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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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This commit is contained in:
Alexander Alekhin
2021-09-02 15:24:04 +00:00
parent c11195d5e3 7c23ec90a9
commit 5aa7435d25
15 changed files with 633 additions and 434 deletions
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modules/python/test/test_legacy.py
+7 -2
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@@ -20,8 +20,13 @@ class Hackathon244Tests(NewOpenCVTests):
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)
self.assertEqual(ajpg.shape[1], 1)
self.assertTrue(isinstance(ajpg, np.ndarray), "imencode returned buffer of wrong type: {}".format(type(ajpg)))
self.assertEqual(len(ajpg.shape), 1, "imencode returned buffer with wrong shape: {}".format(ajpg.shape))
self.assertGreaterEqual(len(ajpg), 1, "imencode length of the returned buffer should be at least 1")
self.assertLessEqual(
len(ajpg), a.size,
"imencode length of the returned buffer shouldn't exceed number of elements in original image"
)
def test_projectPoints(self):
objpt = np.float64([[1,2,3]])
modules/python/test/test_misc.py
+103
View File
@@ -481,6 +481,109 @@ class Arguments(NewOpenCVTests):
cv.utils.testReservedKeywordConversion(20, lambda_=-4, from_=12), format_str.format(20, -4, 12)
)
def test_parse_vector_int_convertible(self):
np.random.seed(123098765)
try_to_convert = partial(self._try_to_convert, cv.utils.dumpVectorOfInt)
arr = np.random.randint(-20, 20, 40).astype(np.int32).reshape(10, 2, 2)
int_min, int_max = get_limits(ctypes.c_int)
for convertible in ((int_min, 1, 2, 3, int_max), [40, 50], tuple(),
np.array([int_min, -10, 24, int_max], dtype=np.int32),
np.array([10, 230, 12], dtype=np.uint8), arr[:, 0, 1],):
expected = "[" + ", ".join(map(str, convertible)) + "]"
actual = try_to_convert(convertible)
self.assertEqual(expected, actual,
msg=get_conversion_error_msg(convertible, expected, actual))
def test_parse_vector_int_not_convertible(self):
np.random.seed(123098765)
arr = np.random.randint(-20, 20, 40).astype(np.float).reshape(10, 2, 2)
int_min, int_max = get_limits(ctypes.c_int)
test_dict = {1: 2, 3: 10, 10: 20}
for not_convertible in ((int_min, 1, 2.5, 3, int_max), [True, 50], 'test', test_dict,
reversed([1, 2, 3]),
np.array([int_min, -10, 24, [1, 2]], dtype=np.object),
np.array([[1, 2], [3, 4]]), arr[:, 0, 1],):
with self.assertRaises(TypeError, msg=get_no_exception_msg(not_convertible)):
_ = cv.utils.dumpVectorOfInt(not_convertible)
def test_parse_vector_double_convertible(self):
np.random.seed(1230965)
try_to_convert = partial(self._try_to_convert, cv.utils.dumpVectorOfDouble)
arr = np.random.randint(-20, 20, 40).astype(np.int32).reshape(10, 2, 2)
for convertible in ((1, 2.12, 3.5), [40, 50], tuple(),
np.array([-10, 24], dtype=np.int32),
np.array([-12.5, 1.4], dtype=np.double),
np.array([10, 230, 12], dtype=np.float), arr[:, 0, 1], ):
expected = "[" + ", ".join(map(lambda v: "{:.2f}".format(v), convertible)) + "]"
actual = try_to_convert(convertible)
self.assertEqual(expected, actual,
msg=get_conversion_error_msg(convertible, expected, actual))
def test_parse_vector_double_not_convertible(self):
test_dict = {1: 2, 3: 10, 10: 20}
for not_convertible in (('t', 'e', 's', 't'), [True, 50.55], 'test', test_dict,
