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Merge pull request #15915 from VadimLevin:dev/norm_fix

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Fix implicit conversion from array to scalar in python bindings

* Fix wrong conversion behavior for primitive types

  - Introduce ArgTypeInfo namedtuple instead of plain tuple.
    If strict conversion parameter for type is set to true, it is
    handled like object argument in PyArg_ParseTupleAndKeywords and
    converted to concrete type with the appropriate pyopencv_to function
    call.
  - Remove deadcode and unused variables.
  - Fix implicit conversion from numpy array with 1 element to scalar
  - Fix narrowing conversion to size_t type.

* Fix wrong conversion behavior for primitive types

  - Introduce ArgTypeInfo namedtuple instead of plain tuple.
    If strict conversion parameter for type is set to true, it is
    handled like object argument in PyArg_ParseTupleAndKeywords and
    converted to concrete type with the appropriate pyopencv_to function
    call.
  - Remove deadcode and unused variables.
  - Fix implicit conversion from numpy array with 1 element to scalar
  - Fix narrowing conversion to size_t type.·
  - Enable tests with wrong conversion behavior
  - Restrict passing None as value
  - Restrict bool to integer/floating types conversion

* Add PyIntType support for Python 2

* Remove possible narrowing conversion of size_t

* Bindings conversion update

  - Remove unused macro
  - Add better conversion for types to numpy types descriptors
  - Add argument name to fail messages
  - NoneType treated as a valid argument. Better handling will be added
    as a standalone patch

* Add descriptor specialization for size_t

* Add check for signed to unsigned integer conversion safety

  - If signed integer is positive it can be safely converted
    to unsigned
  - Add check for plain python 2 objects
  - Add check for numpy scalars
  - Add simple type_traits implementation for better code style

* Resolve type "overflow" false negative in safe casting check

 - Move type_traits to separate header

* Add copyright message to type_traits.hpp

* Limit conversion scope for integral numpy types

  - Made canBeSafelyCasted specialized only for size_t, so
    type_traits header became unused and was removed.
  - Added clarification about descriptor pointer
This commit is contained in:
Vadim Levin
2020-01-13 18:11:34 +03:00
committed by Alexander Alekhin
parent 4cc458eb10
commit 31289d2f32
4 changed files with 532 additions and 73 deletions
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modules/python/test/test_misc.py
+10 -15
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@@ -136,13 +136,12 @@ class Arguments(NewOpenCVTests):
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), None,
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)
@unittest.skip('Wrong conversion behavior')
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)
@@ -151,7 +150,6 @@ class Arguments(NewOpenCVTests):
self.assertEqual('bool: true', actual,
msg=get_conversion_error_msg(convertible_true, 'bool: true', actual))
@unittest.skip('Wrong conversion behavior')
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),
@@ -172,12 +170,11 @@ class Arguments(NewOpenCVTests):
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), None):
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)
@unittest.skip('Wrong conversion behavior')
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),
@@ -189,7 +186,7 @@ class Arguments(NewOpenCVTests):
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, True, False, max_uint, (12), np.uint8(34), np.int8(12), np.int16(23),
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()
@@ -198,14 +195,15 @@ class Arguments(NewOpenCVTests):
msg=get_conversion_error_msg(convertible, expected, actual))
def test_parse_to_size_t_not_convertible(self):
for not_convertible in (1.2, 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), None):
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)
@unittest.skip('Wrong conversion behavior')
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)
@@ -215,7 +213,6 @@ class Arguments(NewOpenCVTests):
self.assertEqual(expected, actual,
msg=get_conversion_error_msg(convertible, expected, actual))
@unittest.skip('Wrong conversion behavior')
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),
@@ -251,13 +248,12 @@ class Arguments(NewOpenCVTests):
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], None, np.array([1, 2], dtype=np.float),
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)
@unittest.skip('Wrong conversion behavior')
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]),
@@ -289,13 +285,12 @@ class Arguments(NewOpenCVTests):
"Actual: {}".format(type(nan).__name__, actual))
def test_parse_to_double_not_convertible(self):
for not_convertible in ('s', 'str', (12,), [1, 2], None, np.array([1, 2], dtype=np.float),
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)
@unittest.skip('Wrong conversion behavior')
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]),