFT detected keypoints
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* - <b> 6.25f </b> is default and fits for KAZE, SURF detected keypoints
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* - <b> 5.00f </b> should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints
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* TEBLID::SIZE_256_BITS or TEBLID::SIZE_512_BITS.
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*/
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+ (TEBLID*)create:(float)scale_factor NS_SWIFT_NAME(create(scale_factor:));
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//
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// String cv::xfeatures2d::TEBLID::getDefaultName()
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//
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- (NSString*)getDefaultName NS_SWIFT_NAME(getDefaultName());
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@end
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NS_ASSUME_NONNULL_END
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