C++ 调用 Python 脚本，并把 cv::Mat 类型传参到 Python 端

约定不等于承诺〃 2022-11-21 04:14 345阅读 0赞

# C++ 调用 Python 脚本，并把 cv::Mat 类型传参到 Python 端 #

## 前言 ##

查看了很多参考，最后找到一个完整的示例并且跑通，在开始这个任务之前，首先应该确保你的环境是没有问题的，比如：

*  C++ 和 Python 之间可以传递简单类型的参数
 *  C++ 端独立通过 opencv 加载图像是没有问题的
 *  Python 端 import cv2 独立加载图像是没有问题的

具备上面这些条件后，可以参考下面的代码，将 cv::Mat 类型的参数传递到 Python 端。

## 代码 ##

这部分主要参考 [sending Mat][]。

C++ 端需要借助 numpy，所以也需要配置好 numpy 的头文件位置。

C++ code

#include "Python.h"
    #include "numpy/arrayobject.h"
    #include <opencv2/opencv.hpp>
    
    #include <iostream>
    
    using namespace std;
    // for the references to all the functions
    PyObject *m_PyDict, *m_PyFooBar;
    
    // for the reference to the Pyhton module
    PyObject* m_PyModule;
    
    int main() {
    
      Py_Initialize();
    //  PySys_SetArgv(argc, (wchar_t**)argv);
      PyRun_SimpleString("import sys");
      PyRun_SimpleString("sys.path.append('./')");
      PyRun_SimpleString("sys.path.append('/home/tt/test')");
      PyObject *sys_path = PySys_GetObject("path");
      PyList_Append(sys_path, PyUnicode_FromString("."));
    
      // this macro is defined be NumPy and must be included
      import_array1(-1);
    
      m_PyModule = PyImport_ImportModule("cal");
    
      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);
          cv::Mat img = cv::imread("/home/tt/test/1.png");
          int r = img.rows;
          int c = img.cols;
          int chnl = img.channels();
          // total number of elements (here it's an RGB image of size 640x480)
          int nElem = r * c * chnl;
    
          // 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[] = { r, c, chnl};
    
          // convert the cv::Mat to numpy.array
          PyObject* mat = PyArray_SimpleNewFromData(chnl, 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;
    }

Python code

def foo_bar(img=None):
        if img is not None:
           cv2.imshow("image in python", img)
           cv2.imwrite("/home/tt/test/111.png", img)
           cv2.waitKey(0)

[sending Mat]: https://gist.github.com/Xonxt/26d2a9ac6c56505d0896822ede99a646