#!/usr/bin/env python from __future__ import print_function import sys import ctypes from functools import partial from collections import namedtuple import sys if sys.version_info[0] < 3: from collections import Sequence else: from collections.abc import Sequence import numpy as np import cv2 as cv from tests_common import NewOpenCVTests, unittest def is_numeric(dtype): return np.issubdtype(dtype, np.integer) or np.issubdtype(dtype, np.floating) def get_limits(dtype): if not is_numeric(dtype): return None, None if np.issubdtype(dtype, np.integer): info = np.iinfo(dtype) else: info = np.finfo(dtype) return info.min, info.max def get_conversion_error_msg(value, expected, actual): return 'Conversion "{}" of type "{}" failed\nExpected: "{}" vs Actual "{}"'.format( value, type(value).__name__, expected, actual ) def get_no_exception_msg(value): return 'Exception is not risen for {} of type {}'.format(value, type(value).__name__) class Bindings(NewOpenCVTests): def test_inheritance(self): bm = cv.StereoBM_create() bm.getPreFilterCap() # from StereoBM bm.getBlockSize() # from SteroMatcher boost = cv.ml.Boost_create() boost.getBoostType() # from ml::Boost boost.getMaxDepth() # from ml::DTrees boost.isClassifier() # from ml::StatModel def test_raiseGeneralException(self): with self.assertRaises((cv.error,), msg='C++ exception is not propagated to Python in the right way') as cm: cv.utils.testRaiseGeneralException() self.assertEqual(str(cm.exception), 'exception text') def test_redirectError(self): try: cv.imshow("", None) # This causes an assert self.assertEqual("Dead code", 0) except cv.error as _e: pass handler_called = [False] def test_error_handler(status, func_name, err_msg, file_name, line): handler_called[0] = True cv.redirectError(test_error_handler) try: cv.imshow("", None) # This causes an assert self.assertEqual("Dead code", 0) except cv.error as _e: self.assertEqual(handler_called[0], True) pass cv.redirectError(None) try: cv.imshow("", None) # This causes an assert self.assertEqual("Dead code", 0) except cv.error as _e: pass def test_overload_resolution_can_choose_correct_overload(self): val = 123 point = (51, 165) self.assertEqual(cv.utils.testOverloadResolution(val, point), 'overload (int={}, point=(x={}, y={}))'.format(val, *point), "Can't select first overload if all arguments are provided as positional") self.assertEqual(cv.utils.testOverloadResolution(val, point=point), 'overload (int={}, point=(x={}, y={}))'.format(val, *point), "Can't select first overload if one of the arguments are provided as keyword") self.assertEqual(cv.utils.testOverloadResolution(val), 'overload (int={}, point=(x=42, y=24))'.format(val), "Can't select first overload if one of the arguments has default value") rect = (1, 5, 10, 23) self.assertEqual(cv.utils.testOverloadResolution(rect), 'overload (rect=(x={}, y={}, w={}, h={}))'.format(*rect), "Can't select second overload if all arguments are provided") def test_overload_resolution_fails(self): def test_overload_resolution(msg, *args, **kwargs): no_exception_msg = 'Overload resolution failed without any exception for: "{}"'.format(msg) wrong_exception_msg = 'Overload resolution failed with wrong exception type for: "{}"'.format(msg) with self.assertRaises((cv.error, Exception), msg=no_exception_msg) as cm: res = cv.utils.testOverloadResolution(*args, **kwargs) self.fail("Unexpected result for {}: '{}'".format(msg, res)) self.assertEqual(type(cm.exception), cv.error, wrong_exception_msg) test_overload_resolution('wrong second arg type (keyword arg)', 5, point=(1, 2, 3)) test_overload_resolution('wrong second arg type', 5, 2) test_overload_resolution('wrong first arg', 3.4, (12, 21)) test_overload_resolution('wrong first arg, no second arg', 4.5) test_overload_resolution('wrong args