opencv/modules/python/src2/gen2.py

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#!/usr/bin/env python
from __future__ import print_function
import hdr_parser, sys, re, os
from string import Template
from pprint import pprint
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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from collections import namedtuple
if sys.version_info[0] >= 3:
from io import StringIO
else:
from cStringIO import StringIO
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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forbidden_arg_types = ["void*"]
ignored_arg_types = ["RNG*"]
pass_by_val_types = ["Point*", "Point2f*", "Rect*", "String*", "double*", "float*", "int*"]
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gen_template_check_self = Template("""
${cname} * self1 = 0;
if (!pyopencv_${name}_getp(self, self1))
return failmsgp("Incorrect type of self (must be '${name}' or its derivative)");
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${pname} _self_ = ${cvt}(self1);
""")
gen_template_call_constructor_prelude = Template("""new (&(self->v)) Ptr<$cname>(); // init Ptr with placement new
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if(self) """)
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gen_template_call_constructor = Template("""self->v.reset(new ${cname}${args})""")
gen_template_simple_call_constructor_prelude = Template("""if(self) """)
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gen_template_simple_call_constructor = Template("""new (&(self->v)) ${cname}${args}""")
gen_template_parse_args = Template("""const char* keywords[] = { $kw_list, NULL };
if( PyArg_ParseTupleAndKeywords(args, kw, "$fmtspec", (char**)keywords, $parse_arglist)$code_cvt )""")
gen_template_func_body = Template("""$code_decl
$code_parse
{
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${code_prelude}ERRWRAP2($code_fcall);
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$code_ret;
}
""")
gen_template_mappable = Template("""
{
${mappable} _src;
if (pyopencv_to_safe(src, _src, info))
{
return cv_mappable_to(_src, dst);
}
}
""")
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gen_template_type_decl = Template("""
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// Converter (${name})
template<>
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struct PyOpenCV_Converter< ${cname} >
{
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static PyObject* from(const ${cname}& r)
{
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return pyopencv_${name}_Instance(r);
}
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static bool to(PyObject* src, ${cname}& dst, const ArgInfo& info)
{
if(!src || src == Py_None)
return true;
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${cname} * dst_;
if (pyopencv_${name}_getp(src, dst_))
{
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dst = *dst_;
return true;
}
${mappable_code}
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failmsg("Expected ${cname} for argument '%s'", info.name);
return false;
}
};
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""")
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gen_template_map_type_cvt = Template("""
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template<> bool pyopencv_to(PyObject* src, ${cname}& dst, const ArgInfo& info);
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""")
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gen_template_set_prop_from_map = Template("""
if( PyMapping_HasKeyString(src, (char*)"$propname") )
{
tmp = PyMapping_GetItemString(src, (char*)"$propname");
ok = tmp && pyopencv_to_safe(tmp, dst.$propname, ArgInfo("$propname", false));
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Py_DECREF(tmp);
if(!ok) return false;
}""")
gen_template_type_impl = Template("""
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// GetSet (${name})
${getset_code}
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// Methods (${name})
${methods_code}
// Tables (${name})
static PyGetSetDef pyopencv_${name}_getseters[] =
{${getset_inits}
{NULL} /* Sentinel */
};
static PyMethodDef pyopencv_${name}_methods[] =
{
${methods_inits}
{NULL, NULL}
};
""")
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gen_template_get_prop = Template("""
static PyObject* pyopencv_${name}_get_${member}(pyopencv_${name}_t* p, void *closure)
{
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return pyopencv_from(p->v${access}${member});
}
""")
gen_template_get_prop_algo = Template("""
static PyObject* pyopencv_${name}_get_${member}(pyopencv_${name}_t* p, void *closure)
{
$cname* _self_ = dynamic_cast<$cname*>(p->v.get());
if (!_self_)
return failmsgp("Incorrect type of object (must be '${name}' or its derivative)");
return pyopencv_from(_self_${access}${member});
}
""")
gen_template_set_prop = Template("""
static int pyopencv_${name}_set_${member}(pyopencv_${name}_t* p, PyObject *value, void *closure)
{
if (!value)
{
PyErr_SetString(PyExc_TypeError, "Cannot delete the ${member} attribute");
return -1;
}
return pyopencv_to_safe(value, p->v${access}${member}, ArgInfo("value", false)) ? 0 : -1;
}
""")
gen_template_set_prop_algo = Template("""
static int pyopencv_${name}_set_${member}(pyopencv_${name}_t* p, PyObject *value, void *closure)
{
if (!value)
{
PyErr_SetString(PyExc_TypeError, "Cannot delete the ${member} attribute");
return -1;
}
$cname* _self_ = dynamic_cast<$cname*>(p->v.get());
if (!_self_)
{
failmsgp("Incorrect type of object (must be '${name}' or its derivative)");
return -1;
}
return pyopencv_to_safe(value, _self_${access}${member}, ArgInfo("value", false)) ? 0 : -1;
}
""")
gen_template_prop_init = Template("""
