py::moduleeos_module("eos","Python bindings for the eos 3D Morphable Face Model fitting library.\n\nFor an overview of the functionality, see the documentation of the submodules. For the full documentation, see the C++ doxygen documentation.");
py::moduleeos_module("eos","Python bindings for the eos 3D Morphable Face Model fitting library.\n\nFor an overview of the functionality, see the documentation of the submodules. For the full documentation, see the C++ doxygen documentation.");
/**
* General bindings, for OpenCV vector types and cv::Mat:
* - cv::Vec2f
* - cv::Vec4f
* - cv::Mat (only 1-channel matrices and only conversion of CV_32F C++ matrices to Python, and conversion of CV_32FC1 and CV_64FC1 matrices from Python to C++)
*/
py::class_<cv::Vec2f>(eos_module,"Vec2f","Wrapper for OpenCV's cv::Vec2f type.")
.def("__init__",[](cv::Vec2f&vec,py::bufferb){
py::buffer_infoinfo=b.request();
if(info.ndim!=1)
throwstd::runtime_error("Buffer ndim is "+std::to_string(info.ndim)+", please hand a buffer with dimension == 1 to create a Vec2f.");
if(info.strides.size()!=1)
throwstd::runtime_error("strides.size() is "+std::to_string(info.strides.size())+", please hand a buffer with strides.size() == 1 to create a Vec2f.");
// Todo: Should add a check that checks for default stride sizes, everything else would not work yet I think.
if(info.shape.size()!=1)
throwstd::runtime_error("shape.size() is "+std::to_string(info.shape.size())+", please hand a buffer with shape dimension == 1 to create a Vec2f.");
if(info.shape[0]!=2)
throwstd::runtime_error("shape[0] is "+std::to_string(info.shape[0])+", please hand a buffer with 2 entries to create a Vec2f.");
throwstd::runtime_error("Not given a buffer of type float - please hand a buffer of type float to create a Vec2f.");
}
})
.def_buffer([](cv::Vec2f&vec)->py::buffer_info{
returnpy::buffer_info(
&vec.val,/* Pointer to buffer */
sizeof(float),/* Size of one scalar */
py::format_descriptor<float>::format(),/* Python struct-style format descriptor */
2,/* Number of dimensions */
{vec.rows,vec.cols},/* Buffer dimensions */
{sizeof(float),/* Strides (in bytes) for each index */
sizeof(float)}/* => both sizeof(float), since the data is hold in an array, i.e. contiguous memory */
);
});
py::class_<cv::Vec4f>(eos_module,"Vec4f","Wrapper for OpenCV's cv::Vec4f type.")
.def("__init__",[](cv::Vec4f&vec,py::bufferb){
py::buffer_infoinfo=b.request();
if(info.ndim!=1)
throwstd::runtime_error("Buffer ndim is "+std::to_string(info.ndim)+", please hand a buffer with dimension == 1 to create a Vec4f.");
if(info.strides.size()!=1)
throwstd::runtime_error("strides.size() is "+std::to_string(info.strides.size())+", please hand a buffer with strides.size() == 1 to create a Vec4f.");
// Todo: Should add a check that checks for default stride sizes, everything else would not work yet I think.
if(info.shape.size()!=1)
throwstd::runtime_error("shape.size() is "+std::to_string(info.shape.size())+", please hand a buffer with shape dimension == 1 to create a Vec4f.");
if(info.shape[0]!=4)
throwstd::runtime_error("shape[0] is "+std::to_string(info.shape[0])+", please hand a buffer with 4 entries to create a Vec4f.");
throwstd::runtime_error("Not given a buffer of type float - please hand a buffer of type float to create a Vec4f.");
}
})
.def_buffer([](cv::Vec4f&vec)->py::buffer_info{
returnpy::buffer_info(
&vec.val,/* Pointer to buffer */
sizeof(float),/* Size of one scalar */
py::format_descriptor<float>::format(),/* Python struct-style format descriptor */
2,/* Number of dimensions */
{vec.rows,vec.cols},/* Buffer dimensions */
{sizeof(float),/* Strides (in bytes) for each index */
sizeof(float)}/* => both sizeof(float), since the data is hold in an array, i.e. contiguous memory */
);
});
py::class_<cv::Mat>(eos_module,"Mat","Wrapper for OpenCV's cv::Mat type (currently only 1-channel matrices are supported and only conversion of CV_32F C++ matrices to Python, and conversion of CV_32FC1 and CV_64FC1 matrices from Python to C++).")
// This adds support for creating eos.Mat objects in Python from buffers like NumPy arrays:
.def("__init__",[](cv::Mat&mat,py::bufferb){
py::buffer_infoinfo=b.request();
if(info.ndim!=2)
throwstd::runtime_error("Buffer ndim is "+std::to_string(info.ndim)+", only buffer dimension == 2 is currently supported.");
if(info.strides.size()!=2)
throwstd::runtime_error("strides.size() is "+std::to_string(info.strides.size())+", only strides.size() == 2 is currently supported.");
// Todo: Should add a check that checks for default stride sizes, everything else would not work yet I think.
if(info.shape.size()!=2)
throwstd::runtime_error("shape.size() is "+std::to_string(info.shape.size())+", only shape dimensions of == 2 are currently supported - i.e. only 2-dimensional matrices with rows and colums.");
throwstd::runtime_error("Only the cv::Mat types CV_32FC1 and CV_64FC1 are currently supported. If needed, it should not be too hard to add other types.");
}
})
// This gives cv::Mat a Python buffer interface, so the data can be used as NumPy array in Python:
.def_buffer([](cv::Mat&mat)->py::buffer_info{
// Note: Exceptions within def_buffer don't seem to be shown in Python, use cout for now.
if(!mat.isContinuous())
{
std::stringerror_msg("Only continuous (contiguous) cv::Mat objects are currently supported.");
std::cout<<error_msg<<std::endl;
throwstd::runtime_error(error_msg);
}
// Note: Also stride/step should be 1 too, but I think this is covered by isContinuous().
autodimensions=mat.dims;
if(dimensions!=2)
{
std::stringerror_msg("Only cv::Mat objects with dims == 2 are currently supported.");
std::cout<<error_msg<<std::endl;
throwstd::runtime_error(error_msg);
}
if(mat.channels()!=1)
{
std::stringerror_msg("Only cv::Mat objects with channels() == 1 are currently supported.");
std::cout<<error_msg<<std::endl;
throwstd::runtime_error(error_msg);
}
std::size_trows=mat.rows;
std::size_tcols=mat.cols;
if(mat.type()==CV_32F){
returnpy::buffer_info(
mat.data,/* Pointer to buffer */
sizeof(float),/* Size of one scalar */
py::format_descriptor<float>::format(),/* Python struct-style format descriptor */
dimensions,/* Number of dimensions */
{rows,cols},/* Buffer dimensions */
{sizeof(float)*cols,/* Strides (in bytes) for each index */
sizeof(float)}// this way is correct for row-major memory layout (OpenCV)
);
}
else{
std::stringerror_msg("Only the cv::Mat type CV_32F is currently supported. If needed, it would be easy to add CV_8U and CV_64F.");