number for first overload', 3, (12, 21), 123) test_overload_resolution('wrong args number for second overload', (3, 12, 12, 1), (12, 21)) # One of the common problems test_overload_resolution('rect with float coordinates', (4.5, 4, 2, 1)) test_overload_resolution('rect with wrong number of coordinates', (4, 4, 1)) def test_properties_with_reserved_keywords_names_are_transformed(self): obj = cv.utils.ClassWithKeywordProperties(except_arg=23) self.assertTrue(hasattr(obj, "lambda_"), msg="Class doesn't have RW property with converted name") try: obj.lambda_ = 32 except Exception as e: self.fail("Failed to set value to RW property. Error: {}".format(e)) self.assertTrue(hasattr(obj, "except_"), msg="Class doesn't have readonly property with converted name") self.assertEqual(obj.except_, 23, msg="Can't access readonly property value") with self.assertRaises(AttributeError): obj.except_ = 32 def test_maketype(self): data = { cv.CV_8UC3: [cv.CV_8U, 3, cv.CV_8UC], cv.CV_16SC1: [cv.CV_16S, 1, cv.CV_16SC], cv.CV_32FC4: [cv.CV_32F, 4, cv.CV_32FC], cv.CV_64FC2: [cv.CV_64F, 2, cv.CV_64FC], cv.CV_8SC4: [cv.CV_8S, 4, cv.CV_8SC], cv.CV_16UC2: [cv.CV_16U, 2, cv.CV_16UC], cv.CV_32SC1: [cv.CV_32S, 1, cv.CV_32SC], cv.CV_16FC3: [cv.CV_16F, 3, cv.CV_16FC], } for ref, (depth, channels, func) in data.items(): self.assertEqual(ref, cv.CV_MAKETYPE(depth, channels)) self.assertEqual(ref, func(channels)) class Arguments(NewOpenCVTests): def _try_to_convert(self, conversion, value): try: result = conversion(value).lower() except Exception as e: self.fail( '{} "{}" is risen for conversion {} of type {}'.format( type(e).__name__, e, value, type(value).__name__ ) ) else: return result def test_InputArray(self): res1 = cv.utils.dumpInputArray(None) # self.assertEqual(res1, "InputArray: noArray()") # not supported self.assertEqual(res1, "InputArray: empty()=true kind=0x00010000 flags=0x01010000 total(-1)=0 dims(-1)=0 size(-1)=0x0 type(-1)=CV_8UC1") res2_1 = cv.utils.dumpInputArray((1, 2)) self.assertEqual(res2_1, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=2 dims(-1)=2 size(-1)=1x2 type(-1)=CV_64FC1") res2_2 = cv.utils.dumpInputArray(1.5) # Scalar(1.5, 1.5, 1.5, 1.5) self.assertEqual(res2_2, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=4 dims(-1)=2 size(-1)=1x4 type(-1)=CV_64FC1") a = np.array([[1, 2], [3, 4], [5, 6]]) res3 = cv.utils.dumpInputArray(a) # 32SC1 self.assertEqual(res3, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=6 dims(-1)=2 size(-1)=2x3 type(-1)=CV_32SC1") a = np.array([[[1, 2], [3, 4], [5, 6]]], dtype='f') res4 = cv.utils.dumpInputArray(a) # 32FC2 self.assertEqual(res4, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=3 dims(-1)=2 size(-1)=3x1 type(-1)=CV_32FC2") a = np.array([[[1, 2]], [[3, 4]], [[5, 6]]], dtype=float) res5 = cv.utils.dumpInputArray(a) # 64FC2 self.assertEqual(res5, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=3 dims(-1)=2 size(-1)=1x3 type(-1)=CV_64FC2") a = np.zeros((2,3,4), dtype='f') res6 = cv.utils.dumpInputArray(a) self.assertEqual(res6, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=6 dims(-1)=2 size(-1)=3x2 type(-1)=CV_32FC4") a = np.zeros((2,3,4,5), dtype='f') res7 = cv.utils.dumpInputArray(a) self.assertEqual(res7, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=120 dims(-1)=4 size(-1)=[2 3 4 5] type(-1)=CV_32FC1") def test_InputArrayOfArrays(self): res1 = cv.utils.dumpInputArrayOfArrays(None) # self.assertEqual(res1, "InputArray: noArray()") # not supported self.assertEqual(res1, "InputArrayOfArrays: empty()=true kind=0x00050000 flags=0x01050000 total(-1)=0 dims(-1)=1 size(-1)=0x0") res2_1 = cv.utils.dumpInputArrayOfArrays((1, 2)) # { Scalar:all(1), Scalar::all(2) } self.assertEqual(res2_1, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=2 dims(-1)=1 size(-1)=2x1 