third_party/opencv
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge remote-tracking branch 'upstream/3.4' into merge-3.4

Browse Source
This commit is contained in:
Alexander Alekhin
2021-09-02 15:24:04 +00:00
parent c11195d5e3 7c23ec90a9
commit 5aa7435d25
15 changed files with 633 additions and 434 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/python/src2/cv2.cpp
+311 -345
View File
@@ -496,6 +496,33 @@ bool parseSequence(PyObject* obj, RefWrapper<T> (&value)[N], const ArgInfo& info
}
} // namespace
namespace traits {
template <bool Value>
struct BooleanConstant
{
static const bool value = Value;
typedef BooleanConstant<Value> type;
};
typedef BooleanConstant<true> TrueType;
typedef BooleanConstant<false> FalseType;
template <class T>
struct VoidType {
typedef void type;
};
template <class T, class DType = void>
struct IsRepresentableAsMatDataType : FalseType
{
};
template <class T>
struct IsRepresentableAsMatDataType<T, typename VoidType<typename DataType<T>::channel_type>::type> : TrueType
{
};
} // namespace traits
typedef std::vector<uchar> vector_uchar;
typedef std::vector<char> vector_char;
typedef std::vector<int> vector_int;
@@ -1072,6 +1099,30 @@ bool pyopencv_to(PyObject* obj, uchar& value, const ArgInfo& info)
return ivalue != -1 || !PyErr_Occurred();
}
template<>
bool pyopencv_to(PyObject* obj, char& value, const ArgInfo& info)
{
if (!obj || obj == Py_None)
{
return true;
}
if (isBool(obj))
{
failmsg("Argument '%s' must be an integer, not bool", info.name);
return false;
}
if (PyArray_IsIntegerScalar(obj))
{
value = saturate_cast<char>(PyArray_PyIntAsInt(obj));
}
else
{
failmsg("Argument '%s' is required to be an integer", info.name);
return false;
}
return !CV_HAS_CONVERSION_ERROR(value);
}
template<>
PyObject* pyopencv_from(const double& value)
{
@@ -1484,357 +1535,12 @@ PyObject* pyopencv_from(const Point3d& p)
return Py_BuildValue("(ddd)", p.x, p.y, p.z);
}
template<typename _Tp> struct pyopencvVecConverter
{
typedef typename DataType<_Tp>::channel_type _Cp;
static inline bool copyOneItem(PyObject *obj, size_t start, int channels, _Cp * data)
{
for(size_t j = 0; (int)j < channels; j++ )
{
SafeSeqItem sub_item_wrap(obj, start + j);
PyObject* item_ij = sub_item_wrap.item;
if( PyInt_Check(item_ij))
{
int v = (int)PyInt_AsLong(item_ij);
if( v == -1 && PyErr_Occurred() )
return false;
data[j] = saturate_cast<_Cp>(v);
}
else if( PyLong_Check(item_ij))
{
int v = (int)PyLong_AsLong(item_ij);
if( v == -1 && PyErr_Occurred() )
return false;
data[j] = saturate_cast<_Cp>(v);
}
else if( PyFloat_Check(item_ij))
{
double v = PyFloat_AsDouble(item_ij);
if( PyErr_Occurred() )
return false;
data[j] = saturate_cast<_Cp>(v);
}
else
return false;
}
return true;
}
static bool to(PyObject* obj, std::vector<_Tp>& value, const ArgInfo& info)
{
if(!obj || obj == Py_None)
return true;
if (PyArray_Check(obj))
{
Mat m;
pyopencv_to(obj, m, info);
m.copyTo(value);
return true;
}
else if (PySequence_Check(obj))
{
const int type = traits::Type<_Tp>::value;
const int depth = CV_MAT_DEPTH(type), channels = CV_MAT_CN(type);
size_t i, n = PySequence_Size(obj);
value.resize(n);
for (i = 0; i < n; i++ )
{
SafeSeqItem item_wrap(obj, i);
PyObject* item = item_wrap.item;
_Cp* data = (_Cp*)&value[i];
if( channels == 2 && PyComplex_Check(item) )
{
