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opencv_surf 소스코드 #23

Open taeho9o opened 9 years ago

taeho9o commented 9 years ago

include

include

include "opencv2/core/core.hpp"

include "opencv2/features2d/features2d.hpp"

include "opencv2/highgui/highgui.hpp"

include "opencv2/calib3d/calib3d.hpp"

include "opencv2/nonfree/nonfree.hpp"

using namespace cv;

/* @function main / int main( int argc, char\ argv ) { Mat img_object = imread( "test1.jpg", CV_LOAD_IMAGE_GRAYSCALE ); // Mat img_scene = imread( "test7.jpg", CV_LOAD_IMAGE_GRAYSCALE ); //

if( !img_object.data || !img_scene.data )
{ std::cout<< " --(!) Error reading images " << std::endl; return -1; }

//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 900;

SurfFeatureDetector detector( minHessian );

std::vector<KeyPoint> keypoints_object, keypoints_scene;

detector.detect( img_object, keypoints_object );
detector.detect( img_scene, keypoints_scene );

//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;

Mat descriptors_object, descriptors_scene;

extractor.compute( img_object, keypoints_object, descriptors_object );
extractor.compute( img_scene, keypoints_scene, descriptors_scene );

//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_object, descriptors_scene, matches );

double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_object.rows; i++ )
{ double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}

printf("-- Max dist : %f \n", max_dist );
printf("-- Min dist : %f \n", min_dist );

//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
std::vector< DMatch > good_matches;

for( int i = 0; i < descriptors_object.rows; i++ )
{ if( matches[i].distance < 3*min_dist )
{ good_matches.push_back( matches[i]); }
}

Mat img_matches;
drawMatches( img_object, keypoints_object, img_scene, keypoints_scene,
    good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
    vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

//-- Localize the object
std::vector<Point2f> obj;
std::vector<Point2f> scene;

for( int i = 0; i < good_matches.size(); i++ )
{
    //-- Get the keypoints from the good matches
    obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
    scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
}

Mat H = findHomography( obj, scene, CV_RANSAC );

//-- Get the corners from the image_1 ( the object to be "detected" )
std::vector<Point2f> obj_corners(4);
obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 );
obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows );
std::vector<Point2f> scene_corners(4);

perspectiveTransform( obj_corners, scene_corners, H);

//-- Draw lines between the corners (the mapped object in the scene - image_2 )
line( img_matches, scene_corners[0] + Point2f( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 );
line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );

//-- Show detected matches
imshow( "Good Matches & Object detection", img_matches );

waitKey(0);
return 0;

}

cheolgi commented 9 years ago

소스코드를 issue로 올리는 거는 너무하다고 생각되지 않니?

    1. 15., 오후 5:41, TAEHOLEE notifications@github.com 작성:

include

include

include "opencv2/core/core.hpp"

include "opencv2/features2d/features2d.hpp"

include "opencv2/highgui/highgui.hpp"

include "opencv2/calib3d/calib3d.hpp"

include "opencv2/nonfree/nonfree.hpp"

using namespace cv;

/* @function https://github.com/function main / int main( int argc, char\ argv ) { Mat img_object = imread( "test1.jpg", CV_LOAD_IMAGE_GRAYSCALE ); // Mat img_scene = imread( "test7.jpg", CV_LOAD_IMAGE_GRAYSCALE ); //

if( !img_object.data || !img_scene.data ) { std::cout<< " --(!) Error reading images " << std::endl; return -1; }

//-- Step 1: Detect the keypoints using SURF Detector int minHessian = 900;

SurfFeatureDetector detector( minHessian );

std::vector keypoints_object, keypoints_scene;

detector.detect( img_object, keypoints_object ); detector.detect( img_scene, keypoints_scene );

//-- Step 2: Calculate descriptors (feature vectors) SurfDescriptorExtractor extractor;

Mat descriptors_object, descriptors_scene;

extractor.compute( img_object, keypoints_object, descriptors_object ); extractor.compute( img_scene, keypoints_scene, descriptors_scene );

//-- Step 3: Matching descriptor vectors using FLANN matcher FlannBasedMatcher matcher; std::vector< DMatch > matches; matcher.match( descriptors_object, descriptors_scene, matches );

double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints for( int i = 0; i < descriptors_object.rows; i++ ) { double dist = matches[i].distance; if( dist < min_dist ) min_dist = dist; if( dist > max_dist ) max_dist = dist; }

printf("-- Max dist : %f \n", max_dist ); printf("-- Min dist : %f \n", min_dist );

//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist ) std::vector< DMatch > good_matches;

for( int i = 0; i < descriptors_object.rows; i++ ) { if( matches[i].distance < 3*min_dist ) { good_matches.push_back( matches[i]); } }

Mat img_matches; drawMatches( img_object, keypoints_object, img_scene, keypoints_scene, good_matches, img_matches, Scalar::all(-1), Scalar::all(-1), vector(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );

//-- Localize the object std::vector obj; std::vector scene;

for( int i = 0; i < good_matches.size(); i++ ) { //-- Get the keypoints from the good matches obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt ); scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt ); }

Mat H = findHomography( obj, scene, CV_RANSAC );

//-- Get the corners from the image_1 ( the object to be "detected" ) std::vector obj_corners(4); obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 ); obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows ); std::vector scene_corners(4);

perspectiveTransform( obj_corners, scene_corners, H);

//-- Draw lines between the corners (the mapped object in the scene - image_2 ) line( img_matches, scene_corners[0] + Point2f( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 ); line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 ); line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );

//-- Show detected matches imshow( "Good Matches & Object detection", img_matches );

waitKey(0); return 0; }

— Reply to this email directly or view it on GitHub https://github.com/kauHyunju/kaudesign2015/issues/23.

taeho9o commented 9 years ago

교수님 죄송합니다 코드 공유하려고 올렸다가 그대로 두었습니다 정정하겠습니다

cheolgi commented 9 years ago

내가 쓴 글을 내가 읽어봐도 정색하고 쓴 거 같이 보이네...

정색하고 쓴 글은 아니니까 심각하게 받아들이지는 말아라... :)

    1. 21., 오후 3:22, TAEHOLEE notifications@github.com 작성:

교수님 죄송합니다 코드 공유하려고 올렸다가 그대로 두었습니다 정정하겠습니다

— Reply to this email directly or view it on GitHub https://github.com/kauHyunju/kaudesign2015/issues/23#issuecomment-94652611.