{(char*)"${member}", (getter)pyopencv_${name}_get_${member}, NULL, (char*)"${member}", NULL},""")
gen_template_rw_prop_init = Template("""
{(char*)"${member}", (getter)pyopencv_${name}_get_${member}, (setter)pyopencv_${name}_set_${member}, (char*)"${member}", NULL},""")
gen_template_overloaded_function_call = Template("""
{
${variant}
pyPopulateArgumentConversionErrors();
}
""")
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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class FormatStrings:
string = 's'
unsigned_char = 'b'
short_int = 'h'
int = 'i'
unsigned_int = 'I'
long = 'l'
unsigned_long = 'k'
long_long = 'L'
unsigned_long_long = 'K'
size_t = 'n'
float = 'f'
double = 'd'
object = 'O'
ArgTypeInfo = namedtuple('ArgTypeInfo',
['atype', 'format_str', 'default_value',
'strict_conversion'])
# strict_conversion is False by default
ArgTypeInfo.__new__.__defaults__ = (False,)
simple_argtype_mapping = {
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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"bool": ArgTypeInfo("bool", FormatStrings.unsigned_char, "0", True),
"size_t": ArgTypeInfo("size_t", FormatStrings.unsigned_long_long, "0", True),
"int": ArgTypeInfo("int", FormatStrings.int, "0", True),
"float": ArgTypeInfo("float", FormatStrings.float, "0.f", True),
"double": ArgTypeInfo("double", FormatStrings.double, "0", True),
"c_string": ArgTypeInfo("char*", FormatStrings.string, '(char*)""')
}
# Set of reserved keywords for Python. Can be acquired via the following call
# $ python -c "help('keywords')"
# Keywords that are reserved in C/C++ are excluded because they can not be
# used as variables identifiers
python_reserved_keywords = {
"True", "None", "False", "as", "assert", "def", "del", "elif", "except", "exec",
"finally", "from", "global", "import", "in", "is", "lambda", "nonlocal",
"pass", "print", "raise", "with", "yield"
}
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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def normalize_class_name(name):
return re.sub(r"^cv\.", "", name).replace(".", "_")
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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def get_type_format_string(arg_type_info):
if arg_type_info.strict_conversion:
return FormatStrings.object
else:
return arg_type_info.format_str
class ClassProp(object):
def __init__(self, decl):
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self.tp = decl[0].replace("*", "_ptr")
self.name = decl[1]
self.readonly = True
if "/RW" in decl[3]:
self.readonly = False
class ClassInfo(object):
def __init__(self, name, decl=None, codegen=None):
# Scope name can be a module or other class e.g. cv::SimpleBlobDetector::Params
scope_name, self.original_name = name.rsplit(".", 1)
# In case scope refer the outer class exported with different name
if codegen:
scope_name = codegen.get_export_scope_name(scope_name)
self.scope_name = re.sub(r"^cv\.?", "", scope_name)
self.export_name = self.original_name
self.class_id = normalize_class_name(name)
self.cname = name.replace(".", "::")
self.ismap = False
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self.issimple = False
self.isalgorithm = False
self.methods = {}
self.props = []
self.mappables = []
self.consts = {}
self.base = None
self.constructor = None
customname = False
if decl:
bases = decl[1].split()[1:]
if len(bases) > 1:
print("Note: Class %s has more than 1 base class (not supported by Python C extensions)" % (self.cname,))
print(" Bases: ", " ".join(bases))
print(" Only the first base class will be used")
#return sys.exit(-1)
elif len(bases) == 1:
self.base = bases[0].strip(",")
if self.base.startswith("cv::"):
self.base = self.base[4:]
if self.base == "Algorithm":
self.isalgorithm = True
self.base = self.base.replace("::", "_")
for m in decl[2]:
if m.startswith("="):
# Aliasing only affects the exported class name, not class identifier
self.export_name = m[1:]
elif m == "/Map":
self.ismap = True
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elif m == "/Simple":
self.issimple = True
self.props = [ClassProp(p) for p in decl[3]]
if not self.has_export_alias and self.original_name.startswith("Cv"):
self.export_name = self.export_name[2:]
if not customname and self.wname.startswith("Cv"):
self.wname = self.wname[2:]
@property
def wname(self):
if len(self.scope_name) > 0:
return self.scope_name.replace(".", "_") + "_" + self.export_name
return self.export_name
@property
def name(self):
return self.class_id
@property
def full_scope_name(self):
return "cv." + self.scope_name if len(self.scope_name) else "cv"
@property
def full_export_name(self):
return self.full_scope_name + "." + self.export_name
@property
def full_original_name(self):
return self.full_scope_name + "." + self.original_name
@property
def has_export_alias(self):
return self.export_name != self.original_name
def gen_map_code(self, codegen):
all_classes = codegen.classes
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code = "static bool pyopencv_to(PyObject* src, %s& dst, const ArgInfo& info)\n{\n PyObject* tmp;\n bool ok;\n" % (self.cname)
code += "".join([gen_template_set_prop_from_map.substitute(propname=p.name,proptype=p.tp) for p in self.props])
if self.base:
code += "\n return pyopencv_to_safe(src, (%s&)dst, info);\n}\n" % all_classes[self.base].cname
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else:
code += "\n return true;\n}\n"
return code
def gen_code(self, codegen):
all_classes = codegen.classes
if self.ismap:
return self.gen_map_code(codegen)
getset_code = StringIO()
getset_inits = StringIO()
sorted_props = [(p.name, p) for p in self.props]
sorted_props.sort()
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access_op = "->"
if self.issimple:
access_op = "."
