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Open Source Computer Vision Library
https://opencv.org/
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131 lines
5.2 KiB
131 lines
5.2 KiB
#!/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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import os |
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import sys |
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import unittest |
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from tests_common import NewOpenCVTests |
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try: |
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if sys.version_info[:2] < (3, 0): |
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raise unittest.SkipTest('Python 2.x is not supported') |
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class MatTest(NewOpenCVTests): |
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def test_mat_construct(self): |
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data = np.random.random([10, 10, 3]) |
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#print(np.ndarray.__dictoffset__) # 0 |
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#print(cv.Mat.__dictoffset__) # 88 (> 0) |
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#print(cv.Mat) # <class cv2.Mat> |
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#print(cv.Mat.__base__) # <class 'numpy.ndarray'> |
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mat_data0 = cv.Mat(data) |
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assert isinstance(mat_data0, cv.Mat) |
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assert isinstance(mat_data0, np.ndarray) |
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self.assertEqual(mat_data0.wrap_channels, False) |
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res0 = cv.utils.dumpInputArray(mat_data0) |
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self.assertEqual(res0, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=300 dims(-1)=3 size(-1)=[10 10 3] type(-1)=CV_64FC1") |
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mat_data1 = cv.Mat(data, wrap_channels=True) |
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assert isinstance(mat_data1, cv.Mat) |
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assert isinstance(mat_data1, np.ndarray) |
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self.assertEqual(mat_data1.wrap_channels, True) |
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res1 = cv.utils.dumpInputArray(mat_data1) |
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self.assertEqual(res1, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=100 dims(-1)=2 size(-1)=10x10 type(-1)=CV_64FC3") |
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mat_data2 = cv.Mat(mat_data1) |
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assert isinstance(mat_data2, cv.Mat) |
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assert isinstance(mat_data2, np.ndarray) |
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self.assertEqual(mat_data2.wrap_channels, True) # fail if __array_finalize__ doesn't work |
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res2 = cv.utils.dumpInputArray(mat_data2) |
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self.assertEqual(res2, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=100 dims(-1)=2 size(-1)=10x10 type(-1)=CV_64FC3") |
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def test_mat_construct_4d(self): |
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data = np.random.random([5, 10, 10, 3]) |
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mat_data0 = cv.Mat(data) |
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assert isinstance(mat_data0, cv.Mat) |
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assert isinstance(mat_data0, np.ndarray) |
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self.assertEqual(mat_data0.wrap_channels, False) |
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res0 = cv.utils.dumpInputArray(mat_data0) |
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self.assertEqual(res0, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=1500 dims(-1)=4 size(-1)=[5 10 10 3] type(-1)=CV_64FC1") |
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mat_data1 = cv.Mat(data, wrap_channels=True) |
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assert isinstance(mat_data1, cv.Mat) |
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assert isinstance(mat_data1, np.ndarray) |
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self.assertEqual(mat_data1.wrap_channels, True) |
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res1 = cv.utils.dumpInputArray(mat_data1) |
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self.assertEqual(res1, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=500 dims(-1)=3 size(-1)=[5 10 10] type(-1)=CV_64FC3") |
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mat_data2 = cv.Mat(mat_data1) |
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assert isinstance(mat_data2, cv.Mat) |
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assert isinstance(mat_data2, np.ndarray) |
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self.assertEqual(mat_data2.wrap_channels, True) # __array_finalize__ doesn't work |
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res2 = cv.utils.dumpInputArray(mat_data2) |
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self.assertEqual(res2, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=500 dims(-1)=3 size(-1)=[5 10 10] type(-1)=CV_64FC3") |
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def test_mat_wrap_channels_fail(self): |
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data = np.random.random([2, 3, 4, 520]) |
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mat_data0 = cv.Mat(data) |
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assert isinstance(mat_data0, cv.Mat) |
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assert isinstance(mat_data0, np.ndarray) |
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self.assertEqual(mat_data0.wrap_channels, False) |
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res0 = cv.utils.dumpInputArray(mat_data0) |
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self.assertEqual(res0, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=12480 dims(-1)=4 size(-1)=[2 3 4 520] type(-1)=CV_64FC1") |
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with self.assertRaises(cv.error): |
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mat_data1 = cv.Mat(data, wrap_channels=True) # argument unable to wrap channels, too high (520 > CV_CN_MAX=512) |
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res1 = cv.utils.dumpInputArray(mat_data1) |
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print(mat_data1.__dict__) |
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print(res1) |
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def test_ufuncs(self): |
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data = np.arange(10) |
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mat_data = cv.Mat(data) |
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mat_data2 = 2 * mat_data |
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self.assertEqual(type(mat_data2), cv.Mat) |
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np.testing.assert_equal(2 * data, 2 * mat_data) |
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def test_comparison(self): |
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# Undefined behavior, do NOT use that. |
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# Behavior may be changed in the future |
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data = np.ones((10, 10, 3)) |
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mat_wrapped = cv.Mat(data, wrap_channels=True) |
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mat_simple = cv.Mat(data) |
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np.testing.assert_equal(mat_wrapped, mat_simple) # ???: wrap_channels is not checked for now |
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np.testing.assert_equal(data, mat_simple) |
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np.testing.assert_equal(data, mat_wrapped) |
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#self.assertEqual(mat_wrapped, mat_simple) # ??? |
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#self.assertTrue(mat_wrapped == mat_simple) # ??? |
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#self.assertTrue((mat_wrapped == mat_simple).all()) |
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except unittest.SkipTest as e: |
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message = str(e) |
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class TestSkip(unittest.TestCase): |
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def setUp(self): |
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self.skipTest('Skip tests: ' + message) |
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def test_skip(): |
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pass |
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pass |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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