【PyBind11+anaconda+opencv+windows11+cmake+wsl+vscode】从入门到跑通。构建基于opencv c++的python package

如何安装请详见上文
【PyBind11+anaconda+opencv+windows11+cmake+wsl+vscode】从入门到跑通。构建基于opencv c++的python接口_子韵如初的博客-CSDN博客w不需要安装啥x11 、 xming直接mobxterm可以搞定点击右上角的X server打开可视化服务器然后 apt install x11-apps -yxclock 搞定从mobxterm可以看到display的端口X11显示可视化的原理是就是通过X协议，类似于http对linux于windows上进行通信。那么他们通信的ip地址就是这个DISPLAY=localhost:10.0比如一个XClinet要在屏幕上输出一个圆，X应用程序只负责...https://blog.csdn.net/weixin_43953700/article/details/123760942计算机视觉-Paper&Code - 知乎V100 is all u needhttps://www.zhihu.com/column/c_1488286320929333249
第一步：首先在C/C++ IDE中编写C/C++函数，然后采用pybind11封装为python可调用的包装函数，之后采用C/C++编译器编译器生成.pyd文件

第二步：将生成的.pyd文件复制到python工程中，之后作为python module import导入使用

存在的问题不同操作系统下直接调用生成的pyd可能会出错，不能跨平台调用
在上述过程中，pyd动态链接库的生成是在本地PC上，但是如果想在不同的操作系统、硬件平台上调用之前生成的pyd，显然是会出错的。比如在windows上编译生成了一个python扩展.pyd, 但是Ubuntu系统想调用这个python扩展就不行了。
解决方案为了使得C/C++创建的python扩展可以跨平台使用，那么最简单的办法就是直接发布源码，然后在该操作系统、硬件平台上编译生成python扩展。
因此本节内容利用python setuptools 方式实现
首先配置cmake编译不依赖外部工程链接 ex.cpp
#include#include#include#includenamespace py = pybind11;class Matrix{public:Matrix() {};Matrix(int rows, int cols) {this->m_rows = rows;this->m_cols = cols;m_data = https://tazarkount.com/read/new float[rows*cols];}~Matrix() {};private:int m_rows;int m_cols;float* m_data;public:float* data() { return m_data; };int rows() { return m_rows; };int cols() { return m_cols; };};void save_2d_numpy_array(py::array_t a, std::string file_name) {std::ofstream out;out.open(file_name, std::ios::out);std::cout << a.ndim() << std::endl;for (int i = 0; i < a.ndim(); i++){std::cout << a.shape()[i] << std::endl;}for (int i = 0; i < a.shape()[0]; i++){for (int j = 0; j < a.shape()[1]; j++){if (j == a.shape()[1]-1){//访问读取,索引 numpy.ndarray 中的元素out << a.at(i, j)<< std::endl;}else {out << a.at(i, j) << " ";}}}}PYBIND11_MODULE(numpy_demo, m) {m.doc() = "Simple numpy demo";py::class_(m,"Matrix",py::buffer_protocol()).def_buffer([](Matrix& mm)->py::buffer_info {return py::buffer_info(mm.data(),//Pointer to buffer, 数据指针sizeof(float),//Size of one scalar, 每个元素大小(byte)py::format_descriptor::format(), //python struct-style foramt descriptor2,//Number of dims, 维度{mm.rows(), mm.cols()}, //strides (in bytes){sizeof(float) * mm.cols(),sizeof(float)});});m.def("save_2d_numpy_array", &save_2d_numpy_array);}
setup.py使用pip安装install，生成numpy_demo.cpython-38-x86_64-linux-gnu.so
python setup.py build_ext --inplacebuild_ext: 给python编译一个c、c++的拓展-–inplace: 忽略build-lib，将编译后的扩展放到源目录中，与纯Python模块放在一起 from setuptools import setupfrom setuptools import Extensionexample_module = Extension(name='numpy_demo',# 模块名称sources=['ex.cpp'],# 源码include_dirs=[r'/root/anaconda3/envs/py3/lib/python3.8/site-packages/pybind11/include'])setup(ext_modules=[example_module])# build_ext:build C/C++ extensions (compile/link to build directory)，给python编译一个c、c++的拓展# –inplace:ignore build-lib and put compiled extensions into the source directory alongside your pure Python modules，忽略build-lib，将编译后的扩展放到源目录中，与纯Python模块放在一起# python setup.py build_ext --inplace test.py测试
import numpy as npimport numpy_demo from numpy_demo import Matrixres = numpy_demo.save_2d_numpy_array(np.zeros(shape=[4,7], dtype=np.float32), './data.dat')print(Matrix.__dict__)print(Matrix)
如果需要引用opencv怎么做上面c++的拓展，只是使用了pybind11
因此继续编辑c++代码
main.cpp
#include#include#include#include#include#include#include"wrapper.h"namespace py = pybind11;py::array_t test_rgb_to_gray(py::array_t& input) {cv::Mat img_rgb = numpy_uint8_3c_to_cv_mat(input);cv::Mat dst;cv::cvtColor(img_rgb, dst, cv::COLOR_RGB2GRAY);return cv_mat_uint8_1c_to_numpy(dst);}/*@return Python list*/py::list test_pyramid_image(py::array_t& input) {cv::Mat src = https://tazarkount.com/read/numpy_uint8_1c_to_cv_mat(input);std::vector dst;cv::buildPyramid(src, dst, 4);py::list out;for (int i = 0; i < dst.size(); i++){out.append>(cv_mat_uint8_1c_to_numpy(dst.at(i)));}return out;}PYBIND11_MODULE(cv_demo1, m) {m.doc() = "Simple opencv demo";m.def("test_rgb_to_gray1", &test_rgb_to_gray);m.def("test_gray_canny1", &test_gray_canny);m.def("test_pyramid_image1", &test_pyramid_image);} wrapper.h
#ifndef WRAPPER_H_#include#include#includenamespace py = pybind11;cv::Mat numpy_uint8_1c_to_cv_mat(py::array_t& input);cv::Mat numpy_uint8_3c_to_cv_mat(py::array_t& input);py::array_t cv_mat_uint8_1c_to_numpy(cv::Mat & input);py::array_t cv_mat_uint8_3c_to_numpy(cv::Mat & input);#endif // !WRAPPER_H_
wrapper.?????cpp
#include"wrapper.h"#include cv::Mat numpy_uint8_1c_to_cv_mat(py::array_t& input) {if (input.ndim() != 2)throw std::runtime_error("1-channel image must be 2 dims ");py::buffer_info buf = input.request();cv::Mat mat(buf.shape[0], buf.shape[1], CV_8UC1, (unsigned char*)buf.ptr);return mat;}cv::Mat numpy_uint8_3c_to_cv_mat(py::array_t& input) {if (input.ndim() != 3)throw std::runtime_error("3-channel image must be 3 dims ");py::buffer_info buf = input.request();cv::Mat mat(buf.shape[0], buf.shape[1], CV_8UC3, (unsigned char*)buf.ptr);return mat;}/*C++ Mat ->numpy*/py::array_t cv_mat_uint8_1c_to_numpy(cv::Mat& input) {py::array_t dst = py::array_t({ input.rows,input.cols }, input.data);return dst;}py::array_t cv_mat_uint8_3c_to_numpy(cv::Mat& input) {py::array_t dst = py::array_t({ input.rows,input.cols,3}, input.data);return dst;} 【【PyBind11+anaconda+opencv+windows11+cmake+wsl+vscode】从入门到跑通。构建基于opencv c++的python package】setup.py
其中需要注意的是