for pname, p in sorted_props:
if self.isalgorithm:
getset_code.write(gen_template_get_prop_algo.substitute(name=self.name, cname=self.cname, member=pname, membertype=p.tp, access=access_op))
else:
getset_code.write(gen_template_get_prop.substitute(name=self.name, member=pname, membertype=p.tp, access=access_op))
if p.readonly:
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getset_inits.write(gen_template_prop_init.substitute(name=self.name, member=pname))
else:
if self.isalgorithm:
getset_code.write(gen_template_set_prop_algo.substitute(name=self.name, cname=self.cname, member=pname, membertype=p.tp, access=access_op))
else:
getset_code.write(gen_template_set_prop.substitute(name=self.name, member=pname, membertype=p.tp, access=access_op))
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getset_inits.write(gen_template_rw_prop_init.substitute(name=self.name, member=pname))
methods_code = StringIO()
methods_inits = StringIO()
sorted_methods = list(self.methods.items())
sorted_methods.sort()
if self.constructor is not None:
methods_code.write(self.constructor.gen_code(codegen))
for mname, m in sorted_methods:
methods_code.write(m.gen_code(codegen))
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methods_inits.write(m.get_tab_entry())
code = gen_template_type_impl.substitute(name=self.name,
getset_code=getset_code.getvalue(),
getset_inits=getset_inits.getvalue(),
methods_code=methods_code.getvalue(),
methods_inits=methods_inits.getvalue())
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return code
def gen_def(self, codegen):
all_classes = codegen.classes
baseptr = "NoBase"
if self.base and self.base in all_classes:
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baseptr = all_classes[self.base].name
constructor_name = "0"
if self.constructor is not None:
constructor_name = self.constructor.get_wrapper_name()
return 'CVPY_TYPE({}, {}, {}, {}, {}, {}, "{}");\n'.format(
self.export_name,
self.class_id,
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self.cname if self.issimple else "Ptr<{}>".format(self.cname),
self.original_name if self.issimple else "Ptr",
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baseptr,
constructor_name,
# Leading dot is required to provide correct class naming
"." + self.scope_name if len(self.scope_name) > 0 else self.scope_name
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)
def handle_ptr(tp):
if tp.startswith('Ptr_'):
tp = 'Ptr<' + "::".join(tp.split('_')[1:]) + '>'
return tp
class ArgInfo(object):
def __init__(self, arg_tuple):
self.tp = handle_ptr(arg_tuple[0])
self.name = arg_tuple[1]
if self.name in python_reserved_keywords:
self.name += "_"
self.defval = arg_tuple[2]
self.isarray = False
self.arraylen = 0
self.arraycvt = None
self.inputarg = True
self.outputarg = False
self.returnarg = False
for m in arg_tuple[3]:
if m == "/O":
self.inputarg = False
self.outputarg = True
self.returnarg = True
elif m == "/IO":
self.inputarg = True
self.outputarg = True
self.returnarg = True
elif m.startswith("/A"):
self.isarray = True
self.arraylen = m[2:].strip()
elif m.startswith("/CA"):
self.isarray = True
self.arraycvt = m[2:].strip()
self.py_inputarg = False
self.py_outputarg = False
def isbig(self):
return self.tp == "Mat" or self.tp == "vector_Mat" or self.tp == "cuda::GpuMat"\
or self.tp == "UMat" or self.tp == "vector_UMat" # or self.tp.startswith("vector")
def crepr(self):
return "ArgInfo(\"%s\", %d)" % (self.name, self.outputarg)
class FuncVariant(object):
def __init__(self, classname, name, decl, isconstructor, isphantom=False):
2010-11-03 01:58:22 +08:00
self.classname = classname
self.name = self.wname = name
self.isconstructor = isconstructor
self.isphantom = isphantom
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self.docstring = decl[5]
self.rettype = decl[4] or handle_ptr(decl[1])
if self.rettype == "void":
self.rettype = ""
self.args = []
self.array_counters = {}
for a in decl[3]:
ainfo = ArgInfo(a)
if ainfo.isarray and not ainfo.arraycvt:
c = ainfo.arraylen
c_arrlist = self.array_counters.get(c, [])
if c_arrlist:
c_arrlist.append(ainfo.name)
else:
self.array_counters[c] = [ainfo.name]
self.args.append(ainfo)
self.init_pyproto()
def init_pyproto(self):
# string representation of argument list, with '[', ']' symbols denoting optional arguments, e.g.
# "src1, src2[, dst[, mask]]" for cv.add
argstr = ""
# list of all input arguments of the Python function, with the argument numbers:
# [("src1", 0), ("src2", 1), ("dst", 2), ("mask", 3)]
# we keep an argument number to find the respective argument quickly, because
# some of the arguments of C function may not present in the Python function (such as array counters)
# or even go in a different order ("heavy" output parameters of the C function
# become the first optional input parameters of the Python function, and thus they are placed right after
# non-optional input parameters)
arglist = []
# the list of "heavy" output parameters. Heavy parameters are the parameters
# that can be expensive to allocate each time, such as vectors and matrices (see isbig).
outarr_list = []