data[0] = saturate_cast<_Cp>(PyComplex_RealAsDouble(item));
data[1] = saturate_cast<_Cp>(PyComplex_ImagAsDouble(item));
}
else if( channels > 1 )
{
if( PyArray_Check(item))
{
Mat src;
pyopencv_to(item, src, info);
if( src.dims != 2 || src.channels() != 1 ||
((src.cols != 1 || src.rows != channels) &&
(src.cols != channels || src.rows != 1)))
break;
Mat dst(src.rows, src.cols, depth, data);
src.convertTo(dst, type);
if( dst.data != (uchar*)data )
break;
}
else if (PySequence_Check(item))
{
if (!copyOneItem(item, 0, channels, data))
break;
}
else
{
break;
}
}
else if (channels == 1)
{
if (!copyOneItem(obj, i, channels, data))
break;
}
else
{
break;
}
}
if (i != n)
{
failmsg("Can't convert vector element for '%s', index=%d", info.name, i);
}
return i == n;
}
failmsg("Can't convert object to vector for '%s', unsupported type", info.name);
return false;
}
static PyObject* from(const std::vector<_Tp>& value)
{
if(value.empty())
return PyTuple_New(0);
int type = traits::Type<_Tp>::value;
int depth = CV_MAT_DEPTH(type), channels = CV_MAT_CN(type);
Mat src((int)value.size(), channels, depth, (uchar*)&value[0]);
return pyopencv_from(src);
}
};
template<typename _Tp>
bool pyopencv_to(PyObject* obj, std::vector<_Tp>& value, const ArgInfo& info)
{
return pyopencvVecConverter<_Tp>::to(obj, value, info);
}
template<typename _Tp>
PyObject* pyopencv_from(const std::vector<_Tp>& value)
{
return pyopencvVecConverter<_Tp>::from(value);
}
template<typename _Tp> static inline bool pyopencv_to_generic_vec(PyObject* obj, std::vector<_Tp>& value, const ArgInfo& info)
{
if(!obj || obj == Py_None)
return true;
if (!PySequence_Check(obj))
return false;
size_t n = PySequence_Size(obj);
value.resize(n);
for(size_t i = 0; i < n; i++ )
{
SafeSeqItem item_wrap(obj, i);
if(!pyopencv_to(item_wrap.item, value[i], info))
return false;
}
return true;
}
template<> inline bool pyopencv_to_generic_vec(PyObject* obj, std::vector<bool>& value, const ArgInfo& info)
{
if(!obj || obj == Py_None)
return true;
if (!PySequence_Check(obj))
return false;
size_t n = PySequence_Size(obj);
value.resize(n);
for(size_t i = 0; i < n; i++ )
{
SafeSeqItem item_wrap(obj, i);
bool elem{};
if(!pyopencv_to(item_wrap.item, elem, info))
return false;
value[i] = elem;
}
return true;
}
template<typename _Tp> static inline PyObject* pyopencv_from_generic_vec(const std::vector<_Tp>& value)
{
int i, n = (int)value.size();
PyObject* seq = PyList_New(n);
for( i = 0; i < n; i++ )
{
_Tp elem = value[i];
PyObject* item = pyopencv_from(elem);
if(!item)
break;
PyList_SetItem(seq, i, item);
}
if( i < n )
{
Py_DECREF(seq);
return 0;
}
return seq;
}
template<> inline PyObject* pyopencv_from_generic_vec(const std::vector<bool>& value)
{
int i, n = (int)value.size();
PyObject* seq = PyList_New(n);
for( i = 0; i < n; i++ )
{
bool elem = value[i];
PyObject* item = pyopencv_from(elem);
if(!item)
break;
PyList_SetItem(seq, i, item);
}
if( i < n )
{
Py_DECREF(seq);
return 0;
}
return seq;
}
template<std::size_t I = 0, typename... Tp>
inline typename std::enable_if<I == sizeof...(Tp), void>::type
convert_to_python_tuple(const std::tuple<Tp...>&, PyObject*) { }
template<std::size_t I = 0, typename... Tp>
inline typename std::enable_if<I < sizeof...(Tp), void>::type
convert_to_python_tuple(const std::tuple<Tp...>& cpp_tuple, PyObject* py_tuple)
{
