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Open Source Computer Vision Library
https://opencv.org/
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336 lines
17 KiB
336 lines
17 KiB
#!/usr/bin/env python |
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from __future__ import print_function |
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import ctypes |
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from functools import partial |
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import numpy as np |
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import cv2 as cv |
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from tests_common import NewOpenCVTests, unittest |
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def is_numeric(dtype): |
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return np.issubdtype(dtype, np.integer) or np.issubdtype(dtype, np.floating) |
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def get_limits(dtype): |
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if not is_numeric(dtype): |
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return None, None |
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if np.issubdtype(dtype, np.integer): |
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info = np.iinfo(dtype) |
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else: |
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info = np.finfo(dtype) |
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return info.min, info.max |
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def get_conversion_error_msg(value, expected, actual): |
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return 'Conversion "{}" of type "{}" failed\nExpected: "{}" vs Actual "{}"'.format( |
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value, type(value).__name__, expected, actual |
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) |
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def get_no_exception_msg(value): |
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return 'Exception is not risen for {} of type {}'.format(value, type(value).__name__) |
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class Bindings(NewOpenCVTests): |
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def test_inheritance(self): |
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bm = cv.StereoBM_create() |
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bm.getPreFilterCap() # from StereoBM |
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bm.getBlockSize() # from SteroMatcher |
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boost = cv.ml.Boost_create() |
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boost.getBoostType() # from ml::Boost |
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boost.getMaxDepth() # from ml::DTrees |
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boost.isClassifier() # from ml::StatModel |
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def test_redirectError(self): |
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try: |
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cv.imshow("", None) # This causes an assert |
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self.assertEqual("Dead code", 0) |
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except cv.error as _e: |
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pass |
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handler_called = [False] |
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def test_error_handler(status, func_name, err_msg, file_name, line): |
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handler_called[0] = True |
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cv.redirectError(test_error_handler) |
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try: |
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cv.imshow("", None) # This causes an assert |
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self.assertEqual("Dead code", 0) |
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except cv.error as _e: |
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self.assertEqual(handler_called[0], True) |
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pass |
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cv.redirectError(None) |
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try: |
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cv.imshow("", None) # This causes an assert |
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self.assertEqual("Dead code", 0) |
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except cv.error as _e: |
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pass |
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class Arguments(NewOpenCVTests): |
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def _try_to_convert(self, conversion, value): |
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try: |
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result = conversion(value).lower() |
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except Exception as e: |
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self.fail( |
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'{} "{}" is risen for conversion {} of type {}'.format( |
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type(e).__name__, e, value, type(value).__name__ |
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) |
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) |
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else: |
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return result |
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def test_InputArray(self): |
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res1 = cv.utils.dumpInputArray(None) |
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# self.assertEqual(res1, "InputArray: noArray()") # not supported |
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self.assertEqual(res1, "InputArray: empty()=true kind=0x00010000 flags=0x01010000 total(-1)=0 dims(-1)=0 size(-1)=0x0 type(-1)=CV_8UC1") |
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res2_1 = cv.utils.dumpInputArray((1, 2)) |
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self.assertEqual(res2_1, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=2 dims(-1)=2 size(-1)=1x2 type(-1)=CV_64FC1") |
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res2_2 = cv.utils.dumpInputArray(1.5) # Scalar(1.5, 1.5, 1.5, 1.5) |
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self.assertEqual(res2_2, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=4 dims(-1)=2 size(-1)=1x4 type(-1)=CV_64FC1") |
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a = np.array([[1, 2], [3, 4], [5, 6]]) |
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res3 = cv.utils.dumpInputArray(a) # 32SC1 |
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self.assertEqual(res3, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=6 dims(-1)=2 size(-1)=2x3 type(-1)=CV_32SC1") |
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a = np.array([[[1, 2], [3, 4], [5, 6]]], dtype='f') |
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res4 = cv.utils.dumpInputArray(a) # 32FC2 |
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self.assertEqual(res4, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=3 dims(-1)=2 size(-1)=3x1 type(-1)=CV_32FC2") |
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a = np.array([[[1, 2]], [[3, 4]], [[5, 6]]], dtype=float) |
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res5 = cv.utils.dumpInputArray(a) # 64FC2 |
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self.assertEqual(res5, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=3 dims(-1)=2 size(-1)=1x3 type(-1)=CV_64FC2") |
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def test_InputArrayOfArrays(self): |
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res1 = cv.utils.dumpInputArrayOfArrays(None) |
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# self.assertEqual(res1, "InputArray: noArray()") # not supported |
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self.assertEqual(res1, "InputArrayOfArrays: empty()=true kind=0x00050000 flags=0x01050000 total(-1)=0 dims(-1)=1 size(-1)=0x0") |
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res2_1 = cv.utils.dumpInputArrayOfArrays((1, 2)) # { Scalar:all(1), Scalar::all(2) } |
