new tutorial

dnn_tutorial/vggfeatures_demo.cpp

@@ -0,0 +1,95 @@
+#include <opencv2/opencv.hpp>
+#include <opencv2/xfeatures2d.hpp>
+#include <iostream>
+
+using namespace cv;
+using namespace cv::xfeatures2d;
+using namespace std;
+
+void find_known_object(Mat &box, Mat &box_scene);
+int main(int argc, char** argv) {
+
+	Mat box = imread("D:/vcprojects/images/box.png");
+	Mat scene = imread("D:/vcprojects/images/box_in_scene.png");
+	imshow("box image", box);
+	imshow("scene image", scene);
+	find_known_object(box, scene);
+
+	waitKey(0);
+	return 0;
+}
+
+void find_known_object(Mat &box, Mat &box_scene) {
+
+	Ptr<SURF> detector = SURF::create();
+	int minHessian = 400;
+	std::vector<KeyPoint> keypoints_1, keypoints_2;
+	detector->setHessianThreshold(minHessian);
+	detector->detect(box, keypoints_1);
+	detector->detect(box_scene, keypoints_2);
+
+	Ptr<VGG> vgg_descriptor = VGG::create();
+	Mat descriptors_1, descriptors_2;
+	vgg_descriptor->compute(box,  keypoints_1, descriptors_1);
+	vgg_descriptor->compute(box_scene, keypoints_2, descriptors_2);
+
+	// 计算匹配点
+	FlannBasedMatcher matcher;
+	std::vector< DMatch > matches;
+	matcher.match(descriptors_1, descriptors_2, matches);
+	double max_dist = 0; double min_dist = 100;
+
+	// 计算最大与最小距离
+	for (int i = 0; i < descriptors_1.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);
+
+	// 寻找最佳匹配，距离越小越好
+	std::vector< DMatch > good_matches;
+	for (int i = 0; i < descriptors_1.rows; i++)
+	{
+		if (matches[i].distance <= min(2 * min_dist, 1.5))
+		{
+			good_matches.push_back(matches[i]);
+		}
+	}
+
+	// 绘制最终匹配点
+	Mat img_matches;
+	drawMatches(box, keypoints_1, box_scene, keypoints_2,
+		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 (size_t i = 0; i < good_matches.size(); i++)
+	{
+		//-- Get the keypoints from the good matches
+		obj.push_back(keypoints_1[good_matches[i].queryIdx].pt);
+		scene.push_back(keypoints_2[good_matches[i].trainIdx].pt);
+	}
+	Mat H = findHomography(obj, scene, 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(box.cols, 0);
+	obj_corners[2] = cvPoint(box.cols, box.rows); obj_corners[3] = cvPoint(0, box.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(box.cols, 0), scene_corners[1] + Point2f(box.cols, 0), Scalar(0, 255, 0), 4);
+	line(img_matches, scene_corners[1] + Point2f(box.cols, 0), scene_corners[2] + Point2f(box.cols, 0), Scalar(0, 255, 0), 4);
+	line(img_matches, scene_corners[2] + Point2f(box.cols, 0), scene_corners[3] + Point2f(box.cols, 0), Scalar(0, 255, 0), 4);
+	line(img_matches, scene_corners[3] + Point2f(box.cols, 0), scene_corners[0] + Point2f(box.cols, 0), Scalar(0, 255, 0), 4);
+	//-- Show detected matches
+	imshow("Good Matches & Object detection", img_matches);
+	imwrite("D:/box_match_result.png", img_matches);
+	waitKey(0);
+}