#define PY_SSIZE_T_CLEAN #include #include #include #include #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION #include "numpy/arrayobject.h" #include extern "C" { // Simple addition test function (return = in1 + in2) static PyObject* test_func(PyObject* self, PyObject* args) { int input1, input2; if (!PyArg_ParseTuple(args, "ii", &input1, &input2)) { // Arguments are 2 integer values ("ii") return nullptr; } PyObject *return_value = PyLong_FromLong(input1 + input2); // Create object to return return return_value; } // Simple image processing function (Inverse image color) static PyObject* test_image_processing(PyObject* self, PyObject* args) { PyArrayObject* input_image; PyObject* output_image; if(!PyArg_ParseTuple(args, "O!", &PyArray_Type, &input_image)) { // Argument is an Numpy array object return nullptr; } output_image = PyArray_NewLikeArray(input_image, NPY_ANYORDER, NULL, 0); // Create object to return int ndim = PyArray_NDIM(input_image); // Number of dimensions of the input Numpy array npy_intp *shape; shape = PyArray_SHAPE(input_image); // Shape of the input Numpy array (npy_intp[]) // Obtain data buffer pointers char* in_buf = static_cast(PyArray_DATA(input_image)); // PyArray_DATA() will return void* char* out_buf = static_cast(PyArray_DATA(reinterpret_cast(output_image))); // Image processing size_t C = shape[2]; size_t W = shape[1]; size_t H = shape[0]; for(size_t y=0; y(PyArray_DATA(input_image)); // PyArray_DATA() will return void* // Image processing with OpenCV cv::Mat in_mat(shape[0] /*Width(rows)*/, shape[1] /*Height(cols)*/, CV_8UC3, in_buf); // Input cv::Mat generated from input Numpy object cv::Mat out_mat; // Mat object to store final image cv::Mat channels[3]; // Mat object for channel extraction cv::cvtColor(in_mat, in_mat, cv::COLOR_BGR2GRAY); // Color -> Gray scale cv::split(in_mat, channels); // Channel extraction. packed BGR -> [B, G, R] cv::Canny(channels[0], out_mat, th1, th2); // Canny edge detection npy_intp out_shape[] = { out_mat.rows, out_mat.cols, out_mat.channels() }; PyObject* result = PyArray_SimpleNew(3, out_shape, NPY_UINT8); // Create a Numpy object to return char* out_buf = static_cast(PyArray_DATA(reinterpret_cast(result))); // Obtain data buffer pointer of the final image memcpy(out_buf, out_mat.data, out_shape[0] * out_shape[1] * out_shape[2]); // Copy data buffer return result; // Return created Numpy object } // Numpy array attribute extraction test function static PyObject* npy_array_test(PyObject* self, PyObject* args) { PyArrayObject* input_image; if(!PyArg_ParseTuple(args, "O!", &PyArray_Type, &input_image)) { // Argument is a Numpy object return nullptr; } size_t ndims = PyArray_NDIM(input_image); // Number of dimensions std::cout << "#Dims: " << PyArray_NDIM(input_image) << std::endl; npy_intp* shape = PyArray_SHAPE(input_image); // Shape for(size_t i=0; i(PyArray_DATA(input_image)); // PyArray_DATA() will return void* // Show first 10 items of the Numpy array int bytes = PyArray_NBYTES(input_image); int disp_size = bytes<10 ? bytes : 10; for(size_t i=0; i(test_func), METH_VARARGS, "test method function of test module"}, {"test_image_processing", static_cast(test_image_processing), METH_VARARGS, "test image processing function"}, {"test_image_processing_OCV", static_cast(test_image_processing_OCV), METH_VARARGS, "test image processing function"}, {"npy_array_test", static_cast(npy_array_test), METH_VARARGS, "test numpy array handling test"}, {NULL, NULL, 0, NULL} }; // Module definition table PyModuleDef test_module = { PyModuleDef_HEAD_INIT, "python_cpp_module", "test module", -1, method_table }; // Initialize and register module function // Function name must be 'PyInit_'+module name // This function must be the only *non-static* function in the source code PyMODINIT_FUNC PyInit_python_cpp_module(void) { import_array(); // Required to receive Numpy object as arguments if (PyErr_Occurred()) { return nullptr; } return PyModule_Create(&test_module); } } // extern "C"