init - 初始化项目

modules/js/test/test_calib3d.js

@@ -0,0 +1,91 @@
+// 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.
+
+if (typeof module !== 'undefined' && module.exports) {
+  // The environment is Node.js
+  var cv = require('./opencv.js'); // eslint-disable-line no-var
+}
+
+QUnit.module('Camera Calibration and 3D Reconstruction', {});
+
+QUnit.test('constants', function(assert) {
+  assert.strictEqual(typeof cv.LMEDS, 'number');
+  assert.strictEqual(typeof cv.RANSAC, 'number');
+  assert.strictEqual(typeof cv.RHO, 'number');
+});
+
+QUnit.test('findHomography', function(assert) {
+  let srcPoints = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    56,
+    65,
+    368,
+    52,
+    28,
+    387,
+    389,
+    390,
+  ]);
+  let dstPoints = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    0,
+    0,
+    300,
+    0,
+    0,
+    300,
+    300,
+    300,
+  ]);
+
+  const mat = cv.findHomography(srcPoints, dstPoints);
+
+  assert.ok(mat instanceof cv.Mat);
+});
+
+QUnit.test('Rodrigues', function(assert) {
+  // Converts a rotation matrix to a rotation vector and vice versa
+  // data64F is the output array
+  const rvec0 = cv.matFromArray(1, 3, cv.CV_64F, [1,1,1]);
+  let rMat0 = new cv.Mat();
+  let rvec1 = new cv.Mat();
+
+  // Args: input Mat, output Mat. The function mutates the output Mat, so the function does not return anything.
+  // cv.Rodrigues (InputArray=src, OutputArray=dst, jacobian=0)
+  // https://docs.opencv.org/2.4/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html#void%20Rodrigues(InputArray%20src,%20OutputArray%20dst,%20OutputArray%20jacobian)
+  // vec to Mat, starting number is 3 long and each element is 1.
+  cv.Rodrigues(rvec0, rMat0);
+
+  assert.ok(rMat0.data64F.length == 9);
+  assert.ok(0.23 > rMat0.data64F[0] > 0.22);
+
+  // convert Mat to Vec, should be same as what we started with, 3 long and each item should be a 1.
+  cv.Rodrigues(rMat0, rvec1);
+
+  assert.ok(rvec1.data64F.length == 3);
+  assert.ok(1.01 > rvec1.data64F[0] > 0.9);
+  // Answer should be around 1: 0.9999999999999999
+});
+
+QUnit.test('estimateAffine2D', function(assert) {
+   const inputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    1, 1,
+    80, 0,
+    0, 80,
+    80, 80
+  ]);
+  const outputs = cv.matFromArray(4, 1, cv.CV_32FC2, [
+    21, 51,
+    70, 77,
+    40, 40,
+    10, 70
+  ]);
+  const M = cv.estimateAffine2D(inputs, outputs);
+  assert.ok(M instanceof cv.Mat);
+  assert.deepEqual(Array.from(M.data), [
+     23,  55,  97, 126,  87, 139, 227,  63,   0,   0,
+      0,   0,   0,   0, 232, 191,  71, 246,  12,  68,
+    165,  35,  53,  64,  99,  56,  27,  66,  14, 254,
+    212,  63, 103, 102, 102, 102, 102, 102, 182, 191,
+    195, 252, 174,  22,  55,  97,  73,  64
+  ]);
+});