type(0)=CV_64FC1 dims(0)=2 size(0)=1x4") res2_2 = cv.utils.dumpInputArrayOfArrays([1.5]) self.assertEqual(res2_2, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=1 dims(-1)=1 size(-1)=1x1 type(0)=CV_64FC1 dims(0)=2 size(0)=1x4") a = np.array([[1, 2], [3, 4], [5, 6]]) b = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) res3 = cv.utils.dumpInputArrayOfArrays([a, b]) self.assertEqual(res3, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=2 dims(-1)=1 size(-1)=2x1 type(0)=CV_32SC1 dims(0)=2 size(0)=2x3") c = np.array([[[1, 2], [3, 4], [5, 6]]], dtype='f') res4 = cv.utils.dumpInputArrayOfArrays([c, a, b]) self.assertEqual(res4, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=3 dims(-1)=1 size(-1)=3x1 type(0)=CV_32FC2 dims(0)=2 size(0)=3x1") a = np.zeros((2,3,4), dtype='f') res5 = cv.utils.dumpInputArrayOfArrays([a, b]) self.assertEqual(res5, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=2 dims(-1)=1 size(-1)=2x1 type(0)=CV_32FC4 dims(0)=2 size(0)=3x2") # TODO: fix conversion error #a = np.zeros((2,3,4,5), dtype='f') #res6 = cv.utils.dumpInputArray([a, b]) #self.assertEqual(res6, "InputArrayOfArrays: empty()=false kind=0x00050000 flags=0x01050000 total(-1)=2 dims(-1)=1 size(-1)=2x1 type(0)=CV_32FC1 dims(0)=4 size(0)=[2 3 4 5]") def test_unsupported_numpy_data_types_string_description(self): for dtype in (object, str, np.complex128): test_array = np.zeros((4, 4, 3), dtype=dtype) msg = ".*type = {} is not supported".format(test_array.dtype) if sys.version_info[0] < 3: self.assertRaisesRegexp( Exception, msg, cv.utils.dumpInputArray, test_array ) else: self.assertRaisesRegex( Exception, msg, cv.utils.dumpInputArray, test_array ) def test_numpy_writeable_flag_is_preserved(self): array = np.zeros((10, 10, 1), dtype=np.uint8) array.setflags(write=False) with self.assertRaises(Exception): cv.rectangle(array, (0, 0), (5, 5), (255), 2) def test_20968(self): pixel = np.uint8([[[40, 50, 200]]]) _ = cv.cvtColor(pixel, cv.COLOR_RGB2BGR) # should not raise exception def test_parse_to_bool_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpBool) for convertible_true in (True, 1, 64, np.int8(123), np.int16(11), np.int32(2), np.int64(1), np.bool_(12)): actual = try_to_convert(convertible_true) self.assertEqual('bool: true', actual, msg=get_conversion_error_msg(convertible_true, 'bool: true', actual)) for convertible_false in (False, 0, np.uint8(0), np.bool_(0), np.int_(0)): actual = try_to_convert(convertible_false) self.assertEqual('bool: false', actual, msg=get_conversion_error_msg(convertible_false, 'bool: false', actual)) def test_parse_to_bool_not_convertible(self): for not_convertible in (1.2, np.float32(2.3), 's', 'str', (1, 2), [1, 2], complex(1, 1), complex(imag=2), complex(1.1), np.array([1, 0], dtype=bool)): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpBool(not_convertible) def test_parse_to_bool_convertible_extra(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpBool) _, max_size_t = get_limits(ctypes.c_size_t) for convertible_true in (-1, max_size_t): actual = try_to_convert(convertible_true) self.assertEqual('bool: true', actual, msg=get_conversion_error_msg(convertible_true, 'bool: true', actual)) def test_parse_to_bool_not_convertible_extra(self): for not_convertible in (np.array([False]), np.array([True])): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpBool(not_convertible) def test_parse_to_int_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpInt) min_int, max_int = get_limits(ctypes.c_int) for convertible in (-10, -1, 2, int(43.2), np.uint8(15), np.int8(33), np.int16(-13), np.int32(4), np.int64(345), (23), min_int, max_int, np.int_(33)): expected = 'int: {0:d}'.format(convertible) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_int_not_convertible(self): min_int, max_int = get_limits(ctypes.c_int) for not_convertible in (1.2, float(3), np.float32(4), np.double(45), 's', 'str', np.array([1, 2]), (1,), [1, 2], min_int - 1, max_int + 1, complex(1, 1), complex(imag=2), complex(1.1)): with self.assertRaises((TypeError, OverflowError, ValueError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpInt(not_convertible) def test_parse_to_int_not_convertible_extra(self): for not_convertible in (np.bool_(True), True, False, np.float32(2.3), np.array([3, ], dtype=int), np.array([-2, ], dtype=np.int32), np.array([11, ], dtype=np.uint8)): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpInt(not_convertible) def test_parse_to_int64_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpInt64) min_int64, max_int64 = get_limits(ctypes.c_longlong) for convertible in (-10, -1, 2, int(43.2), np.uint8(15), np.int8(33), np.int16(-13), np.int32(4), np.int64(345), (23), min_int64, max_int64, np.int_(33)): expected = 'int64: {0:d}'.format(convertible) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_int64_not_convertible(self): min_int64, max_int64 = get_limits(ctypes.c_longlong) for not_convertible in (1.2, np.float32(4), float(3), np.double(45), 's', 'str', np.array([1, 2]), (1,), [1, 2], min_int64 - 1, max_int64 + 1, complex(1, 1), complex(imag=2), complex(1.1), np.bool_(True), True, False, np.float32(2.3), np.array([3, ], dtype=int), np.array([-2, ], dtype=np.int32), np.array([11, ], dtype=np.uint8)): with self.assertRaises((TypeError, OverflowError, ValueError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpInt64(not_convertible) def test_parse_to_size_t_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpSizeT) _, max_uint = get_limits(ctypes.c_uint) for convertible in (2, max_uint, (12), np.uint8(34), np.int8(12), np.int16(23), np.int32(123), np.int64(344), np.uint64(3), np.uint16(2), np.uint32(5), np.uint(44)): expected = 'size_t: {0:d}'.format(convertible).lower() actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_size_t_not_convertible(self): min_long, _ = get_limits(ctypes.c_long) for not_convertible in (1.2, True, False, np.bool_(True), np.float32(4), float(3), np.double(45), 's', 'str', np.array([1, 2]), (1,), [1, 2], np.float64(6), complex(1, 1), complex(imag=2), complex(1.1), -1, min_long, np.int8(-35)): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpSizeT(not_convertible) def test_parse_to_size_t_convertible_extra(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpSizeT) _, max_size_t = get_limits(ctypes.c_size_t) for convertible in (max_size_t,): expected = 'size_t: {0:d}'.format(convertible).lower() actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_size_t_not_convertible_extra(self): for not_convertible in (np.bool_(True), True, False, np.array([123, ], dtype=np.uint8),): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpSizeT(not_convertible) def test_parse_to_float_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpFloat) min_float, max_float = get_limits(ctypes.c_float) for convertible in (2, -13, 1.24, np.float32(32.45), float(32), np.double(12.23), np.float32(-12.3), np.float64(3.22), np.float_(-1.5), min_float, max_float, np.inf, -np.inf, float('Inf'), -float('Inf'), np.double(np.inf), np.double(-np.inf), np.double(float('Inf')), np.double(-float('Inf'))): expected = 'Float: {0:.2f}'.format(convertible).lower() actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) # Workaround for Windows NaN tests due to Visual C runtime # special floating point values (indefinite NaN) for nan in (float('NaN'), np.nan, np.float32(np.nan), np.double(np.nan), np.double(float('NaN'))): actual = try_to_convert(nan) self.assertIn('nan', actual, msg="Can't convert nan of type {} to float. " "Actual: {}".format(type(nan).