# the list of output parameters. Also includes input/output parameters.
outlist = []
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firstoptarg = 1000000
argno = -1
for a in self.args:
argno += 1
if a.name in self.array_counters:
continue
assert not a.tp in forbidden_arg_types, 'Forbidden type "{}" for argument "{}" in "{}" ("{}")'.format(a.tp, a.name, self.name, self.classname)
if a.tp in ignored_arg_types:
continue
if a.returnarg:
outlist.append((a.name, argno))
if (not a.inputarg) and a.isbig():
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outarr_list.append((a.name, argno))
continue
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if not a.inputarg:
continue
if not a.defval:
arglist.append((a.name, argno))
else:
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firstoptarg = min(firstoptarg, len(arglist))
# if there are some array output parameters before the first default parameter, they
# are added as optional parameters before the first optional parameter
if outarr_list:
arglist += outarr_list
outarr_list = []
arglist.append((a.name, argno))
if outarr_list:
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firstoptarg = min(firstoptarg, len(arglist))
arglist += outarr_list
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firstoptarg = min(firstoptarg, len(arglist))
noptargs = len(arglist) - firstoptarg
argnamelist = [aname for aname, argno in arglist]
argstr = ", ".join(argnamelist[:firstoptarg])
argstr = "[, ".join([argstr] + argnamelist[firstoptarg:])
argstr += "]" * noptargs
if self.rettype:
outlist = [("retval", -1)] + outlist
elif self.isconstructor:
assert outlist == []
outlist = [("self", -1)]
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if self.isconstructor:
classname = self.classname
if classname.startswith("Cv"):
classname=classname[2:]
outstr = "<%s object>" % (classname,)
elif outlist:
outstr = ", ".join([o[0] for o in outlist])
else:
outstr = "None"
self.py_arg_str = argstr
self.py_return_str = outstr
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self.py_prototype = "%s(%s) -> %s" % (self.wname, argstr, outstr)
self.py_noptargs = noptargs
self.py_arglist = arglist
for aname, argno in arglist:
self.args[argno].py_inputarg = True
for aname, argno in outlist:
if argno >= 0:
self.args[argno].py_outputarg = True
self.py_outlist = outlist
class FuncInfo(object):
def __init__(self, classname, name, cname, isconstructor, namespace, is_static):
self.classname = classname
self.name = name
self.cname = cname
self.isconstructor = isconstructor
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self.namespace = namespace
self.is_static = is_static
self.variants = []
def add_variant(self, decl, isphantom=False):
self.variants.append(FuncVariant(self.classname, self.name, decl, self.isconstructor, isphantom))
def get_wrapper_name(self):
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name = self.name
if self.classname:
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classname = self.classname + "_"
if "[" in name:
name = "getelem"
else:
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classname = ""
if self.is_static:
name += "_static"
return "pyopencv_" + self.namespace.replace('.','_') + '_' + classname + name
def get_wrapper_prototype(self, codegen):
full_fname = self.get_wrapper_name()
if self.isconstructor:
return "static int {fn_name}(pyopencv_{type_name}_t* self, PyObject* args, PyObject* kw)".format(
fn_name=full_fname, type_name=codegen.classes[self.classname].name)
if self.classname:
self_arg = "self"
else:
self_arg = ""
return "static PyObject* %s(PyObject* %s, PyObject* args, PyObject* kw)" % (full_fname, self_arg)
def get_tab_entry(self):
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prototype_list = []
docstring_list = []
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have_empty_constructor = False
for v in self.variants:
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s = v.py_prototype
if (not v.py_arglist) and self.isconstructor:
have_empty_constructor = True
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if s not in prototype_list:
prototype_list.append(s)
docstring_list.append(v.docstring)
# if there are just 2 constructors: default one and some other,
# we simplify the notation.
# Instead of ClassName(args ...) -> object or ClassName() -> object
# we write ClassName([args ...]) -> object
if have_empty_constructor and len(self.variants) == 2:
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idx = self.variants[1].py_arglist != []
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s = self.variants[idx].py_prototype
p1 = s.find("(")
p2 = s.rfind(")")
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prototype_list = [s[:p1+1] + "[" + s[p1+1:p2] + "]" + s[p2:]]
# The final docstring will be: Each prototype, followed by
# their relevant doxygen comment
full_docstring = ""
for prototype, body in zip(prototype_list, docstring_list):
full_docstring += Template("$prototype\n$docstring\n\n\n\n").substitute(
prototype=prototype,
docstring='\n'.join(
['. ' + line
for line in body.split('\n')]
)
)
# Escape backslashes, newlines, and double quotes
full_docstring = full_docstring.strip().replace("\\", "\\\\").replace('\n', '\\n').replace("\"", "\\\"")
# Convert unicode chars to xml representation, but keep as string instead of bytes
full_docstring = full_docstring.encode('ascii', errors='xmlcharrefreplace').decode()