np.array([-10.1, 24.5, [1, 2]], dtype=np.object),
np.array([[1, 2], [3, 4]]),):
with self.assertRaises(TypeError, msg=get_no_exception_msg(not_convertible)):
_ = cv.utils.dumpVectorOfDouble(not_convertible)
def test_parse_vector_rect_convertible(self):
np.random.seed(1238765)
try_to_convert = partial(self._try_to_convert, cv.utils.dumpVectorOfRect)
arr_of_rect_int32 = np.random.randint(5, 20, 4 * 3).astype(np.int32).reshape(3, 4)
arr_of_rect_cast = np.random.randint(10, 40, 4 * 5).astype(np.uint8).reshape(5, 4)
for convertible in (((1, 2, 3, 4), (10, -20, 30, 10)), arr_of_rect_int32, arr_of_rect_cast,
arr_of_rect_int32.astype(np.int8), [[5, 3, 1, 4]],
((np.int8(4), np.uint8(10), np.int(32), np.int16(55)),)):
expected = "[" + ", ".join(map(lambda v: "[x={}, y={}, w={}, h={}]".format(*v), convertible)) + "]"
actual = try_to_convert(convertible)
self.assertEqual(expected, actual,
msg=get_conversion_error_msg(convertible, expected, actual))
def test_parse_vector_rect_not_convertible(self):
np.random.seed(1238765)
arr = np.random.randint(5, 20, 4 * 3).astype(np.float).reshape(3, 4)
for not_convertible in (((1, 2, 3, 4), (10.5, -20, 30.1, 10)), arr,
[[5, 3, 1, 4], []],
((np.float(4), np.uint8(10), np.int(32), np.int16(55)),)):
with self.assertRaises(TypeError, msg=get_no_exception_msg(not_convertible)):
_ = cv.utils.dumpVectorOfRect(not_convertible)
def test_vector_general_return(self):
expected_number_of_mats = 5
expected_shape = (10, 10, 3)
expected_type = np.uint8
mats = cv.utils.generateVectorOfMat(5, 10, 10, cv.CV_8UC3)
self.assertTrue(isinstance(mats, tuple),
"Vector of Mats objects should be returned as tuple. Got: {}".format(type(mats)))
self.assertEqual(len(mats), expected_number_of_mats, "Returned array has wrong length")
for mat in mats:
self.assertEqual(mat.shape, expected_shape, "Returned Mat has wrong shape")
self.assertEqual(mat.dtype, expected_type, "Returned Mat has wrong elements type")
empty_mats = cv.utils.generateVectorOfMat(0, 10, 10, cv.CV_32FC1)
self.assertTrue(isinstance(empty_mats, tuple),
"Empty vector should be returned as empty tuple. Got: {}".format(type(mats)))
self.assertEqual(len(empty_mats), 0, "Vector of size 0 should be returned as tuple of length 0")
def test_vector_fast_return(self):
expected_shape = (5, 4)
rects = cv.utils.generateVectorOfRect(expected_shape[0])
self.assertTrue(isinstance(rects, np.ndarray),
"Vector of rectangles should be returned as numpy array. Got: {}".format(type(rects)))
self.assertEqual(rects.dtype, np.int32, "Vector of rectangles has wrong elements type")
self.assertEqual(rects.shape, expected_shape, "Vector of rectangles has wrong shape")
empty_rects = cv.utils.generateVectorOfRect(0)
self.assertTrue(isinstance(empty_rects, tuple),
"Empty vector should be returned as empty tuple. Got: {}".format(type(empty_rects)))
self.assertEqual(len(empty_rects), 0, "Vector of size 0 should be returned as tuple of length 0")
expected_shape = (10,)
ints = cv.utils.generateVectorOfInt(expected_shape[0])
self.assertTrue(isinstance(ints, np.ndarray),
"Vector of integers should be returned as numpy array. Got: {}".format(type(ints)))
self.assertEqual(ints.dtype, np.int32, "Vector of integers has wrong elements type")
self.assertEqual(ints.shape, expected_shape, "Vector of integers has wrong shape.")
class SamplesFindFile(NewOpenCVTests):