PyObject* item = pyopencv_from(std::get<I>(cpp_tuple));
if (!item)
return;
PyTuple_SetItem(py_tuple, I, item);
convert_to_python_tuple<I + 1, Tp...>(cpp_tuple, py_tuple);
}
template<typename... Ts>
PyObject* pyopencv_from(const std::tuple<Ts...>& cpp_tuple)
{
size_t size = sizeof...(Ts);
PyObject* py_tuple = PyTuple_New(size);
convert_to_python_tuple(cpp_tuple, py_tuple);
size_t actual_size = PyTuple_Size(py_tuple);
if (actual_size < size)
{
Py_DECREF(py_tuple);
return NULL;
}
return py_tuple;
}
template<>
PyObject* pyopencv_from(const std::pair<int, double>& src)
{
return Py_BuildValue("(id)", src.first, src.second);
}
template<typename _Tp, typename _Tr> struct pyopencvVecConverter<std::pair<_Tp, _Tr> >
{
static bool to(PyObject* obj, std::vector<std::pair<_Tp, _Tr> >& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<std::pair<_Tp, _Tr> >& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<typename _Tp> struct pyopencvVecConverter<std::vector<_Tp> >
{
static bool to(PyObject* obj, std::vector<std::vector<_Tp> >& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<std::vector<_Tp> >& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<Mat>
{
static bool to(PyObject* obj, std::vector<Mat>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<Mat>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<UMat>
{
static bool to(PyObject* obj, std::vector<UMat>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<UMat>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<KeyPoint>
{
static bool to(PyObject* obj, std::vector<KeyPoint>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<KeyPoint>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<DMatch>
{
static bool to(PyObject* obj, std::vector<DMatch>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<DMatch>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<String>
{
static bool to(PyObject* obj, std::vector<String>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<String>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<> struct pyopencvVecConverter<RotatedRect>
{
static bool to(PyObject* obj, std::vector<RotatedRect>& value, const ArgInfo& info)
{
return pyopencv_to_generic_vec(obj, value, info);
}
static PyObject* from(const std::vector<RotatedRect>& value)
{
return pyopencv_from_generic_vec(value);
}
};
template<>
bool pyopencv_to(PyObject* obj, TermCriteria& dst, const ArgInfo& info)
{
@@ -1962,6 +1668,266 @@ PyObject* pyopencv_from(const Moments& m)
"nu30", m.nu30, "nu21", m.nu21, "nu12", m.nu12, "nu03", m.nu03);
}
template <typename Tp>
struct pyopencvVecConverter;
template <typename Tp>
bool pyopencv_to(PyObject* obj, std::vector<Tp>& value, const ArgInfo& info)
{
if (!obj || obj == Py_None)
{
return true;
}
return pyopencvVecConverter<Tp>::to(obj, value, info);
}
template <typename Tp>
PyObject* pyopencv_from(const std::vector<Tp>& value)
{
return pyopencvVecConverter<Tp>::from(value);
}
template <typename Tp>
static bool pyopencv_to_generic_vec(PyObject* obj, std::vector<Tp>& value, const ArgInfo& info)
{
if (!obj || obj == Py_None)
{
return true;
}
if (!PySequence_Check(obj))
{
failmsg("Can't parse '%s'. Input argument doesn't provide sequence protocol", info.name);
return false;
}
const size_t n = static_cast<size_t>(PySequence_Size(obj));
value.resize(n);
