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Merge remote-tracking branch 'upstream/3.4' into merge-3.4
Revert "documentation: avoid links to 'master' branch from 3.4 maintenance branch" This reverts commit9ba9358ecb. Revert "documentation: avoid links to 'master' branch from 3.4 maintenance branch (2)" This reverts commitf185802489.
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@@ -11,67 +11,32 @@ In this tutorial you will learn how to:
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detection process
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- Use the function @ref cv::drawKeypoints to draw the detected keypoints
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\warning You need the <a href="https://github.com/opencv/opencv_contrib">OpenCV contrib modules</a> to be able to use the SURF features
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(alternatives are ORB, KAZE, ... features).
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Theory
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------
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Code
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----
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This tutorial code's is shown lines below.
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@code{.cpp}
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#include <stdio.h>
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#include <iostream>
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#include "opencv2/core.hpp"
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#include "opencv2/features2d.hpp"
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#include "opencv2/xfeatures2d.hpp"
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#include "opencv2/highgui.hpp"
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@add_toggle_cpp
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
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@include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp
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@end_toggle
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using namespace cv;
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using namespace cv::xfeatures2d;
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@add_toggle_java
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
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@include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
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@end_toggle
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void readme();
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/* @function main */
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int main( int argc, char** argv )
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{
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if( argc != 3 )
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{ readme(); return -1; }
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Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
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Mat img_2 = imread( argv[2], IMREAD_GRAYSCALE );
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if( !img_1.data || !img_2.data )
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{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }
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//-- Step 1: Detect the keypoints using SURF Detector
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int minHessian = 400;
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Ptr<SURF> detector = SURF::create( minHessian );
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std::vector<KeyPoint> keypoints_1, keypoints_2;
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detector->detect( img_1, keypoints_1 );
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detector->detect( img_2, keypoints_2 );
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//-- Draw keypoints
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Mat img_keypoints_1; Mat img_keypoints_2;
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drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
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drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
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//-- Show detected (drawn) keypoints
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imshow("Keypoints 1", img_keypoints_1 );
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imshow("Keypoints 2", img_keypoints_2 );
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waitKey(0);
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return 0;
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}
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/* @function readme */
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void readme()
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{ std::cout << " Usage: ./SURF_detector <img1> <img2>" << std::endl; }
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@endcode
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@add_toggle_python
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
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@include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py
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@end_toggle
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Explanation
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-----------
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@@ -79,10 +44,10 @@ Explanation
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Result
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------
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-# Here is the result of the feature detection applied to the first image:
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-# Here is the result of the feature detection applied to the `box.png` image:
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-# And here is the result for the second image:
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-# And here is the result for the `box_in_scene.png` image:
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