absa0 = np.abs(a)
self.assert_(cv2.norm(a, cv2.NORM_L1) == 15)
absa1 = cv2.absdiff(a, 0)
- self.assert_(cv2.norm(absa1, absa0, cv2.NORM_INF) == 0)
+ self.assertEqual(cv2.norm(absa1, absa0, cv2.NORM_INF), 0)
def test_imencode(self):
a = np.zeros((480, 640), dtype=np.uint8)
flag, ajpg = cv2.imencode("img_q90.jpg", a, [cv2.IMWRITE_JPEG_QUALITY, 90])
- self.assert_(flag == True and ajpg.dtype == np.uint8 and ajpg.shape[0] > 1 and ajpg.shape[1] == 1)
+ self.assertEqual(flag, True)
+ self.assertEqual(ajpg.dtype, np.uint8)
+ self.assertGreater(ajpg.shape[0], 1)
+ self.assertEqual(ajpg.shape[1], 1)
+
+ def test_projectPoints(self):
+ objpt = np.float64([[1,2,3]])
+ imgpt0, jac0 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([]))
+ imgpt1, jac1 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), None)
+ self.assertEqual(imgpt0.shape, (objpt.shape[0], 1, 2))
+ self.assertEqual(imgpt1.shape, imgpt0.shape)
+ self.assertEqual(jac0.shape, jac1.shape)
+ self.assertEqual(jac0.shape[0], 2*objpt.shape[0])
+
+ def test_estimateAffine3D(self):
+ pattern_size = (11, 8)
+ pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
+ pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2)
+ pattern_points *= 10
+ (retval, out, inliers) = cv2.estimateAffine3D(pattern_points, pattern_points)
+ self.assertEqual(retval, 1)
+ if cv2.norm(out[2,:]) < 1e-3:
+ out[2,2]=1
+ self.assertLess(cv2.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3)
+ self.assertEqual(cv2.countNonZero(inliers), pattern_size[0]*pattern_size[1])
+
+ def test_fast(self):
+ fd = cv2.FastFeatureDetector(30, True)
+ img = self.get_sample("samples/cpp/right02.jpg", 0)
+ img = cv2.medianBlur(img, 3)
+ imgc = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
+ keypoints = fd.detect(img)
+ self.assert_(600 <= len(keypoints) <= 700)
+ for kpt in keypoints:
+ self.assertNotEqual(kpt.response, 0)
+
if __name__ == '__main__':
print "testing", cv.__version__