python: 'cv2.' -> 'cv.' via 'import cv2 as cv'
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@@ -9,7 +9,7 @@ reads distorted images, calculates the calibration and write undistorted images
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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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import cv2 as cv
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from tests_common import NewOpenCVTests
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@@ -38,10 +38,10 @@ class calibration_test(NewOpenCVTests):
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continue
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h, w = img.shape[:2]
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found, corners = cv2.findChessboardCorners(img, pattern_size)
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found, corners = cv.findChessboardCorners(img, pattern_size)
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if found:
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term = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1)
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cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
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term = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_COUNT, 30, 0.1)
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cv.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
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if not found:
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continue
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@@ -50,7 +50,7 @@ class calibration_test(NewOpenCVTests):
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obj_points.append(pattern_points)
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# calculate camera distortion
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rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None, flags = 0)
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rms, camera_matrix, dist_coefs, _rvecs, _tvecs = cv.calibrateCamera(obj_points, img_points, (w, h), None, None, flags = 0)
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eps = 0.01
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normCamEps = 10.0
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@@ -64,8 +64,8 @@ class calibration_test(NewOpenCVTests):
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1.21234330e-03, -1.40825372e-04, 1.54865844e-01]
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self.assertLess(abs(rms - 0.196334638034), eps)
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self.assertLess(cv2.norm(camera_matrix - cameraMatrixTest, cv2.NORM_L1), normCamEps)
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self.assertLess(cv2.norm(dist_coefs - distCoeffsTest, cv2.NORM_L1), normDistEps)
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self.assertLess(cv.norm(camera_matrix - cameraMatrixTest, cv.NORM_L1), normCamEps)
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self.assertLess(cv.norm(dist_coefs - distCoeffsTest, cv.NORM_L1), normDistEps)
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