I hosted a test of this problem here iCollect
It seems opencv.js doesn’t have cv.Point2fVector as I am getting an error
"Uncaught TypeError: cv.Point2fVector is not a constructor"
when I declare points1 vector as follows:
let points1 = new cv.Point2fVector();
So I am now declaring “points1 and points2” as follows:
let points1 = [];
the findHomography() succeeds when I do this but the warpPerspective() fails with an ‘unhandled exception’
I have 2 questions:
- how should I declare the vectors “points1” and “points2”?
- if the declaration of “= [];” is fine, then why would warpPerspective() fail with an ‘unhandled exception’
I included the cpp code inline below that I am referencing from https://learnopencv.com/image-alignment-feature-based-using-opencv-c-python
function Align_img() {
//im2 is the original reference image we are trying to align to
let im2 = cv.imread(image_A_element);
//im1 is the image we are trying to line up correctly
let im1 = cv.imread(image_B_element);
//17 Convert images to grayscale
//18 Mat im1Gray, im2Gray;
//19 cvtColor(im1, im1Gray, CV_BGR2GRAY);
//20 cvtColor(im2, im2Gray, CV_BGR2GRAY);
let im1Gray = new cv.Mat();
let im2Gray = new cv.Mat();
cv.cvtColor(im1, im1Gray, cv.COLOR_BGRA2GRAY);
cv.cvtColor(im2, im2Gray, cv.COLOR_BGRA2GRAY);
//22 Variables to store keypoints and descriptors
//23 std::vector<KeyPoint> keypoints1, keypoints2;
//24 Mat descriptors1, descriptors2;
let keypoints1 = new cv.KeyPointVector();
let keypoints2 = new cv.KeyPointVector();
let descriptors1 = new cv.Mat();
let descriptors2 = new cv.Mat();
//26 Detect ORB features and compute descriptors.
//27 Ptr<Feature2D> orb = ORB::create(MAX_FEATURES);
//28 orb->detectAndCompute(im1Gray, Mat(), keypoints1, descriptors1);
//29 orb->detectAndCompute(im2Gray, Mat(), keypoints2, descriptors2);
var orb = new cv.ORB(5000);
orb.detectAndCompute(im1Gray, new cv.Mat(), keypoints1, descriptors1);
orb.detectAndCompute(im2Gray, new cv.Mat(), keypoints2, descriptors2);
//31 Match features.
//32 std::vector<DMatch> matches;
//33 Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-Hamming");
//34 matcher->match(descriptors1, descriptors2, matches, Mat());
let bf = new cv.BFMatcher(cv.NORM_HAMMING, true);
let matches = new cv.DMatchVector();
bf.match(descriptors1, descriptors2, matches);
//36 Sort matches by score
//37 std::sort(matches.begin(), matches.end());
//39 Remove not so good matches
//40 const int numGoodMatches = matches.size() * GOOD_MATCH_PERCENT;
//41 matches.erase(matches.begin()+numGoodMatches, matches.end());
let good_matches = new cv.DMatchVector();
console.log("matches.size: ", matches.size());
for (let i = 0; i < matches.size(); i++) {
if (matches.get(i).distance < 30) {
good_matches.push_back(matches.get(i));
}
}
//44 Draw top matches
//45 Mat imMatches;
//46 drawMatches(im1, keypoints1, im2, keypoints2, matches, imMatches);
//47 imwrite("matches.jpg", imMatches);
let imMatches = new cv.Mat();
let color = new cv.Scalar(0,255,0, 255);
cv.drawMatches(im1, keypoints1, im2, keypoints2, good_matches, imMatches, color);
cv.imshow('imageCompareMatches', imMatches);
//50 Extract location of good matches
//51 std::vector<Point2f> points1, points2;
//53 for( size_t i = 0; i < matches.size(); i++ )
//54 {
//55 points1.push_back( keypoints1[ matches[i].queryIdx ].pt );
//56 points2.push_back( keypoints2[ matches[i].trainIdx ].pt );
//57 }
let points1 = new cv.Point2fVector();//[];
let points2 = new cv.Point2fVector();//[];
if(good_matches.size() == 0){
alert("No matches found!");
return;
}
for (let i = 0; i < good_matches.size(); i++) {
points1.push_back(keypoints1.get(good_matches.get(i).queryIdx ).pt );
points2.push_back(keypoints2.get(good_matches.get(i).trainIdx ).pt );
}
//59 Find homography
//60 h = findHomography( points1, points2, RANSAC );
//The first 2 arguments to findHomography need to be matArray so you must convert your point1 and point2 to matArray
let mat1 = cv.matFromArray(points1.length, 2, cv.CV_32F, points1);
let mat2 = cv.matFromArray(points2.length, 2, cv.CV_32F, points2);
// Calculate Homography points1 and points2 need to be CV_32FC2 - a 32-bit, floating-point, and 2-channels structure
let h = cv.findHomography(mat1, mat2, cv.RANSAC);
//62 Use homography to warp image
//63 warpPerspective(im1, im1Reg, h, im2.size());
let image_B_final_result = new cv.Mat();
cv.warpPerspective(im1, image_B_final_result, h, im2.size());
cv.imshow('imageAligned', image_B_final_result);
matches.delete();
bf.delete();
orb.delete();
descriptors1.delete();
descriptors2.delete();
keypoints1.delete();
keypoints2.delete();
im1Gray.delete();
im2Gray.delete();
h.delete();
image_B_final_result.delete();
mat1.delete();
mat2.delete();
}