__name__, actual)) min_double, max_double = get_limits(ctypes.c_double) for inf in (min_float * 10, max_float * 10, min_double, max_double): expected = 'float: {}inf'.format('-' if inf < 0 else '') actual = try_to_convert(inf) self.assertEqual(expected, actual, msg=get_conversion_error_msg(inf, expected, actual)) def test_parse_to_float_not_convertible(self): for not_convertible in ('s', 'str', (12,), [1, 2], np.array([1, 2], dtype=float), np.array([1, 2], dtype=np.double), complex(1, 1), complex(imag=2), complex(1.1)): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpFloat(not_convertible) def test_parse_to_float_not_convertible_extra(self): for not_convertible in (np.bool_(False), True, False, np.array([123, ], dtype=int), np.array([1., ]), np.array([False]), np.array([True])): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpFloat(not_convertible) def test_parse_to_double_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpDouble) min_float, max_float = get_limits(ctypes.c_float) min_double, max_double = get_limits(ctypes.c_double) for convertible in (2, -13, 1.24, np.float32(32.45), float(2), np.double(12.23), np.float32(-12.3), np.float64(3.22), np.float_(-1.5), min_float, max_float, min_double, max_double, np.inf, -np.inf, float('Inf'), -float('Inf'), np.double(np.inf), np.double(-np.inf), np.double(float('Inf')), np.double(-float('Inf'))): expected = 'Double: {0:.2f}'.format(convertible).lower() actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) # Workaround for Windows NaN tests due to Visual C runtime # special floating point values (indefinite NaN) for nan in (float('NaN'), np.nan, np.double(np.nan), np.double(float('NaN'))): actual = try_to_convert(nan) self.assertIn('nan', actual, msg="Can't convert nan of type {} to double. " "Actual: {}".format(type(nan).__name__, actual)) def test_parse_to_double_not_convertible(self): for not_convertible in ('s', 'str', (12,), [1, 2], np.array([1, 2], dtype=np.float32), np.array([1, 2], dtype=np.double), complex(1, 1), complex(imag=2), complex(1.1)): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpDouble(not_convertible) def test_parse_to_double_not_convertible_extra(self): for not_convertible in (np.bool_(False), True, False, np.array([123, ], dtype=int), np.array([1., ]), np.array([False]), np.array([12.4], dtype=np.double), np.array([True])): with self.assertRaises((TypeError, OverflowError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpDouble(not_convertible) def test_parse_to_cstring_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpCString) for convertible in ('', 's', 'str', str(123), ('char'), np.str_('test2')): expected = 'string: ' + convertible actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_cstring_not_convertible(self): for not_convertible in ((12,), ('t', 'e', 's', 't'), np.array(['123', ]), np.array(['t', 'e', 's', 't']), 1, -1.4, True, False, None): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpCString(not_convertible) def test_parse_to_string_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpString) for convertible in (None, '', 's', 'str', str(123), np.str_('test2')): expected = 'string: ' + (convertible if convertible else '') actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_string_not_convertible(self): for not_convertible in ((12,), ('t', 'e', 's', 't'), np.array(['123', ]), np.array(['t', 'e', 's', 't']), 1, True, False): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpString(not_convertible) def test_parse_to_rect_convertible(self): Rect = namedtuple('Rect', ('x', 'y', 'w', 'h')) try_to_convert = partial(self._try_to_convert, cv.utils.dumpRect) for convertible in ((1, 2, 4, 5), [5, 3, 10, 20], np.array([10, 20, 23, 10]), Rect(10, 30, 40, 55), tuple(np.array([40, 20, 24, 20])), list(np.array([20, 40, 30, 35]))): expected = 'rect: (x={}, y={}, w={}, h={})'.format(*convertible) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_rect_not_convertible(self): for not_convertible in (np.empty(shape=(4, 1)), (), [], np.array([]), (12, ), [3, 4, 5, 10, 123], {1: 2, 3:4, 5:10, 6:30}, '1234', np.array([1, 2, 3, 4], dtype=np.float32), np.array([[1, 2], [3, 4], [5, 6], [6, 8]]), (1, 2, 5, 1.5)): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpRect(not_convertible) def test_parse_to_rotated_rect_convertible(self): RotatedRect = namedtuple('RotatedRect', ('center', 'size', 'angle')) try_to_convert = partial(self._try_to_convert, cv.utils.dumpRotatedRect) for convertible in (((2.5, 2.5), (10., 20.), 12.5), [[1.5, 10.5], (12.5, 51.5), 10], RotatedRect((10, 40), np.array([10.5, 20.5]), 5), np.array([[10, 6], [50, 50], 5.5], dtype=object)): center, size, angle = convertible expected = 'rotated_rect: (c_x={:.6f}, c_y={:.6f}, w={:.6f},' \ ' h={:.6f}, a={:.6f})'.format(center[0], center[1], size[0], size[1], angle) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_wrap_rotated_rect(self): center = (34.5, 52.) size = (565.0, 140.0) angle = -177.5 rect1 = cv.RotatedRect(center, size, angle) self.assertEqual(rect1.center, center) self.assertEqual(rect1.size, size) self.assertEqual(rect1.angle, angle) pts = [[ 319.7845, -5.6109037], [ 313.6778, 134.25586], [-250.78448, 109.6109], [-244.6778, -30.25586]] self.assertLess(np.max(np.abs(rect1.points() - pts)), 1e-4) rect2 = cv.RotatedRect(pts[0], pts[1], pts[2]) _, inter_pts = cv.rotatedRectangleIntersection(rect1, rect2) self.assertLess(np.max(np.abs(inter_pts.reshape(-1, 2) - pts)), 1e-4) def test_parse_to_rotated_rect_not_convertible(self): for not_convertible in ([], (), np.array([]), (123, (45, 34), 1), {1: 2, 3: 4}, 123, np.array([[123, 123, 14], [1, 3], 56], dtype=object), '123'): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpRotatedRect(not_convertible) def test_parse_to_term_criteria_convertible(self): TermCriteria = namedtuple('TermCriteria', ('type', 'max_count', 'epsilon')) try_to_convert = partial(self._try_to_convert, cv.utils.dumpTermCriteria) for convertible in ((1, 10, 1e-3), [2, 30, 1e-1], np.array([10, 20, 0.5], dtype=object), TermCriteria(0, 5, 0.1)): expected = 'term_criteria: (type={}, max_count={}, epsilon={:.6f}'.format(*convertible) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_term_criteria_not_convertible(self): for not_convertible in ([], (), np.array([]), [1, 4], (10,), (1.5, 34, 0.1), {1: 5, 3: 5, 10: 10}, '145'): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpTermCriteria(not_convertible) def test_parse_to_range_convertible_to_all(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpRange) for convertible in ((), [], np.array([])): expected = 'range: all' actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_range_convertible(self): Range = namedtuple('Range', ('start', 'end')) try_to_convert = partial(self._try_to_convert, cv.utils.dumpRange) for convertible in ((10, 20), [-1, 3], np.array([10, 24]), Range(-4, 6)): expected = 'range: (s={}, e={})'.format(*convertible) actual = try_to_convert(convertible) self.assertEqual(expected, actual, msg=get_conversion_error_msg(convertible, expected, actual)) def test_parse_to_range_not_convertible(self): for not_convertible in ((1, ), [40, ], np.array([1, 4, 6]), {'a': 1, 'b': 40}, (1.5, 13.5), [3, 6.7], np.array([6.3, 2.1]), '14, 4'): with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): _ = cv.utils.dumpRange(not_convertible) def test_reserved_keywords_are_transformed(self): default_lambda_value = 2 default_from_value = 3 format_str = "arg={}, lambda={}, from={}" self.assertEqual( cv.utils.testReservedKeywordConversion(20), format_str.format(20, default_lambda_value, default_from_value) ) self.assertEqual( cv.utils.testReservedKeywordConversion(10, lambda_=10), format_str.format(10, 10, default_from_value) ) self.assertEqual( cv.utils.testReservedKeywordConversion(10, from_=10), format_str.format(10, default_lambda_value, 10) ) self.assertEqual( 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.float32).