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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 type(0)=CV_64FC1") |
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res2_2 = cv.utils.dumpInputArrayOfArrays([1.5]) |
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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 type(0)=CV_64FC1") |
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a = np.array([[1, 2], [3, 4], [5, 6]]) |
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b = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) |
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res3 = cv.utils.dumpInputArrayOfArrays([a, b]) |
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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 type(0)=CV_32SC1") |
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c = np.array([[[1, 2], [3, 4], [5, 6]]], dtype='f') |
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res4 = cv.utils.dumpInputArrayOfArrays([c, a, b]) |
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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 type(0)=CV_32FC2") |
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def test_parse_to_bool_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpBool) |
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for convertible_true in (True, 1, 64, np.bool(1), np.int8(123), np.int16(11), np.int32(2), |
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np.int64(1), np.bool_(3), np.bool8(12)): |
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actual = try_to_convert(convertible_true) |
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self.assertEqual('bool: true', actual, |
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msg=get_conversion_error_msg(convertible_true, 'bool: true', actual)) |
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for convertible_false in (False, 0, np.uint8(0), np.bool_(0), np.int_(0)): |
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actual = try_to_convert(convertible_false) |
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self.assertEqual('bool: false', actual, |
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msg=get_conversion_error_msg(convertible_false, 'bool: false', actual)) |
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def test_parse_to_bool_not_convertible(self): |
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for not_convertible in (1.2, np.float(2.3), 's', 'str', (1, 2), [1, 2], complex(1, 1), |
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complex(imag=2), complex(1.1), np.array([1, 0], dtype=np.bool)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpBool(not_convertible) |
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def test_parse_to_bool_convertible_extra(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpBool) |
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_, max_size_t = get_limits(ctypes.c_size_t) |
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for convertible_true in (-1, max_size_t): |
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actual = try_to_convert(convertible_true) |
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self.assertEqual('bool: true', actual, |
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msg=get_conversion_error_msg(convertible_true, 'bool: true', actual)) |
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def test_parse_to_bool_not_convertible_extra(self): |
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for not_convertible in (np.array([False]), np.array([True], dtype=np.bool)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpBool(not_convertible) |
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def test_parse_to_int_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpInt) |
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min_int, max_int = get_limits(ctypes.c_int) |
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for convertible in (-10, -1, 2, int(43.2), np.uint8(15), np.int8(33), np.int16(-13), |
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np.int32(4), np.int64(345), (23), min_int, max_int, np.int_(33)): |
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expected = 'int: {0:d}'.format(convertible) |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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def test_parse_to_int_not_convertible(self): |
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min_int, max_int = get_limits(ctypes.c_int) |
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for not_convertible in (1.2, np.float(4), float(3), np.double(45), 's', 'str', |
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np.array([1, 2]), (1,), [1, 2], min_int - 1, max_int + 1, |
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complex(1, 1), complex(imag=2), complex(1.1)): |
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with self.assertRaises((TypeError, OverflowError, ValueError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpInt(not_convertible) |
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def test_parse_to_int_not_convertible_extra(self): |
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for not_convertible in (np.bool_(True), True, False, np.float32(2.3), |
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np.array([3, ], dtype=int), np.array([-2, ], dtype=np.int32), |
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np.array([1, ], dtype=np.int), np.array([11, ], dtype=np.uint8)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpInt(not_convertible) |
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def test_parse_to_size_t_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpSizeT) |
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_, max_uint = get_limits(ctypes.c_uint) |
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for convertible in (2, max_uint, (12), np.uint8(34), np.int8(12), np.int16(23), |
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np.int32(123), np.int64(344), np.uint64(3), np.uint16(2), np.uint32(5), |
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np.uint(44)): |
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expected = 'size_t: {0:d}'.format(convertible).lower() |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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def test_parse_to_size_t_not_convertible(self): |
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min_long, _ = get_limits(ctypes.c_long) |
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for not_convertible in (1.2, True, False, np.bool_(True), np.float(4), float(3), |
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np.double(45), 's', 'str', np.array([1, 2]), (1,), [1, 2], |
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np.float64(6), complex(1, 1), complex(imag=2), complex(1.1), |
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-1, min_long, np.int8(-35)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpSizeT(not_convertible) |
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def test_parse_to_size_t_convertible_extra(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpSizeT) |
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_, max_size_t = get_limits(ctypes.c_size_t) |
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for convertible in (max_size_t,): |
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expected = 'size_t: {0:d}'.format(convertible).lower() |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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def test_parse_to_size_t_not_convertible_extra(self): |
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for not_convertible in (np.bool_(True), True, False, np.array([123, ], dtype=np.uint8),): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpSizeT(not_convertible) |
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def test_parse_to_float_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpFloat) |
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min_float, max_float = get_limits(ctypes.c_float) |
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for convertible in (2, -13, 1.24, float(32), np.float(32.45), np.double(12.23), |
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np.float32(-12.3), np.float64(3.22), np.float_(-1.5), min_float, |
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max_float, np.inf, -np.inf, float('Inf'), -float('Inf'), |
