on running this code an assertion failed error occurred on cmd line window
OPENCV Error : Assertion Failed in cv::cvtColor,file:C:\(address)
#include
#include
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace cv;
/** @function main */
int main()
{
// Load the images
Mat image1 = imread("scene11.jpeg");
Mat image2 = imread("scene21.jpeg");
Mat gray_image1;
Mat gray_image2;
// Convert to Grayscale
cvtColor(image1, gray_image1, CV_RGB2GRAY);
cvtColor(image2, gray_image2, CV_RGB2GRAY);
imshow("image1", image2);
imshow("image2", image1);
if (!gray_image1.data || !gray_image2.data)
{
std::cout << " --(!) Error reading images " << std::endl; return -1;
}
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector(minHessian);
std::vector< KeyPoint > keypoints_object, keypoints_scene;
detector.detect(gray_image1, keypoints_object);
detector.detect(gray_image2, keypoints_scene);
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_object, descriptors_scene;
extractor.compute(gray_image1, keypoints_object, descriptors_object);
extractor.compute(gray_image2, 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);
//-- Use 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]);
}
}
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_object[good_matches[i].queryIdx].pt);
scene.push_back(keypoints_scene[good_matches[i].trainIdx].pt);
}
// Find the Homography Matrix
Mat H = findHomography(obj, scene, CV_RANSAC);
// Use the Homography Matrix to warp the images
cv::Mat result;
warpPerspective(image1, result, H, cv::Size(image1.cols + image2.cols, image1.rows));
cv::Mat half(result, cv::Rect(0, 0, image2.cols, image2.rows));
image2.copyTo(half);
imshow("Result", result);
waitKey(0);
return 0;
}
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