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=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.float32), 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=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), 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.float32).reshape(3, 4) for not_convertible in (((1, 2, 3, 4), (10.5, -20, 30.1, 10)), arr, [[5, 3, 1, 4], []], ((float(4), np.uint8(10), 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.") def test_result_rotated_rect_issue_20930(self): rr = cv.utils.testRotatedRect(10, 20, 100, 200, 45) self.assertTrue(isinstance(rr, tuple), msg=type(rr)) self.assertEqual(len(rr), 3) rrv = cv.utils.testRotatedRectVector(10, 20, 100, 200, 45) self.assertTrue(isinstance(rrv, tuple), msg=type(rrv)) self.assertEqual(len(rrv), 10) rr = rrv[0] self.assertTrue(isinstance(rr, tuple), msg=type(rrv)) self.assertEqual(len(rr), 3) def test_nested_function_availability(self): self.assertTrue(hasattr(cv.utils, "nested"), msg="Module is not generated for nested namespace") self.assertTrue(hasattr(cv.utils.nested, "testEchoBooleanFunction"), msg="Function in nested module is not available") if sys.version_info[0] < 3: # Nested submodule is managed only by the global submodules dictionary # and parent native module expected_ref_count = 2 else: # Nested submodule is managed by the global submodules dictionary, # parent native module and Python part of the submodule expected_ref_count = 3 # `getrefcount` temporary increases reference counter by 1 actual_ref_count = sys.getrefcount(cv.utils.nested) - 1 self.assertEqual(actual_ref_count, expected_ref_count, msg="Nested submodule reference counter has wrong value\n" "Expected: {}. Actual: {}".format(expected_ref_count, actual_ref_count)) for flag in (True, False): self.assertEqual(flag, cv.utils.nested.testEchoBooleanFunction(flag), msg="Function in nested module returns wrong result") def test_class_from_submodule_has_global_alias(self): self.assertTrue(hasattr(cv.ml, "Boost"), msg="Class is not registered in the submodule") self.assertTrue(hasattr(cv, "ml_Boost"), msg="Class from submodule doesn't have alias in the " "global module") self.assertEqual(cv.ml.Boost, cv.ml_Boost, msg="Classes from submodules and global module don't refer " "to the same type") def test_inner_class_has_global_alias(self): self.assertTrue(hasattr(cv.SimpleBlobDetector, "Params"), msg="Class is not registered as inner class") self.assertTrue(hasattr(cv, "SimpleBlobDetector_Params"), msg="Inner class doesn't have alias in the global module") self.assertEqual(cv.SimpleBlobDetector.Params, cv.SimpleBlobDetector_Params, msg="Inner class and class in global module don't refer " "to the same type") def test_export_class_with_different_name(self): self.assertTrue(hasattr(cv.utils.nested, "ExportClassName"), msg="Class with export alias is not registered in the submodule") self.assertTrue(hasattr(cv, "utils_nested_ExportClassName"), msg="Class with export alias doesn't have alias in the " "global module") self.assertEqual(cv.utils.nested.ExportClassName.originalName(), "OriginalClassName") instance = cv.utils.nested.ExportClassName.create() self.assertTrue(isinstance(instance, cv.utils.nested.ExportClassName), msg="Factory function returns wrong class instance: {}".format(type(instance))) self.assertTrue(hasattr(cv.utils.nested, "ExportClassName_create"), msg="Factory function should have alias in the same module as the