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* calib3d: use normalized input in solvePnPGeneric() * calib3d: java regression test for solvePnPGeneric * calib3d: python regression test for solvePnPGeneric
45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
#!/usr/bin/env python
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# Python 2/3 compatibility
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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 solvepnp_test(NewOpenCVTests):
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def test_regression_16040(self):
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obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
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img_points = np.array(
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[[700, 400], [700, 600], [900, 600], [900, 400]], dtype=np.float32
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)
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cameraMatrix = np.array(
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[[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
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)
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distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
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r = np.array([], dtype=np.float32)
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x, r, t, e = cv.solvePnPGeneric(
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obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
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)
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def test_regression_16040_2(self):
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obj_points = np.array([[0, 0, 0], [0, 1, 0], [1, 1, 0], [1, 0, 0]], dtype=np.float32)
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img_points = np.array(
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[[[700, 400], [700, 600], [900, 600], [900, 400]]], dtype=np.float32
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)
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cameraMatrix = np.array(
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[[712.0634, 0, 800], [0, 712.540, 500], [0, 0, 1]], dtype=np.float32
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)
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distCoeffs = np.array([[0, 0, 0, 0]], dtype=np.float32)
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r = np.array([], dtype=np.float32)
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x, r, t, e = cv.solvePnPGeneric(
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obj_points, img_points, cameraMatrix, distCoeffs, reprojectionError=r
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)
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if __name__ == '__main__':
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NewOpenCVTests.bootstrap()
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