return Template(' {"$py_funcname", CV_PY_FN_WITH_KW_($wrap_funcname, $flags), "$py_docstring"},\n'
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).substitute(py_funcname = self.variants[0].wname, wrap_funcname=self.get_wrapper_name(),
flags = 'METH_STATIC' if self.is_static else '0', py_docstring = full_docstring)
def gen_code(self, codegen):
all_classes = codegen.classes
proto = self.get_wrapper_prototype(codegen)
code = "%s\n{\n" % (proto,)
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code += " using namespace %s;\n\n" % self.namespace.replace('.', '::')
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selfinfo = None
ismethod = self.classname != "" and not self.isconstructor
# full name is needed for error diagnostic in PyArg_ParseTupleAndKeywords
fullname = self.name
if self.classname:
selfinfo = all_classes[self.classname]
if not self.isconstructor:
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if not self.is_static:
code += gen_template_check_self.substitute(
name=selfinfo.name,
cname=selfinfo.cname if selfinfo.issimple else "Ptr<{}>".format(selfinfo.cname),
pname=(selfinfo.cname + '*') if selfinfo.issimple else "Ptr<{}>".format(selfinfo.cname),
cvt='' if selfinfo.issimple else '*'
)
fullname = selfinfo.wname + "." + fullname
all_code_variants = []
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
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for v in self.variants:
code_decl = ""
code_ret = ""
code_cvt_list = []
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code_args = "("
all_cargs = []
if v.isphantom and ismethod and not self.is_static:
code_args += "_self_"
# declare all the C function arguments,
# add necessary conversions from Python objects to code_cvt_list,
# form the function/method call,
# for the list of type mappings
for a in v.args:
if a.tp in ignored_arg_types:
defval = a.defval
if not defval and a.tp.endswith("*"):
defval = "0"
assert defval
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if not code_args.endswith("("):
code_args += ", "
code_args += defval
all_cargs.append([[None, ""], ""])
continue
tp1 = tp = a.tp
amp = ""
defval0 = ""
if tp in pass_by_val_types:
tp = tp1 = tp[:-1]
amp = "&"
if tp.endswith("*"):
defval0 = "0"
tp1 = tp.replace("*", "_ptr")
tp_candidates = [a.tp, normalize_class_name(self.namespace + "." + a.tp)]
if any(tp in codegen.enums.keys() for tp in tp_candidates):
defval0 = "static_cast<%s>(%d)" % (a.tp, 0)
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
arg_type_info = simple_argtype_mapping.get(tp, ArgTypeInfo(tp, FormatStrings.object, defval0, True))
parse_name = a.name
if a.py_inputarg:
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
if arg_type_info.strict_conversion:
code_decl += " PyObject* pyobj_%s = NULL;\n" % (a.name,)
parse_name = "pyobj_" + a.name
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if a.tp == 'char':
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
code_cvt_list.append("convert_to_char(pyobj_%s, &%s, %s)" % (a.name, a.name, a.crepr()))
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else:
code_cvt_list.append("pyopencv_to_safe(pyobj_%s, %s, %s)" % (a.name, a.name, a.crepr()))
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
all_cargs.append([arg_type_info, parse_name])
defval = a.defval
if not defval:
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
defval = arg_type_info.default_value
else:
if "UMat" in tp:
if "Mat" in defval and "UMat" not in defval:
defval = defval.replace("Mat", "UMat")
if "cuda::GpuMat" in tp:
if "Mat" in defval and "GpuMat" not in defval:
defval = defval.replace("Mat", "cuda::GpuMat")
# "tp arg = tp();" is equivalent to "tp arg;" in the case of complex types
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
if defval == tp + "()" and arg_type_info.format_str == FormatStrings.object:
defval = ""
2010-11-03 01:58:22 +08:00
if a.outputarg and not a.inputarg:
defval = ""
if defval:
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
code_decl += " %s %s=%s;\n" % (arg_type_info.atype, a.name, defval)
else:
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
code_decl += " %s %s;\n" % (arg_type_info.atype, a.name)
2013-08-14 16:32:41 +08:00
if not code_args.endswith("("):
code_args += ", "
code_args += amp + a.name
code_args += ")"
if self.isconstructor:
if selfinfo.issimple:
templ_prelude = gen_template_simple_call_constructor_prelude
templ = gen_template_simple_call_constructor
else:
templ_prelude = gen_template_call_constructor_prelude
templ = gen_template_call_constructor
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code_prelude = templ_prelude.substitute(name=selfinfo.name, cname=selfinfo.cname)
code_fcall = templ.substitute(name=selfinfo.name, cname=selfinfo.cname, args=code_args)
if v.isphantom:
code_fcall = code_fcall.replace("new " + selfinfo.cname, self.cname.replace("::", "_"))
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else:
code_prelude = ""
code_fcall = ""
if v.rettype:
code_decl += " " + v.rettype + " retval;\n"
code_fcall += "retval = "
if not v.isphantom and ismethod and not self.is_static:
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code_fcall += "_self_->" + self.cname
else:
code_fcall += self.cname
code_fcall += code_args
if code_cvt_list:
