718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
639 lines
35 KiB
Python
639 lines
35 KiB
Python
#!/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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from collections import namedtuple
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import sys
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if sys.version_info[0] < 3:
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from collections import Sequence
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else:
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from collections.abc import Sequence
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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_raiseGeneralException(self):
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with self.assertRaises((cv.error,),
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msg='C++ exception is not propagated to Python in the right way') as cm:
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cv.utils.testRaiseGeneralException()
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self.assertEqual(str(cm.exception), 'exception text')
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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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def test_overload_resolution_can_choose_correct_overload(self):
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val = 123
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point = (51, 165)
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self.assertEqual(cv.utils.testOverloadResolution(val, point),
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'overload (int={}, point=(x={}, y={}))'.format(val, *point),
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"Can't select first overload if all arguments are provided as positional")
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self.assertEqual(cv.utils.testOverloadResolution(val, point=point),
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'overload (int={}, point=(x={}, y={}))'.format(val, *point),
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"Can't select first overload if one of the arguments are provided as keyword")
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self.assertEqual(cv.utils.testOverloadResolution(val),
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'overload (int={}, point=(x=42, y=24))'.format(val),
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"Can't select first overload if one of the arguments has default value")
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rect = (1, 5, 10, 23)
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self.assertEqual(cv.utils.testOverloadResolution(rect),
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'overload (rect=(x={}, y={}, w={}, h={}))'.format(*rect),
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"Can't select second overload if all arguments are provided")
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def test_overload_resolution_fails(self):
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def test_overload_resolution(msg, *args, **kwargs):
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no_exception_msg = 'Overload resolution failed without any exception for: "{}"'.format(msg)
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wrong_exception_msg = 'Overload resolution failed with wrong exception type for: "{}"'.format(msg)
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with self.assertRaises((cv.error, Exception), msg=no_exception_msg) as cm:
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res = cv.utils.testOverloadResolution(*args, **kwargs)
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self.fail("Unexpected result for {}: '{}'".format(msg, res))
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self.assertEqual(type(cm.exception), cv.error, wrong_exception_msg)
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test_overload_resolution('wrong second arg type (keyword arg)', 5, point=(1, 2, 3))
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test_overload_resolution('wrong second arg type', 5, 2)
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test_overload_resolution('wrong first arg', 3.4, (12, 21))
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test_overload_resolution('wrong first arg, no second arg', 4.5)
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test_overload_resolution('wrong args number for first overload', 3, (12, 21), 123)
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test_overload_resolution('wrong args number for second overload', (3, 12, 12, 1), (12, 21))
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# One of the common problems
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test_overload_resolution('rect with float coordinates', (4.5, 4, 2, 1))
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test_overload_resolution('rect with wrong number of coordinates', (4, 4, 1))
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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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a = np.zeros((2,3,4), dtype='f')
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res6 = cv.utils.dumpInputArray(a)
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self.assertEqual(res6, "InputArray: empty()=false kind=0x00010000 flags=0x01010000 total(-1)=6 dims(-1)=2 size(-1)=3x2 type(-1)=CV_32FC4")
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a = np.zeros((2,3,4,5), dtype='f')
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res7 = cv.utils.dumpInputArray(a)
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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")
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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")
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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")
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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")
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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")
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a = np.zeros((2,3,4), dtype='f')
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res5 = cv.utils.dumpInputArrayOfArrays([a, b])
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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")
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# TODO: fix conversion error
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#a = np.zeros((2,3,4,5), dtype='f')
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#res6 = cv.utils.dumpInputArray([a, b])
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#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]")
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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))
|
|
|
|
# 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)
|
|
|
|
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_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.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 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")
|
|
|
|
|
|
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()
|