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python: 'cv2.' -> 'cv.' via 'import cv2 as cv'

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Alexander Alekhin
2017-12-11 12:55:03 +03:00
parent 9665dde678
commit 5560db73bf
162 changed files with 2083 additions and 2084 deletions
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modules/python/test/test_legacy.py
+16 -16
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@@ -2,7 +2,7 @@
from __future__ import print_function
import numpy as np
import cv2
import cv2 as cv
from tests_common import NewOpenCVTests
@@ -11,13 +11,13 @@ class Hackathon244Tests(NewOpenCVTests):
def test_int_array(self):
a = np.array([-1, 2, -3, 4, -5])
absa0 = np.abs(a)
self.assertTrue(cv2.norm(a, cv2.NORM_L1) == 15)
absa1 = cv2.absdiff(a, 0)
self.assertEqual(cv2.norm(absa1, absa0, cv2.NORM_INF), 0)
self.assertTrue(cv.norm(a, cv.NORM_L1) == 15)
absa1 = cv.absdiff(a, 0)
self.assertEqual(cv.norm(absa1, absa0, cv.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])
flag, ajpg = cv.imencode("img_q90.jpg", a, [cv.IMWRITE_JPEG_QUALITY, 90])
self.assertEqual(flag, True)
self.assertEqual(ajpg.dtype, np.uint8)
self.assertGreater(ajpg.shape[0], 1)
@@ -25,8 +25,8 @@ class Hackathon244Tests(NewOpenCVTests):
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)
imgpt0, jac0 = cv.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([]))
imgpt1, jac1 = cv.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)
@@ -37,17 +37,17 @@ class Hackathon244Tests(NewOpenCVTests):
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)
(retval, out, inliers) = cv.estimateAffine3D(pattern_points, pattern_points)
self.assertEqual(retval, 1)
if cv2.norm(out[2,:]) < 1e-3:
if cv.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])
self.assertLess(cv.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3)
self.assertEqual(cv.countNonZero(inliers), pattern_size[0]*pattern_size[1])
def test_fast(self):
fd = cv2.FastFeatureDetector_create(30, True)
fd = cv.FastFeatureDetector_create(30, True)
img = self.get_sample("samples/data/right02.jpg", 0)
img = cv2.medianBlur(img, 3)
img = cv.medianBlur(img, 3)
keypoints = fd.detect(img)
self.assertTrue(600 <= len(keypoints) <= 700)
for kpt in keypoints:
@@ -71,9 +71,9 @@ class Hackathon244Tests(NewOpenCVTests):
np.random.seed(244)
a = np.random.randn(npt,2).astype('float32')*50 + 150
be = cv2.fitEllipse(a)
br = cv2.minAreaRect(a)
mc, mr = cv2.minEnclosingCircle(a)
be = cv.fitEllipse(a)
br = cv.minAreaRect(a)
mc, mr = cv.minEnclosingCircle(a)
be0 = ((150.2511749267578, 150.77322387695312), (158.024658203125, 197.57696533203125), 37.57804489135742)
br0 = ((161.2974090576172, 154.41793823242188), (199.2301483154297, 207.7177734375), -9.164555549621582)