for (size_t i = 0; i < n; i++)
{
SafeSeqItem item_wrap(obj, i);
if (!pyopencv_to(item_wrap.item, value[i], info))
{
failmsg("Can't parse '%s'. Sequence item with index %lu has a wrong type", info.name, i);
return false;
}
}
return true;
}
template<> inline bool pyopencv_to_generic_vec(PyObject* obj, std::vector<bool>& value, const ArgInfo& info)
{
if (!obj || obj == Py_None)
{
return true;
}
if (!PySequence_Check(obj))
{
failmsg("Can't parse '%s'. Input argument doesn't provide sequence protocol", info.name);
return false;
}
const size_t n = static_cast<size_t>(PySequence_Size(obj));
value.resize(n);
for (size_t i = 0; i < n; i++)
{
SafeSeqItem item_wrap(obj, i);
bool elem{};
if (!pyopencv_to(item_wrap.item, elem, info))
{
failmsg("Can't parse '%s'. Sequence item with index %lu has a wrong type", info.name, i);
return false;
}
value[i] = elem;
}
return true;
}
template <typename Tp>
static PyObject* pyopencv_from_generic_vec(const std::vector<Tp>& value)
{
Py_ssize_t n = static_cast<Py_ssize_t>(value.size());
PySafeObject seq(PyTuple_New(n));
for (Py_ssize_t i = 0; i < n; i++)
{
PyObject* item = pyopencv_from(value[i]);
// If item can't be assigned - PyTuple_SetItem raises exception and returns -1.
if (!item || PyTuple_SetItem(seq, i, item) == -1)
{
return NULL;
}
}
return seq.release();
}
template<> inline PyObject* pyopencv_from_generic_vec(const std::vector<bool>& value)
{
Py_ssize_t n = static_cast<Py_ssize_t>(value.size());
PySafeObject seq(PyTuple_New(n));
for (Py_ssize_t i = 0; i < n; i++)
{
bool elem = value[i];
PyObject* item = pyopencv_from(elem);
// If item can't be assigned - PyTuple_SetItem raises exception and returns -1.
if (!item || PyTuple_SetItem(seq, i, item) == -1)
{
return NULL;
}
}
return seq.release();
}
template<std::size_t I = 0, typename... Tp>
inline typename std::enable_if<I == sizeof...(Tp), void>::type
convert_to_python_tuple(const std::tuple<Tp...>&, PyObject*) { }
template<std::size_t I = 0, typename... Tp>
inline typename std::enable_if<I < sizeof...(Tp), void>::type
convert_to_python_tuple(const std::tuple<Tp...>& cpp_tuple, PyObject* py_tuple)
{
PyObject* item = pyopencv_from(std::get<I>(cpp_tuple));
if (!item)
return;
PyTuple_SetItem(py_tuple, I, item);
convert_to_python_tuple<I + 1, Tp...>(cpp_tuple, py_tuple);
}
template<typename... Ts>
PyObject* pyopencv_from(const std::tuple<Ts...>& cpp_tuple)
{
size_t size = sizeof...(Ts);
PyObject* py_tuple = PyTuple_New(size);
convert_to_python_tuple(cpp_tuple, py_tuple);
size_t actual_size = PyTuple_Size(py_tuple);
if (actual_size < size)
{
Py_DECREF(py_tuple);
return NULL;
}
return py_tuple;
}
template <typename Tp>
struct pyopencvVecConverter
{
typedef typename std::vector<Tp>::iterator VecIt;
static bool to(PyObject* obj, std::vector<Tp>& value, const ArgInfo& info)
{
if (!PyArray_Check(obj))
{
return pyopencv_to_generic_vec(obj, value, info);
}
// If user passed an array it is possible to make faster conversions in several cases
PyArrayObject* array_obj = reinterpret_cast<PyArrayObject*>(obj);
const NPY_TYPES target_type = asNumpyType<Tp>();
const NPY_TYPES source_type = static_cast<NPY_TYPES>(PyArray_TYPE(array_obj));
if (target_type == NPY_OBJECT)
{
// Non-planar arrays representing objects (e.g. array of N Rect is an array of shape Nx4) have NPY_OBJECT
// as their target type.