code_cvt_list = [""] + code_cvt_list
# add info about return value, if any, to all_cargs. if there non-void return value,
# it is encoded in v.py_outlist as ("retval", -1) pair.
# As [-1] in Python accesses the last element of a list, we automatically handle the return value by
# adding the necessary info to the end of all_cargs list.
if v.rettype:
tp = v.rettype
tp1 = tp.replace("*", "_ptr")
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
default_info = ArgTypeInfo(tp, FormatStrings.object, "0")
arg_type_info = simple_argtype_mapping.get(tp, default_info)
all_cargs.append(arg_type_info)
if v.args and v.py_arglist:
# form the format spec for PyArg_ParseTupleAndKeywords
Merge pull request #15915 from VadimLevin:dev/norm_fix 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
2020-01-13 23:11:34 +08:00
fmtspec = "".join([
get_type_format_string(all_cargs[argno][0])
for aname, argno in v.py_arglist
])
if v.py_noptargs > 0:
fmtspec = fmtspec[:-v.py_noptargs] + "|" + fmtspec[-v.py_noptargs:]
fmtspec += ":" + fullname
# form the argument parse code that:
# - declares the list of keyword parameters
# - calls PyArg_ParseTupleAndKeywords
# - converts complex arguments from PyObject's to native OpenCV types
code_parse = gen_template_parse_args.substitute(
kw_list = ", ".join(['"' + aname + '"' for aname, argno in v.py_arglist]),
fmtspec = fmtspec,
parse_arglist = ", ".join(["&" + all_cargs[argno][1] for aname, argno in v.py_arglist]),
code_cvt = " &&\n ".join(code_cvt_list))
else:
code_parse = "if(PyObject_Size(args) == 0 && (!kw || PyObject_Size(kw) == 0))"
if len(v.py_outlist) == 0:
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code_ret = "Py_RETURN_NONE"
elif len(v.py_outlist) == 1:
if self.isconstructor:
code_ret = "return 0"
else:
aname, argno = v.py_outlist[0]
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code_ret = "return pyopencv_from(%s)" % (aname,)
else:
# there is more than 1 return parameter; form the tuple out of them
fmtspec = "N"*len(v.py_outlist)
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code_ret = "return Py_BuildValue(\"(%s)\", %s)" % \
(fmtspec, ", ".join(["pyopencv_from(" + aname + ")" for aname, argno in v.py_outlist]))
all_code_variants.append(gen_template_func_body.substitute(code_decl=code_decl,
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code_parse=code_parse, code_prelude=code_prelude, code_fcall=code_fcall, code_ret=code_ret))
if len(all_code_variants)==1:
# if the function/method has only 1 signature, then just put it
code += all_code_variants[0]
else:
# try to execute each signature, add an interlude between function
# calls to collect error from all conversions
code += ' pyPrepareArgumentConversionErrorsStorage({});\n'.format(len(all_code_variants))
code += ' \n'.join(gen_template_overloaded_function_call.substitute(variant=v)
for v in all_code_variants)
code += ' pyRaiseCVOverloadException("{}");\n'.format(self.name)
def_ret = "NULL"
if self.isconstructor:
def_ret = "-1"
code += "\n return %s;\n}\n\n" % def_ret
cname = self.cname
classinfo = None
#dump = False
#if dump: pprint(vars(self))
#if dump: pprint(vars(self.variants[0]))
if self.classname:
classinfo = all_classes[self.classname]
#if dump: pprint(vars(classinfo))
if self.isconstructor:
py_name = classinfo.full_export_name
else:
py_name = classinfo.full_export_name + "." + self.variants[0].wname
if not self.is_static:
cname = classinfo.cname + '::' + cname
else:
py_name = '.'.join([self.namespace, self.variants[0].wname])
#if dump: print(cname + " => " + py_name)
py_signatures = codegen.py_signatures.setdefault(cname, [])
for v in self.variants:
s = dict(name=py_name, arg=v.py_arg_str, ret=v.py_return_str)
for old in py_signatures:
if s == old:
break
else:
py_signatures.append(s)
return code
class Namespace(object):
def __init__(self):
self.funcs = {}
self.consts = {}
class PythonWrapperGenerator(object):
def __init__(self):
self.clear()
def clear(self):
self.classes = {}
self.namespaces = {}
self.consts = {}
self.enums = {}
self.code_include = StringIO()
self.code_enums = StringIO()
self.code_types = StringIO()
self.code_funcs = StringIO()
self.code_ns_reg = StringIO()
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self.code_ns_init = StringIO()
self.code_type_publish = StringIO()
self.py_signatures = dict()
self.class_idx = 0
def add_class(self, stype, name, decl):
classinfo = ClassInfo(name, decl, self)
classinfo.decl_idx = self.class_idx
self.class_idx += 1
if classinfo.name in self.classes:
print("Generator error: class %s (cname=%s) already exists" \
% (classinfo.name, classinfo.cname))
sys.exit(-1)
self.classes[classinfo.name] = classinfo
namespace, _, _ = self.split_decl_name(name)
namespace = '.'.join(namespace)
# Registering a namespace if it is not already handled or
# doesn't have anything except classes defined in it
self.namespaces.setdefault(namespace, Namespace())
# Add Class to json file.
py_name = classinfo.full_export_name # use wrapper name
py_signatures = self.py_signatures.setdefault(classinfo.cname, [])
py_signatures.append(dict(name=py_name))
#print('class: ' + classinfo.cname + " => " + py_name)
def get_export_scope_name(self, original_scope_name):
# Outer classes should be registered before their content - inner classes in this case
class_scope = self.classes.get(normalize_class_name(original_scope_name), None)
if class_scope:
return class_scope.full_export_name
# Otherwise it is a namespace.
# If something is messed up at this point - it will be revelead during
# library import
return original_scope_name
def split_decl_name(self, name):
chunks = name.split('.')
