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Commit 1c3b0113 authored by Patrik Huber's avatar Patrik Huber
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Removed old cv::Vec/Mat bindings in favour of new transparent bindings

parent 299683e4
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python/generate-python-bindings.cpp
View file @ 1c3b0113
...@@ -33,6 +33,7 @@ ...@@ -33,6 +33,7 @@
#include "pybind11/pybind11.h" #include "pybind11/pybind11.h"
#include "pybind11/stl.h" #include "pybind11/stl.h"
#include "pybind11_glm.hpp" #include "pybind11_glm.hpp"
#include "pybind11_opencv.hpp"
#include <iostream> #include <iostream>
#include <stdexcept> #include <stdexcept>
...@@ -49,156 +50,6 @@ using namespace eos; ...@@ -49,156 +50,6 @@ using namespace eos;
PYBIND11_PLUGIN(eos) { PYBIND11_PLUGIN(eos) {
py::module eos_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::module eos_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::buffer b) {
py::buffer_info info = b.request();
if (info.ndim != 1)
throw std::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)
throw std::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)
throw std::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)
throw std::runtime_error("shape[0] is " + std::to_string(info.shape[0]) + ", please hand a buffer with 2 entries to create a Vec2f.");
if (info.format == py::format_descriptor<float>::format())
{
cv::Mat temp(1, 2, CV_32FC1, info.ptr);
//std::cout << temp << std::endl;
new (&vec) cv::Vec2f(temp);
}
else {
throw std::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 {
return py::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::buffer b) {
py::buffer_info info = b.request();
if (info.ndim != 1)
throw std::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)
throw std::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)
throw std::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)
throw std::runtime_error("shape[0] is " + std::to_string(info.shape[0]) + ", please hand a buffer with 4 entries to create a Vec4f.");
if (info.format == py::format_descriptor<float>::format())
{
cv::Mat temp(1, 4, CV_32FC1, info.ptr);
//std::cout << temp << std::endl;
new (&vec) cv::Vec4f(temp);
}
else {
throw std::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 {
return py::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::buffer b) {
py::buffer_info info = b.request();
if (info.ndim != 2)
throw std::runtime_error("Buffer ndim is " + std::to_string(info.ndim) + ", only buffer dimension == 2 is currently supported.");
if (info.strides.size() != 2)
throw std::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)
throw std::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.");
if (info.format == py::format_descriptor<float>::format())
{
new (&mat) cv::Mat(info.shape[0], info.shape[1], CV_32FC1, info.ptr); // uses AUTO_STEP
}
else if (info.format == py::format_descriptor<double>::format())
{
new (&mat) cv::Mat(info.shape[0], info.shape[1], CV_64FC1, info.ptr); // uses AUTO_STEP
}
else {
throw std::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::string error_msg("Only continuous (contiguous) cv::Mat objects are currently supported.");
std::cout << error_msg << std::endl;
throw std::runtime_error(error_msg);
}
// Note: Also stride/step should be 1 too, but I think this is covered by isContinuous().
auto dimensions = mat.dims;
if (dimensions != 2)
{
std::string error_msg("Only cv::Mat objects with dims == 2 are currently supported.");
std::cout << error_msg << std::endl;
throw std::runtime_error(error_msg);
}
if (mat.channels() != 1)
{
std::string error_msg("Only cv::Mat objects with channels() == 1 are currently supported.");
std::cout << error_msg << std::endl;
throw std::runtime_error(error_msg);
}
std::size_t rows = mat.rows;
std::size_t cols = mat.cols;
if (mat.type() == CV_32F) {
return py::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::string error_msg("Only the cv::Mat type CV_32F is currently supported. If needed, it would be easy to add CV_8U and CV_64F.");
std::cout << error_msg << std::endl;
throw std::runtime_error(error_msg);
}
// Will never reach here.
})
;
/** /**
* Bindings for the eos::core namespace: * Bindings for the eos::core namespace:
* - LandmarkMapper * - LandmarkMapper
......
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