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