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@Xonxt
Last active February 24, 2023 02:03
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Sending a cv::Mat from C++ to a Python script
/*
This requires adding the "include" directory of your Python installation to the include diretories
of your project, e.g., in Visual Studio you'd add `C:\Program Files\Python36\include`.
You also need to add the 'include' directory of your NumPy package, e.g.
`C:\Program Files\PythonXX\Lib\site-packages\numpy\core\include`.
Additionally, you need to link your "python3#.lib" library, e.g. `C:\Program Files\Python3X\libs\python3X.lib`.
*/
// python bindings
#include "Python.h"
#include "numpy/arrayobject.h"
#include <iostream>
#include "opencv2/opencv.hpp"
// references to all the functions
PyObject *m_PyDict, *m_PyFooBar;
// reference to the Pyhton module
PyObject* m_PyModule;
int main(int argc, char** argv) {
// initialize Python embedding
Py_Initialize();
// set the command line arguments (can be crucial for some python-packages, like tensorflow)
PySys_SetArgv(argc, (wchar_t**) argv);
// add the current folder to the Python's PATH
PyObject *sys_path = PySys_GetObject("path");
PyList_Append(sys_path, PyUnicode_FromString("."));
// this macro is defined by NumPy and must be included
import_array1(-1);
// load our python script (see the gist at the bottom)
// use the script's filename, sans the extension
m_PyModule = PyImport_ImportModule("pythonScript");
if (m_PyModule != NULL)
{
// get dictionary of all available entities in the module
m_PyDict = PyModule_GetDict(m_PyModule);
// grab the functions we are interested in (using its name)
m_PyFooBar = PyDict_GetItemString(m_PyDict, "foo_bar");
// execute the function
if (m_PyFooBar != NULL)
{
// take a cv::Mat object from somewhere (we'll just create an empty one)
cv::Mat img = cv::Mat::zeros(480, 640, CV_8U);
// total number of elements (here it's a greyscale 640x480)
const unsigned int nElem = 640 * 480;
// create an array of apropriate datatype
uchar* m = new uchar[nElem];
// copy the data from the cv::Mat object into the array
std::memcpy(m, img.data, nElem * sizeof(uchar));
// the dimensions of the matrix
npy_intp mdim[] = { 480, 640 };
// convert the cv::Mat to numpy.array
PyObject* mat = PyArray_SimpleNewFromData(2, mdim, NPY_UINT8, (void*) m);
// create a Python-tuple of arguments for the function call
// "()" means "tuple". "O" means "object"
PyObject* args = Py_BuildValue("(O)", mat);
// if we want several arguments, we can write ("i" means "integer"):
// PyObject* args = Py_BuildValue("(OOi)", mat, mat, 123);
// to send two images and an integer, equivalent to Python's (mat, mat, 123) tuple
// see detailed explanation here: https://docs.python.org/2.0/ext/buildValue.html
// execute the function
PyObject* result = PyEval_CallObject(m_PyFooBar, args);
// process the result
// ...
// decrement the object references
Py_XDECREF(mat);
Py_XDECREF(result);
Py_XDECREF(args);
delete[] m;
}
}
else
{
std::cerr << "Failed to load the Python module!" << std::endl;
PyErr_Print();
}
return 0;
}
// same example, but for a 3-channel RGB image.
// python bindings
#include "Python.h"
#include "numpy/arrayobject.h"
#include <iostream>
#include "opencv2/opencv.hpp"
// for the references to all the functions
PyObject *m_PyDict, *m_PyFooBar;
// for the reference to the Pyhton module
PyObject* m_PyModule;
int main(int argc, char** argv) {
// initialize everything (see gist above for details)
Py_Initialize();
PySys_SetArgv(argc, (wchar_t**)argv);
PyObject *sys_path = PySys_GetObject("path");
PyList_Append(sys_path, PyUnicode_FromString("."));
import_array1(-1);
m_PyModule = PyImport_ImportModule("pythonScript");
if (m_PyModule != NULL)
{
// get dictionary of available items in the module
m_PyDict = PyModule_GetDict(m_PyModule);
// grab the functions we are interested in
m_PyFooBar = PyDict_GetItemString(m_PyDict, "foo_bar");
// execute the function
if (m_PyFooBar != NULL)
{
// take a cv::Mat object from somewhere (we'll just create one)
cv::Mat img = cv::Mat::zeros(480, 640, CV_8UC3);
// total number of elements (here it's an RGB image of size 640x480)
const unsigned int nElem = 640 * 480 * 3;
// create an array of apropriate datatype
uchar* m = new uchar[nElem];
// copy the data from the cv::Mat object into the array
std::memcpy(m, img.data, nElem * sizeof(uchar));
// the dimensions of the matrix
npy_intp mdim[] = { 480, 640, 3 };
// convert the cv::Mat to numpy.array
PyObject* mat = PyArray_SimpleNewFromData(3, mdim, NPY_UINT8, (void*) m);
// create a Python-tuple of arguments for the function call
// "()" means "tuple". "O" means "object"
PyObject* args = Py_BuildValue("(O)", mat);
// execute the function
PyObject* result = PyEval_CallObject(m_PyFooBar, args);
// process the result
// ...
// decrement the object references
Py_XDECREF(mat);
Py_XDECREF(result);
Py_XDECREF(args);
delete[] m;
}
}
else
{
std::cerr << "Failed to load the Python module!" << std::endl;
PyErr_Print();
}
return 0;
}
import cv2
import numpy as np
# define the function that we will call from the C++ code
def foo_bar(img=None):
if img is not None:
cv2.imshow("image in python", img)
@IricsDo
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IricsDo commented Oct 24, 2021

Yes. I already installed numpy package in python. That why i can run your code in VS 2017. Now i want run your code in VS 2019 but i have the problem.
Thanks you response for me.

@IricsDo
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IricsDo commented Oct 25, 2021

Yes. I already installed numpy package in python. That why i can run your code in VS 2017. Now i want run your code in VS 2019 but i have the problem. Thanks you response for me.

I have more information, now i return VS 2017 and this code have the same problem :)) . I install two Visual Studio together 2017 and 2019. First 2017 and second 2019.

@SabraHashemi
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SabraHashemi commented Oct 25, 2021

https://gist.github.com/Xonxt/26d2a9ac6c56505d0896822ede99a646#gistcomment-3723333

I tested it again and I think it didn't have any overhead anymore. thanks for the reply.
@Xonxt

@IricsDo
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IricsDo commented Mar 18, 2022

Hi guys, long time no reply :)
I have a new question for you. How i can choose enviromnent for python? It's mean when i call python from c++ script? How to choose env to run python script.
Example: I using ubuntu 18.04 OS . I have 2 virtual environment ( anaconda and venv) and 1 real environment python3.6.9 default of ubuntu (python default). How to i know what env i run python code when call from c++ and how to change it? is it based on python.h (python.a in linux). I think this is similar on window with venv and anaconda and python when install from offcial web site of python.

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