namespace = chunks[:-1]
classes = []
while namespace and '.'.join(namespace) not in self.parser.namespaces:
classes.insert(0, namespace.pop())
return namespace, classes, chunks[-1]
def add_const(self, name, decl):
cname = name.replace('.','::')
namespace, classes, name = self.split_decl_name(name)
namespace = '.'.join(namespace)
name = '_'.join(classes+[name])
ns = self.namespaces.setdefault(namespace, Namespace())
if name in ns.consts:
print("Generator error: constant %s (cname=%s) already exists" \
% (name, cname))
sys.exit(-1)
ns.consts[name] = cname
value = decl[1]
py_name = '.'.join([namespace, name])
py_signatures = self.py_signatures.setdefault(cname, [])
py_signatures.append(dict(name=py_name, value=value))
#print(cname + ' => ' + str(py_name) + ' (value=' + value + ')')
def add_enum(self, name, decl):
wname = normalize_class_name(name)
if wname.endswith("<unnamed>"):
wname = None
else:
self.enums[wname] = name
const_decls = decl[3]
for decl in const_decls:
name = decl[0]
self.add_const(name.replace("const ", "").strip(), decl)
def add_func(self, decl):
namespace, classes, barename = self.split_decl_name(decl[0])
cname = "::".join(namespace+classes+[barename])
name = barename
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classname = ''
bareclassname = ''
if classes:
classname = normalize_class_name('.'.join(namespace+classes))
bareclassname = classes[-1]
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namespace_str = '.'.join(namespace)
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isconstructor = name == bareclassname
is_static = False
isphantom = False
mappable = None
for m in decl[2]:
if m == "/S":
is_static = True
elif m == "/phantom":
isphantom = True
cname = cname.replace("::", "_")
elif m.startswith("="):
name = m[1:]
elif m.startswith("/mappable="):
mappable = m[10:]
self.classes[classname].mappables.append(mappable)
return
if isconstructor:
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name = "_".join(classes[:-1]+[name])
if is_static:
# Add it as a method to the class
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func_map = self.classes[classname].methods
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func = func_map.setdefault(name, FuncInfo(classname, name, cname, isconstructor, namespace_str, is_static))
func.add_variant(decl, isphantom)
# Add it as global function
g_name = "_".join(classes+[name])
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w_classes = []
for i in range(0, len(classes)):
classes_i = classes[:i+1]
classname_i = normalize_class_name('.'.join(namespace+classes_i))
w_classname = self.classes[classname_i].wname
namespace_prefix = normalize_class_name('.'.join(namespace)) + '_'
if w_classname.startswith(namespace_prefix):
w_classname = w_classname[len(namespace_prefix):]
w_classes.append(w_classname)
g_wname = "_".join(w_classes+[name])
func_map = self.namespaces.setdefault(namespace_str, Namespace()).funcs
# Exports static function with internal name (backward compatibility)
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func = func_map.setdefault(g_name, FuncInfo("", g_name, cname, isconstructor, namespace_str, False))
func.add_variant(decl, isphantom)
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if g_wname != g_name: # TODO OpenCV 5.0
wfunc = func_map.setdefault(g_wname, FuncInfo("", g_wname, cname, isconstructor, namespace_str, False))
wfunc.add_variant(decl, isphantom)
else:
if classname and not isconstructor:
if not isphantom:
cname = barename
func_map = self.classes[classname].methods
else:
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func_map = self.namespaces.setdefault(namespace_str, Namespace()).funcs
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func = func_map.setdefault(name, FuncInfo(classname, name, cname, isconstructor, namespace_str, is_static))
func.add_variant(decl, isphantom)
if classname and isconstructor:
self.classes[classname].constructor = func
def gen_namespace(self, ns_name):
ns = self.namespaces[ns_name]
wname = normalize_class_name(ns_name)
self.code_ns_reg.write('static PyMethodDef methods_%s[] = {\n'%wname)
for name, func in sorted(ns.funcs.items()):
if func.isconstructor:
continue
self.code_ns_reg.write(func.get_tab_entry())
self.code_ns_reg.write(' {NULL, NULL}\n};\n\n')
self.code_ns_reg.write('static ConstDef consts_%s[] = {\n'%wname)
for name, cname in sorted(ns.consts.items()):
self.code_ns_reg.write(' {"%s", static_cast<long>(%s)},\n'%(name, cname))
compat_name = re.sub(r"([a-z])([A-Z])", r"\1_\2", name).upper()
if name != compat_name:
self.code_ns_reg.write(' {"%s", static_cast<long>(%s)},\n'%(compat_name, cname))
self.code_ns_reg.write(' {NULL, 0}\n};\n\n')
def gen_enum_reg(self, enum_name):
name_seg = enum_name.split(".")
