95 lines
3.9 KiB
Python
95 lines
3.9 KiB
Python
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#!/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 as cv
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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(cv.norm(a, cv.NORM_L1) == 15)
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absa1 = cv.absdiff(a, 0)
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self.assertEqual(cv.norm(absa1, absa0, cv.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 = cv.imencode("img_q90.jpg", a, [cv.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.assertTrue(isinstance(ajpg, np.ndarray), "imencode returned buffer of wrong type: {}".format(type(ajpg)))
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self.assertEqual(len(ajpg.shape), 1, "imencode returned buffer with wrong shape: {}".format(ajpg.shape))
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self.assertGreaterEqual(len(ajpg), 1, "imencode length of the returned buffer should be at least 1")
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self.assertLessEqual(
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len(ajpg), a.size,
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"imencode length of the returned buffer shouldn't exceed number of elements in original image"
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)
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def test_projectPoints(self):
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objpt = np.float64([[1,2,3]])
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imgpt0, jac0 = cv.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([]))
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imgpt1, jac1 = cv.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) = cv.estimateAffine3D(pattern_points, pattern_points)
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self.assertEqual(retval, 1)
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if cv.norm(out[2,:]) < 1e-3:
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out[2,2]=1
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self.assertLess(cv.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3)
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self.assertEqual(cv.countNonZero(inliers), pattern_size[0]*pattern_size[1])
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def test_fast(self):
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fd = cv.FastFeatureDetector_create(30, True)
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img = self.get_sample("samples/data/right02.jpg", 0)
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img = cv.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 = cv.fitEllipse(a)
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br = cv.minAreaRect(a)
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mc, mr = cv.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), (207.7177734375, 199.2301483154297), 80.83544921875)
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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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