92 lines
2.7 KiB
JavaScript
92 lines
2.7 KiB
JavaScript
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// 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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if (typeof module !== 'undefined' && module.exports) {
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// The environment is Node.js
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var cv = require('./opencv.js'); // eslint-disable-line no-var
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}
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QUnit.module('Camera Calibration and 3D Reconstruction', {});
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QUnit.test('constants', function(assert) {
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assert.strictEqual(typeof cv.LMEDS, 'number');
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assert.strictEqual(typeof cv.RANSAC, 'number');
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assert.strictEqual(typeof cv.RHO, 'number');
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});
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QUnit.test('findHomography', function(assert) {
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let srcPoints = cv.matFromArray(4, 1, cv.CV_32FC2, [
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56,
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65,
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368,
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52,
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28,
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387,
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389,
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390,
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]);
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let dstPoints = cv.matFromArray(4, 1, cv.CV_32FC2, [
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0,
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0,
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300,
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0,
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0,
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300,
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300,
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300,
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]);
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const mat = cv.findHomography(srcPoints, dstPoints);
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assert.ok(mat instanceof cv.Mat);
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});
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QUnit.test('Rodrigues', function(assert) {
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// Converts a rotation matrix to a rotation vector and vice versa
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// data64F is the output array
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const rvec0 = cv.matFromArray(1, 3, cv.CV_64F, [1,1,1]);
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let rMat0 = new cv.Mat();
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let rvec1 = new cv.Mat();
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// Args: input Mat, output Mat. The function mutates the output Mat, so the function does not return anything.
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// cv.Rodrigues (InputArray=src, OutputArray=dst, jacobian=0)
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// https://docs.opencv.org/2.4/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html#void%20Rodrigues(InputArray%20src,%20OutputArray%20dst,%20OutputArray%20jacobian)
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// vec to Mat, starting number is 3 long and each element is 1.
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cv.Rodrigues(rvec0, rMat0);
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assert.ok(rMat0.data64F.length == 9);
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assert.ok(0.23 > rMat0.data64F[0] > 0.22);
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// convert Mat to Vec, should be same as what we started with, 3 long and each item should be a 1.
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cv.Rodrigues(rMat0, rvec1);
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assert.ok(rvec1.data64F.length == 3);
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assert.ok(1.01 > rvec1.data64F[0] > 0.9);
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// Answer should be around 1: 0.9999999999999999
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});
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QUnit.test('estimateAffine2D', function(assert) {
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const inputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
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1, 1,
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80, 0,
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0, 80,
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80, 80
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]);
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const outputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
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21, 51,
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70, 77,
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40, 40,
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10, 70
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]);
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const M = cv.estimateAffine2D(inputs, outputs);
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assert.ok(M instanceof cv.Mat);
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assert.deepEqual(Array.from(M.data), [
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23, 55, 97, 126, 87, 139, 227, 63, 0, 0,
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0, 0, 0, 0, 232, 191, 71, 246, 12, 68,
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165, 35, 53, 64, 99, 56, 27, 66, 14, 254,
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212, 63, 103, 102, 102, 102, 102, 102, 182, 191,
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195, 252, 174, 22, 55, 97, 73, 64
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]);
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});
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