is_enum_class = False
if len(name_seg) >= 2 and name_seg[-1] == name_seg[-2]:
enum_name = ".".join(name_seg[:-1])
is_enum_class = True
wname = normalize_class_name(enum_name)
cname = enum_name.replace(".", "::")
code = ""
if re.sub(r"^cv\.", "", enum_name) != wname:
code += "typedef enum {0} {1};\n".format(cname, wname)
code += "CV_PY_FROM_ENUM({0});\nCV_PY_TO_ENUM({0});\n\n".format(wname)
self.code_enums.write(code)
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def save(self, path, name, buf):
with open(path + "/" + name, "wt") as f:
f.write(buf.getvalue())
def save_json(self, path, name, value):
import json
with open(path + "/" + name, "wt") as f:
json.dump(value, f)
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def gen(self, srcfiles, output_path):
self.clear()
self.parser = hdr_parser.CppHeaderParser(generate_umat_decls=True, generate_gpumat_decls=False)
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# step 1: scan the headers and build more descriptive maps of classes, consts, functions
for hdr in srcfiles:
decls = self.parser.parse(hdr)
if len(decls) == 0:
continue
if hdr.find('opencv2/') >= 0: #Avoid including the shadow files
self.code_include.write( '#include "{0}"\n'.format(hdr[hdr.rindex('opencv2/'):]) )
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for decl in decls:
name = decl[0]
if name.startswith("struct") or name.startswith("class"):
# class/struct
p = name.find(" ")
stype = name[:p]
name = name[p+1:].strip()
self.add_class(stype, name, decl)
elif name.startswith("const"):
# constant
self.add_const(name.replace("const ", "").strip(), decl)
elif name.startswith("enum"):
# enum
self.add_enum(name.rsplit(" ", 1)[1], decl)
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else:
# function
self.add_func(decl)
# step 1.5 check if all base classes exist
for name, classinfo in self.classes.items():
if classinfo.base:
chunks = classinfo.base.split('_')
base = '_'.join(chunks)
while base not in self.classes and len(chunks)>1:
del chunks[-2]
base = '_'.join(chunks)
if base not in self.classes:
print("Generator error: unable to resolve base %s for %s"
% (classinfo.base, classinfo.name))
sys.exit(-1)
base_instance = self.classes[base]
classinfo.base = base
classinfo.isalgorithm |= base_instance.isalgorithm # wrong processing of 'isalgorithm' flag:
# doesn't work for trees(graphs) with depth > 2
self.classes[name] = classinfo
# tree-based propagation of 'isalgorithm'
processed = dict()
def process_isalgorithm(classinfo):
if classinfo.isalgorithm or classinfo in processed:
return classinfo.isalgorithm
res = False
if classinfo.base:
res = process_isalgorithm(self.classes[classinfo.base])
#assert not (res == True or classinfo.isalgorithm is False), "Internal error: " + classinfo.name + " => " + classinfo.base
classinfo.isalgorithm |= res
res = classinfo.isalgorithm
processed[classinfo] = True
return res
for name, classinfo in self.classes.items():
process_isalgorithm(classinfo)
# step 2: generate code for the classes and their methods
classlist = list(self.classes.items())
classlist.sort()
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for name, classinfo in classlist:
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self.code_types.write("//{}\n".format(80*"="))
self.code_types.write("// {} ({})\n".format(name, 'Map' if classinfo.ismap else 'Generic'))
self.code_types.write("//{}\n".format(80*"="))
self.code_types.write(classinfo.gen_code(self))
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if classinfo.ismap:
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self.code_types.write(gen_template_map_type_cvt.substitute(name=classinfo.name, cname=classinfo.cname))
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else:
mappable_code = "\n".join([
gen_template_mappable.substitute(cname=classinfo.cname, mappable=mappable)
for mappable in classinfo.mappables])
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code = gen_template_type_decl.substitute(
name=classinfo.name,
cname=classinfo.cname if classinfo.issimple else "Ptr<{}>".format(classinfo.cname),
mappable_code=mappable_code
)
self.code_types.write(code)
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# register classes in the same order as they have been declared.
# this way, base classes will be registered in Python before their derivatives.
classlist1 = [(classinfo.decl_idx, name, classinfo) for name, classinfo in classlist]
classlist1.sort()
published_types = set() # ensure toposort with base classes
for decl_idx, name, classinfo in classlist1:
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if classinfo.ismap:
continue
def _registerType(classinfo):
if classinfo.decl_idx in published_types:
#print(classinfo.decl_idx, classinfo.name, ' - already published')
return
published_types.add(classinfo.decl_idx)
if classinfo.base and classinfo.base in self.classes:
base_classinfo = self.classes[classinfo.base]
#print(classinfo.decl_idx, classinfo.name, ' - request publishing of base type ', base_classinfo.decl_idx, base_classinfo.name)
_registerType(base_classinfo)
#print(classinfo.decl_idx, classinfo.name, ' - published!')
self.code_type_publish.write(classinfo.gen_def(self))
_registerType(classinfo)
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# step 3: generate the code for all the global functions
for ns_name, ns in sorted(self.namespaces.items()):
if ns_name.split('.')[0] != 'cv':
continue
for name, func in sorted(ns.funcs.items()):
if func.isconstructor:
continue
code = func.gen_code(self)
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self.code_funcs.write(code)
self.gen_namespace(ns_name)
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self.code_ns_init.write('CVPY_MODULE("{}", {});\n'.format(ns_name[2:], normalize_class_name(ns_name)))
# step 4: generate the code for enum types
enumlist = list(self.enums.values())
enumlist.sort()
for name in enumlist:
self.gen_enum_reg(name)
# step 5: generate the code for constants
constlist = list(self.consts.items())
constlist.sort()
for name, constinfo in constlist:
self.gen_const_reg(constinfo)
# That's it. Now save all the files
self.save(output_path, "pyopencv_generated_include.h", self.code_include)
self.save(output_path, "pyopencv_generated_funcs.h", self.code_funcs)
self.save(output_path, "pyopencv_generated_enums.h", self.code_enums)
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self.save(output_path, "pyopencv_generated_types.h", self.code_type_publish)
self.save(output_path, "pyopencv_generated_types_content.h", self.code_types)
self.save(output_path, "pyopencv_generated_modules.h", self.code_ns_init)
self.save(output_path, "pyopencv_generated_modules_content.h", self.code_ns_reg)
self.save_json(output_path, "pyopencv_signatures.json", self.py_signatures)
if __name__ == "__main__":
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srcfiles = hdr_parser.opencv_hdr_list
dstdir = "/Users/vp/tmp"
if len(sys.argv) > 1:
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dstdir = sys.argv[1]
if len(sys.argv) > 2:
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with open(sys.argv[2], 'r') as f:
srcfiles = [l.strip() for l in f.readlines()]
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generator = PythonWrapperGenerator()
generator.gen(srcfiles, dstdir)