class") # self.assertFalse(hasattr(cv.utils.nested, "OriginalClassName_create"), # msg="Factory function should not be registered with original class name, "\ # "when class has different export name") def test_export_inner_class_of_class_exported_with_different_name(self): if not hasattr(cv.utils.nested, "ExportClassName"): raise unittest.SkipTest( "Outer class with export alias is not registered in the submodule") self.assertTrue(hasattr(cv.utils.nested.ExportClassName, "Params"), msg="Inner class with export alias is not registered in " "the outer class") self.assertTrue(hasattr(cv, "utils_nested_ExportClassName_Params"), msg="Inner class with export alias is not registered in " "global module") params = cv.utils.nested.ExportClassName.Params() params.int_value = 45 params.float_value = 4.5 instance = cv.utils.nested.ExportClassName.create(params) self.assertTrue(isinstance(instance, cv.utils.nested.ExportClassName), msg="Factory function returns wrong class instance: {}".format(type(instance))) self.assertEqual( params.int_value, instance.getIntParam(), msg="Class initialized with wrong integer parameter. Expected: {}. Actual: {}".format( params.int_value, instance.getIntParam() ) ) self.assertEqual( params.float_value, instance.getFloatParam(), msg="Class initialized with wrong integer parameter. Expected: {}. Actual: {}".format( params.float_value, instance.getFloatParam() ) ) def test_named_arguments_without_parameters(self): src = np.ones((5, 5, 3), dtype=np.uint8) arguments_dump, src_copy = cv.utils.copyMatAndDumpNamedArguments(src) np.testing.assert_equal(src, src_copy) self.assertEqual(arguments_dump, 'lambda=-1, sigma=0.0') def test_named_arguments_without_output_argument(self): src = np.zeros((2, 2, 3), dtype=np.uint8) arguments_dump, src_copy = cv.utils.copyMatAndDumpNamedArguments( src, lambda_=15, sigma=3.5 ) np.testing.assert_equal(src, src_copy) self.assertEqual(arguments_dump, 'lambda=15, sigma=3.5') def test_named_arguments_with_output_argument(self): src = np.zeros((3, 3, 3), dtype=np.uint8) dst = np.ones_like(src) arguments_dump, src_copy = cv.utils.copyMatAndDumpNamedArguments( src, dst, lambda_=25, sigma=5.5 ) np.testing.assert_equal(src, src_copy) np.testing.assert_equal(dst, src_copy) self.assertEqual(arguments_dump, 'lambda=25, sigma=5.5') class CanUsePurePythonModuleFunction(NewOpenCVTests): def test_can_get_ocv_version(self): import sys if sys.version_info[0] < 3: raise unittest.SkipTest('Python 2.x is not supported') self.assertEqual(cv.misc.get_ocv_version(), cv.__version__, "Can't get package version using Python misc module") def test_native_method_can_be_patched(self): import sys if sys.version_info[0] < 3: raise unittest.SkipTest('Python 2.x is not supported') res = cv.utils.testOverwriteNativeMethod(10) self.assertTrue(isinstance(res, Sequence), msg="Overwritten method should return sequence. " "Got: {} of type {}".format(res, type(res))) self.assertSequenceEqual(res, (11, 10), msg="Failed to overwrite native method") res = cv.utils._native.testOverwriteNativeMethod(123) self.assertEqual(res, 123, msg="Failed to call native method implementation") def test_default_matx_argument(self): res = cv.utils.dumpVec2i() self.assertEqual(res, "Vec2i(42, 24)", msg="Default argument is not properly handled") res = cv.utils.dumpVec2i((12, 21)) self.assertEqual(res, "Vec2i(12, 21)") class SamplesFindFile(NewOpenCVTests): def test_ExistedFile(self): res = cv.samples.findFile('lena.jpg', False) self.assertNotEqual(res, '') def test_MissingFile(self): res = cv.samples.findFile('non_existed.file', False) self.assertEqual(res, '') def test_MissingFileException(self): try: _res = cv.samples.findFile('non_existed.file', True) self.assertEqual("Dead code", 0) except cv.error as _e: pass if __name__ == '__main__': NewOpenCVTests.bootstrap()