return pyopencv_to_generic_vec(obj, value, info);
}
if (PyArray_NDIM(array_obj) > 1)
{
failmsg("Can't parse %dD array as '%s' vector argument", PyArray_NDIM(array_obj), info.name);
return false;
}
if (target_type != source_type)
{
// Source type requires conversion
// Allowed conversions for target type is handled in the corresponding pyopencv_to function
return pyopencv_to_generic_vec(obj, value, info);
}
// For all other cases, all array data can be directly copied to std::vector data
// Simple `memcpy` is not possible because NumPy array can reference a slice of the bigger array:
// ```
// arr = np.ones((8, 4, 5), dtype=np.int32)
// convertible_to_vector_of_int = arr[:, 0, 1]
// ```
value.resize(static_cast<size_t>(PyArray_SIZE(array_obj)));
const npy_intp item_step = PyArray_STRIDE(array_obj, 0) / PyArray_ITEMSIZE(array_obj);
const Tp* data_ptr = static_cast<Tp*>(PyArray_DATA(array_obj));
for (VecIt it = value.begin(); it != value.end(); ++it, data_ptr += item_step) {
*it = *data_ptr;
}
return true;
}
static PyObject* from(const std::vector<Tp>& value)
{
if (value.empty())
{
return PyTuple_New(0);
}
return from(value, ::traits::IsRepresentableAsMatDataType<Tp>());
}
private:
static PyObject* from(const std::vector<Tp>& value, ::traits::FalseType)
{
// Underlying type is not representable as Mat Data Type
return pyopencv_from_generic_vec(value);
}
static PyObject* from(const std::vector<Tp>& value, ::traits::TrueType)
{
// Underlying type is representable as Mat Data Type, so faster return type is available
typedef DataType<Tp> DType;
typedef typename DType::channel_type UnderlyingArrayType;
// If Mat is always exposed as NumPy array this code path can be reduced to the following snipped:
// Mat src(value);
// PyObject* array = pyopencv_from(src);
// return PyArray_Squeeze(reinterpret_cast<PyArrayObject*>(array));
// This puts unnecessary restrictions on Mat object those might be avoided without losing the performance.
// Moreover, this version is a bit faster, because it doesn't create temporary objects with reference counting.
const NPY_TYPES target_type = asNumpyType<UnderlyingArrayType>();
const int cols = DType::channels;
PyObject* array = NULL;
if (cols == 1)
{
npy_intp dims = static_cast<npy_intp>(value.size());
array = PyArray_SimpleNew(1, &dims, target_type);
}
else
{
npy_intp dims[2] = {static_cast<npy_intp>(value.size()), cols};
array = PyArray_SimpleNew(2, dims, target_type);
}
if(!array)
{
// NumPy arrays with shape (N, 1) and (N) are not equal, so correct error message should distinguish
// them too.
String shape;
if (cols > 1)
{
shape = format("(%d x %d)", static_cast<int>(value.size()), cols);
}
else
{
shape = format("(%d)", static_cast<int>(value.size()));
}
const String error_message = format("Can't allocate NumPy array for vector with dtype=%d and shape=%s",
static_cast<int>(target_type), shape.c_str());
emit_failmsg(PyExc_MemoryError, error_message.c_str());
return array;
}
// Fill the array
PyArrayObject* array_obj = reinterpret_cast<PyArrayObject*>(array);
UnderlyingArrayType* array_data = static_cast<UnderlyingArrayType*>(PyArray_DATA(array_obj));
// if Tp is representable as Mat DataType, so the following cast is pretty safe...
const UnderlyingArrayType* value_data = reinterpret_cast<const UnderlyingArrayType*>(value.data());
memcpy(array_data, value_data, sizeof(UnderlyingArrayType) * value.size() * static_cast<size_t>(cols));
return array;
}
};
static int OnError(int status, const char *func_name, const char *err_msg, const char *file_name, int line, void *userdata)
{
PyGILState_STATE gstate;