Chiebot-Mirror
/
opencv
8
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Merge pull request #15955 from VadimLevin:dev/vlevin/generator_tests

Browse Source 
Tests for argument conversion of Python bindings generator

* Tests for parsing elemental types from Python bindings

  - Add positive and negative tests for int, float, double, size_t,
    const char*, bool.
  - Tests with wrong conversion behavior are skipped.

* Move implicit conversion of bool to integer/floating types to wrong
conversion behavior.
pull/16020/head^2
Vadim Levin 5 years ago committed by Alexander Alekhin
parent 41af8aa046
commit 8d74101f07
2 changed files with 292 additions and 19 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 38
      modules/core/include/opencv2/core/bindings_utils.hpp
  2. 273
      modules/python/test/test_misc.py

38
modules/core/include/opencv2/core/bindings_utils.hpp
Unescape View File

@ -20,6 +20,44 @@ CV_EXPORTS_W String dumpInputOutputArray(InputOutputArray argument);
CV_EXPORTS_W String dumpInputOutputArrayOfArrays(InputOutputArrayOfArrays argument);
CV_WRAP static inline
String dumpBool(bool argument)
{
return (argument) ? String("Bool: True") : String("Bool: False");
}
CV_WRAP static inline
String dumpInt(int argument)
{
return cv::format("Int: %d", argument);
}
CV_WRAP static inline
String dumpSizeT(size_t argument)
{
std::ostringstream oss("size_t: ", std::ios::ate);
oss << argument;
return oss.str();
}
CV_WRAP static inline
String dumpFloat(float argument)
{
return cv::format("Float: %.2f", argument);
}
CV_WRAP static inline
String dumpDouble(double argument)
{
return cv::format("Double: %.2f", argument);
}
CV_WRAP static inline
String dumpCString(const char* argument)
{
return cv::format("String: %s", argument);
}
CV_WRAP static inline
AsyncArray testAsyncArray(InputArray argument)
{

273
modules/python/test/test_misc.py
Unescape View File

@ -1,38 +1,66 @@
#!/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
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
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
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
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
cv.imshow("", None) # This causes an assert
self.assertEqual("Dead code", 0)
except cv.error as _e:
self.assertEqual(handler_called[0], True)
@ -40,7 +68,7 @@ class Bindings(NewOpenCVTests):
cv.redirectError(None)
try:
cv.imshow("", None) # This causes an assert
cv.imshow("", None) # This causes an assert
self.assertEqual("Dead code", 0)
except cv.error as _e:
pass
@ -48,41 +76,248 @@ class Bindings(NewOpenCVTests):
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: 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]])
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')
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)
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")
def test_InputArrayOfArrays(self):
res1 = cv.utils.dumpInputArrayOfArrays(None)
#self.assertEqual(res1, "InputArray: noArray()") # not supported
# 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 type(0)=CV_64FC1")
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 type(0)=CV_64FC1")
a = np.array([[1,2],[3,4],[5,6]])
b = np.array([[1,2,3],[4,5,6],[7,8,9]])
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 type(0)=CV_32SC1")
c = np.array([[[1,2],[3,4],[5,6]]], dtype='f')
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 type(0)=CV_32FC2")
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), None,
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)
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))
@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),
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), None):
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),
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, True, False, 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):
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):
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)
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))
@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),
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], None, 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]),
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], None, 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]),
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)
class SamplesFindFile(NewOpenCVTests):

Write Preview
Loading…
Cancel
Save