Open Source Computer Vision Library https://opencv.org/
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
function generateTestFrame(width, height) {
let w = width || 200;
let h = height || 200;
let img = new cv.Mat(h, w, cv.CV_8UC1, new cv.Scalar(0, 0, 0, 0));
let s = new cv.Scalar(255, 255, 255, 255);
let s128 = new cv.Scalar(128, 128, 128, 128);
let rect = new cv.Rect(w / 4, h / 4, w / 2, h / 2);
img.roi(rect).setTo(s);
img.roi(new cv.Rect(w / 2 - w / 8, h / 2 - h / 8, w / 4, h / 4)).setTo(s128);
cv.rectangle(img, new cv.Point(w / 8, h / 8), new cv.Point(w - w / 8, h - h / 8), s, 5);
cv.rectangle(img, new cv.Point(w / 5, h / 5), new cv.Point(w - w / 5, h - h / 5), s128, 3);
cv.line(img, new cv.Point(-w, 0), new cv.Point(w / 2, h / 2), s128, 5);
cv.line(img, new cv.Point(2*w, 0), new cv.Point(w / 2, h / 2), s, 5);
return img;
}
QUnit.module('Features2D', {});
QUnit.test('Detectors', function(assert) {
let image = generateTestFrame();
let kp = new cv.KeyPointVector();
let orb = new cv.ORB();
orb.detect(image, kp);
assert.equal(kp.size(), 67, 'ORB');
let mser = new cv.MSER();
mser.detect(image, kp);
assert.equal(kp.size(), 7, 'MSER');
let brisk = new cv.BRISK();
brisk.detect(image, kp);
assert.equal(kp.size(), 191, 'BRISK');
let ffd = new cv.FastFeatureDetector();
ffd.detect(image, kp);
assert.equal(kp.size(), 12, 'FastFeatureDetector');
let afd = new cv.AgastFeatureDetector();
afd.detect(image, kp);
assert.equal(kp.size(), 67, 'AgastFeatureDetector');
let gftt = new cv.GFTTDetector();
gftt.detect(image, kp);
assert.equal(kp.size(), 168, 'GFTTDetector');
let kaze = new cv.KAZE();
kaze.detect(image, kp);
assert.equal(kp.size(), 159, 'KAZE');
let akaze = new cv.AKAZE();
akaze.detect(image, kp);
assert.equal(kp.size(), 53, 'AKAZE');
});
QUnit.test('SimpleBlobDetector', function(assert) {
let image = generateTestFrame();
let kp = new cv.KeyPointVector();
let sbd = new cv.SimpleBlobDetector();
sbd.detect(image, kp);
assert.equal(kp.size(), 0);
});
QUnit.test('BFMatcher', function(assert) {
// Generate key points.
let image = generateTestFrame();
let kp = new cv.KeyPointVector();
let descriptors = new cv.Mat();
let orb = new cv.ORB();
orb.detectAndCompute(image, new cv.Mat(), kp, descriptors);
assert.equal(kp.size(), 67);
// Run a matcher.
let dm = new cv.DMatchVector();
let matcher = new cv.BFMatcher();
matcher.match(descriptors, descriptors, dm);
assert.equal(dm.size(), 67);
});
QUnit.test('Drawing', function(assert) {
// Generate key points.
let image = generateTestFrame();
let kp = new cv.KeyPointVector();
let descriptors = new cv.Mat();
let orb = new cv.ORB();
orb.detectAndCompute(image, new cv.Mat(), kp, descriptors);
assert.equal(kp.size(), 67);
let dst = new cv.Mat();
cv.drawKeypoints(image, kp, dst);
assert.equal(dst.rows, image.rows);
assert.equal(dst.cols, image.cols);
// Run a matcher.
let dm = new cv.DMatchVector();
let matcher = new cv.BFMatcher();
matcher.match(descriptors, descriptors, dm);
assert.equal(dm.size(), 67);
cv.drawMatches(image, kp, image, kp, dm, dst);
assert.equal(dst.rows, image.rows);
assert.equal(dst.cols, 2 * image.cols);
dm = new cv.DMatchVectorVector();
matcher.knnMatch(descriptors, descriptors, dm, 2);
assert.equal(dm.size(), 67);
cv.drawMatchesKnn(image, kp, image, kp, dm, dst);
assert.equal(dst.rows, image.rows);
assert.equal(dst.cols, 2 * image.cols);
});