ML_SIFT.cpp

/*
#include <opencv2/opencv.hpp>
#include <opencv2/nonfree/nonfree.hpp>
#include <iostream>
#include <vector>
#include <cmath>

using namespace std;
using namespace cv;

const double THRESHOLD = 400;

// Calculate euclid distance

double euclidDistance(Mat& vec1, Mat& vec2) {
	double sum = 0.0;
	int dim = vec1.cols;
	for (int i = 0; i < dim; i++) {
		sum += (vec1.at<uchar>(0, i) - vec2.at<uchar>(0, i)) * (vec1.at<uchar>(0, i) - vec2.at<uchar>(0, i));
	}
	return sqrt(sum);
}


// Find the index of nearest neighbor point from keypoints.

int nearestNeighbor(Mat& vec, vector<KeyPoint>& keypoints, Mat& descriptors) {
	int neighbor = -1;
	double minDist = 1e6;

	for (int i = 0; i < descriptors.rows; i++) {
		KeyPoint pt = keypoints[i];
		Mat v = descriptors.row(i);
		double d = euclidDistance(vec, v);
		//printf("%d %f\n", v.cols, d);
		if (d < minDist) {
			minDist = d;
			neighbor = i;
		}
	}

	if (minDist < THRESHOLD) {
		return neighbor;
	}

	return -1;
}


// Find pairs of points with the smallest distace between them

void findPairs(vector<KeyPoint>& keypoints1, Mat& descriptors1,
	vector<KeyPoint>& keypoints2, Mat& descriptors2,
	vector<Point2f>& srcPoints, vector<Point2f>& dstPoints) {
	for (int i = 0; i < descriptors1.rows; i++) {
		KeyPoint pt1 = keypoints1[i];
		Mat desc1 = descriptors1.row(i);
		int nn = nearestNeighbor(desc1, keypoints2, descriptors2);
		if (nn >= 0) {
			KeyPoint pt2 = keypoints2[nn];
			srcPoints.push_back(pt1.pt);
			dstPoints.push_back(pt2.pt);
		}
	}
}

int main(int argc, char** argv) 
{

	const char* filename = "C:/Users/Nitin/Documents/Visual Studio 2013/files/picture134.jpg";

	printf("load file:%s\n", filename);

	// initialize detector and extractor
	FeatureDetector* detector;
	detector = new SiftFeatureDetector(
		0, // nFeatures
		4, // nOctaveLayers
		0.04, // contrastThreshold
		10, //edgeThreshold
		1.6 //sigma
		);

	DescriptorExtractor* extractor;
	extractor = new SiftDescriptorExtractor();

	// Compute keypoints and descriptor from the source image in advance
	vector<KeyPoint> keypoints2;
	Mat descriptors2;

	Mat originalGrayImage = imread(filename, CV_LOAD_IMAGE_GRAYSCALE);
	if (!originalGrayImage.data) {
		cerr << "gray image load error" << endl;
		return -1;
	}
	Mat originalColorImage = imread(filename, CV_LOAD_IMAGE_ANYCOLOR | CV_LOAD_IMAGE_ANYDEPTH);
	if (!originalColorImage.data) {
		cerr << "color image open error" << endl;
		return -1;
	}

	detector->detect(originalGrayImage, keypoints2);
	extractor->compute(originalGrayImage, keypoints2, descriptors2);
	printf("original image:%d keypoints are found.\n", (int)keypoints2.size());

	VideoCapture capture(0);
	capture.set(CV_CAP_PROP_FRAME_WIDTH, 640);
	capture.set(CV_CAP_PROP_FRAME_HEIGHT, 480);

	namedWindow("mywindow");
	Mat frame;
	while (1) {
		capture >> frame;

		// load gray scale image from camera
		Size size = frame.size();
		Mat grayFrame(size, CV_8UC1);
		cvtColor(frame, grayFrame, CV_BGR2GRAY);
		if (!grayFrame.data) {
			cerr << "cannot find image file1" << endl;
			exit(-1);
		}

		// Create a image for displaying mathing keypoints
		Size sz = Size(size.width + originalColorImage.size().width, size.height + originalColorImage.size().height);
		Mat matchingImage = Mat::zeros(sz, CV_8UC3);

		// Draw camera frame
		Mat roi1 = Mat(matchingImage, Rect(0, 0, size.width, size.height));
		frame.copyTo(roi1);
		// Draw original image
		Mat roi2 = Mat(matchingImage, Rect(size.width, size.height, originalColorImage.size().width, originalColorImage.size().height));
		originalColorImage.copyTo(roi2);

		vector<KeyPoint> keypoints1;
		Mat descriptors1;
		vector<DMatch> matches;

		// Detect keypoints
		detector->detect(grayFrame, keypoints1);
		extractor->compute(grayFrame, keypoints1, descriptors1);

		printf("image1:%d keypoints are found.\n", keypoints1.size());
		for (int i = 0; i<keypoints1.size(); i++){
			KeyPoint kp = keypoints1[i];
			circle(matchingImage, kp.pt, cvRound(kp.size*0.25), Scalar(255, 255, 0), 1, 8, 0);
		}
		// Find nearest neighbor pairs
		vector<Point2f> srcPoints;
		vector<Point2f> dstPoints;
		findPairs(keypoints1, descriptors1, keypoints2, descriptors2, srcPoints, dstPoints);
		printf("%d keypoints are matched.\n", srcPoints.size());
		char text[256];
		sprintf(text, "%d/%d keypoints matched.", srcPoints.size(), keypoints2.size());
		putText(matchingImage, text, Point(0, cvRound(size.height + 30)), FONT_HERSHEY_SCRIPT_SIMPLEX, 1, Scalar(0, 0, 255));
		
		// Draw line between nearest neighbor pairs
		for (int i = 0; i < (int)srcPoints.size(); ++i) {
			Point2f pt1 = srcPoints[i];
			Point2f pt2 = dstPoints[i];
			Point2f from = pt1;
			Point2f to = Point(size.width + pt2.x, size.height + pt2.y);
			line(matchingImage, from, to, Scalar(0, 255, 255));
		}
		
		// Display mathing image
		imshow("mywindow", matchingImage);
		int c = waitKey(2);
		if ((char)c == 'p' || (char)c == 'P')
			break;
	}

	return 0;
}
*/