include_dirs：指定pybind11，和opencv include的路径
library_dirs：指定使用的动态库，静态库的路径
libraries：指定使用的库名称，原文章是将opencv编译成了opencv_world库的

from setuptools import Extensionfrom setuptools import setup__version__ = '0.0.1'# 扩展模块ext_module = Extension(# 模块名称name='cv_demo1',# 源码sources=[r'wrapper.cpp', r'main.cpp'],# 包含头文件include_dirs=[r'/usr/local/include',r'/root/anaconda3/envs/py3/lib/python3.8/site-packages/pybind11/include' ],# 库目录library_dirs=[r'/usr/local/lib'],# 链接库文件libraries=[r'opencv_core', r'opencv_imgproc'],language='c++')setup(name='cv_demo1',description='A simaple demo',ext_modules=[ext_module],install_requires=['numpy'])

python setup.py build_ext --inplace编辑成so文件，编写test.py查看结果
test.py

import cv_demo1 as cv_demoimport numpy as npimport cv2import matplotlib.pyplot as plt# help(cv_demo)image = cv2.imread('./8.jpg', cv2.IMREAD_GRAYSCALE)# rgb to grayplt.figure('rgb->gray')img_gray = cv_demo.test_rgb_to_gray1(cv2.imread('./8.jpg'))plt.imshow(img_gray)plt.show()

总体代码结构如下