#!/usr/bin/env python from __future__ import print_function import ctypes from functools import partial 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_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: cv.utils.testOverloadResolution(*args, **kwargs) 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)) # FIXIT: 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)) 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_parse_to_bool_convertible(self): try_to_convert = partial(self._try_to_convert, cv.utils.dumpBool) for convertible_true in (True, 1, 64, np.bool(1), np.int8(123), np.int16(11), np.int32(2), np.int64(1), np.bool_(3), np.bool8(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.float(2.3), 's', 'str', (1, 2), [1, 2], complex(1, 1), complex(imag=2), complex(1.1), np.array([1, 0], dtype=np.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], dtype=np.bool)): 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, np.float(4), float(3), 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([1, ], dtype=np.int), 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_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.float(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, float(32), np.float(32.45), 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=np.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], dtype=np.bool)): 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.float(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.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.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], dtype=np.bool)): 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('test1'), 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('test1'), 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) 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()