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np.double(np.inf), np.double(-np.inf), np.double(float('Inf')), |
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np.double(-float('Inf'))): |
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expected = 'Float: {0:.2f}'.format(convertible).lower() |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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# Workaround for Windows NaN tests due to Visual C runtime |
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# special floating point values (indefinite NaN) |
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for nan in (float('NaN'), np.nan, np.float32(np.nan), np.double(np.nan), |
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np.double(float('NaN'))): |
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actual = try_to_convert(nan) |
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self.assertIn('nan', actual, msg="Can't convert nan of type {} to float. " |
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"Actual: {}".format(type(nan).__name__, actual)) |
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min_double, max_double = get_limits(ctypes.c_double) |
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for inf in (min_float * 10, max_float * 10, min_double, max_double): |
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expected = 'float: {}inf'.format('-' if inf < 0 else '') |
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actual = try_to_convert(inf) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(inf, expected, actual)) |
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def test_parse_to_float_not_convertible(self): |
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for not_convertible in ('s', 'str', (12,), [1, 2], np.array([1, 2], dtype=np.float), |
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np.array([1, 2], dtype=np.double), complex(1, 1), complex(imag=2), |
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complex(1.1)): |
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with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpFloat(not_convertible) |
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def test_parse_to_float_not_convertible_extra(self): |
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for not_convertible in (np.bool_(False), True, False, np.array([123, ], dtype=int), |
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np.array([1., ]), np.array([False]), |
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np.array([True], dtype=np.bool)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpFloat(not_convertible) |
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def test_parse_to_double_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpDouble) |
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min_float, max_float = get_limits(ctypes.c_float) |
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min_double, max_double = get_limits(ctypes.c_double) |
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for convertible in (2, -13, 1.24, np.float(32.45), float(2), np.double(12.23), |
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np.float32(-12.3), np.float64(3.22), np.float_(-1.5), min_float, |
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max_float, min_double, max_double, np.inf, -np.inf, float('Inf'), |
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-float('Inf'), np.double(np.inf), np.double(-np.inf), |
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np.double(float('Inf')), np.double(-float('Inf'))): |
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expected = 'Double: {0:.2f}'.format(convertible).lower() |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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# Workaround for Windows NaN tests due to Visual C runtime |
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# special floating point values (indefinite NaN) |
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for nan in (float('NaN'), np.nan, np.double(np.nan), |
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np.double(float('NaN'))): |
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actual = try_to_convert(nan) |
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self.assertIn('nan', actual, msg="Can't convert nan of type {} to double. " |
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"Actual: {}".format(type(nan).__name__, actual)) |
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def test_parse_to_double_not_convertible(self): |
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for not_convertible in ('s', 'str', (12,), [1, 2], np.array([1, 2], dtype=np.float), |
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np.array([1, 2], dtype=np.double), complex(1, 1), complex(imag=2), |
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complex(1.1)): |
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with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpDouble(not_convertible) |
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def test_parse_to_double_not_convertible_extra(self): |
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for not_convertible in (np.bool_(False), True, False, np.array([123, ], dtype=int), |
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np.array([1., ]), np.array([False]), |
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np.array([12.4], dtype=np.double), np.array([True], dtype=np.bool)): |
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with self.assertRaises((TypeError, OverflowError), |
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msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpDouble(not_convertible) |
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def test_parse_to_cstring_convertible(self): |
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try_to_convert = partial(self._try_to_convert, cv.utils.dumpCString) |
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for convertible in ('s', 'str', str(123), ('char'), np.str('test1'), np.str_('test2')): |
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expected = 'string: ' + convertible |
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actual = try_to_convert(convertible) |
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self.assertEqual(expected, actual, |
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msg=get_conversion_error_msg(convertible, expected, actual)) |
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def test_parse_to_cstring_not_convertible(self): |
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for not_convertible in ((12,), ('t', 'e', 's', 't'), np.array(['123', ]), |
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np.array(['t', 'e', 's', 't']), 1, -1.4, True, False, None): |
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with self.assertRaises((TypeError), msg=get_no_exception_msg(not_convertible)): |
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_ = cv.utils.dumpCString(not_convertible) |
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class SamplesFindFile(NewOpenCVTests): |
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def test_ExistedFile(self): |
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res = cv.samples.findFile('lena.jpg', False) |
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self.assertNotEqual(res, '') |
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def test_MissingFile(self): |
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res = cv.samples.findFile('non_existed.file', False) |
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self.assertEqual(res, '') |
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def test_MissingFileException(self): |
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try: |
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_res = cv.samples.findFile('non_existed.file', True) |
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self.assertEqual("Dead code", 0) |
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except cv.error as _e: |
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pass |
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if __name__ == '__main__': |
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NewOpenCVTests.bootstrap()
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