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Open Source Computer Vision Library
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89 lines
3.5 KiB
89 lines
3.5 KiB
#!/usr/bin/env python |
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from __future__ import print_function |
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import numpy as np |
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import cv2 |
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from tests_common import NewOpenCVTests |
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class Hackathon244Tests(NewOpenCVTests): |
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def test_int_array(self): |
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a = np.array([-1, 2, -3, 4, -5]) |
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absa0 = np.abs(a) |
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self.assertTrue(cv2.norm(a, cv2.NORM_L1) == 15) |
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absa1 = cv2.absdiff(a, 0) |
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self.assertEqual(cv2.norm(absa1, absa0, cv2.NORM_INF), 0) |
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def test_imencode(self): |
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a = np.zeros((480, 640), dtype=np.uint8) |
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flag, ajpg = cv2.imencode("img_q90.jpg", a, [cv2.IMWRITE_JPEG_QUALITY, 90]) |
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self.assertEqual(flag, True) |
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self.assertEqual(ajpg.dtype, np.uint8) |
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self.assertGreater(ajpg.shape[0], 1) |
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self.assertEqual(ajpg.shape[1], 1) |
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def test_projectPoints(self): |
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objpt = np.float64([[1,2,3]]) |
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imgpt0, jac0 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([])) |
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imgpt1, jac1 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), None) |
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self.assertEqual(imgpt0.shape, (objpt.shape[0], 1, 2)) |
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self.assertEqual(imgpt1.shape, imgpt0.shape) |
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self.assertEqual(jac0.shape, jac1.shape) |
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self.assertEqual(jac0.shape[0], 2*objpt.shape[0]) |
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def test_estimateAffine3D(self): |
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pattern_size = (11, 8) |
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pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32) |
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pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2) |
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pattern_points *= 10 |
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(retval, out, inliers) = cv2.estimateAffine3D(pattern_points, pattern_points) |
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self.assertEqual(retval, 1) |
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if cv2.norm(out[2,:]) < 1e-3: |
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out[2,2]=1 |
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self.assertLess(cv2.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3) |
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self.assertEqual(cv2.countNonZero(inliers), pattern_size[0]*pattern_size[1]) |
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def test_fast(self): |
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fd = cv2.FastFeatureDetector_create(30, True) |
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img = self.get_sample("samples/data/right02.jpg", 0) |
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img = cv2.medianBlur(img, 3) |
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keypoints = fd.detect(img) |
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self.assertTrue(600 <= len(keypoints) <= 700) |
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for kpt in keypoints: |
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self.assertNotEqual(kpt.response, 0) |
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def check_close_angles(self, a, b, angle_delta): |
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self.assertTrue(abs(a - b) <= angle_delta or |
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abs(360 - abs(a - b)) <= angle_delta) |
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def check_close_pairs(self, a, b, delta): |
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self.assertLessEqual(abs(a[0] - b[0]), delta) |
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self.assertLessEqual(abs(a[1] - b[1]), delta) |
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def check_close_boxes(self, a, b, delta, angle_delta): |
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self.check_close_pairs(a[0], b[0], delta) |
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self.check_close_pairs(a[1], b[1], delta) |
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self.check_close_angles(a[2], b[2], angle_delta) |
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def test_geometry(self): |
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npt = 100 |
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np.random.seed(244) |
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a = np.random.randn(npt,2).astype('float32')*50 + 150 |
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be = cv2.fitEllipse(a) |
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br = cv2.minAreaRect(a) |
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mc, mr = cv2.minEnclosingCircle(a) |
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be0 = ((150.2511749267578, 150.77322387695312), (158.024658203125, 197.57696533203125), 37.57804489135742) |
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br0 = ((161.2974090576172, 154.41793823242188), (199.2301483154297, 207.7177734375), -9.164555549621582) |
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mc0, mr0 = (160.41790771484375, 144.55152893066406), 136.713500977 |
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self.check_close_boxes(be, be0, 5, 15) |
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self.check_close_boxes(br, br0, 5, 15) |
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self.check_close_pairs(mc, mc0, 5) |
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self.assertLessEqual(abs(mr - mr0), 5) |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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