基本流程:
定义cpp文件实现算法逻辑,因为编译器在编译的时候是会把c++函数改名,所以对于python调用的函数是要声明为以c的方式编译 #include "execute.h"
extern "C"
{
Execute execute;
void show_matrix(int *matrix, int rows, int columns) {
execute.show_matrix(matrix, rows, columns);
}
// 传递uchar数组到c++
void show_uchar_matrix(uchar *matrix, int rows, int columns) {
execute.show_uchar_matrix(matrix, rows, columns);
}
// 传递图片到c++
void transfer_image(uchar *frame_data, int height, int width, int channel) {
execute.transfer_image(frame_data, height, width, channel);
}
// 在c++层处理数组 并返回值
float sum_array(float *data, int len) {
return execute.sum_array(data, len);
}
// 在c++层处理数组
void change_array(float *data, int len) {
execute.change_array(data, len);
}
// 传递结构体到 c++ 层 并返回结构体
result transfer_struct(result t) {
return execute.transfer_struct(t);
}
}
将cpp文件打包为动态库 so 文件 在python中加载 so 文件,调用对应的cpp算法
一个简单的 c++ 例子
execute.h 头文件
#ifndef PY_C_TEST_EXCUTE_H
#define PY_C_TEST_EXCUTE_H
#include
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/core/core.hpp"
typedef struct Result {
int a;
char *b;
} result;
class Execute {
public:
// 传递int数组到c++
void show_matrix(int *matrix, int rows, int columns);
// 传递uchar数组到c++
void show_uchar_matrix(uchar *matrix, int rows, int columns);
// 传递图片到c++
void transfer_image(uchar *frame_data, int height, int width, int channel);
// 在c++层处理数组
void change_array(float *data, int len);
// 在c++层处理数组
float sum_array(float *data, int len);
// 传递结构体到c++层并传回
result transfer_struct(result t);
};
#endif //PY_C_TEST_EXCUTE_H
#include "execute.h"
// python 传递数组到 c++ 端时, 需要将其拉平为 1 维.
void Execute::show_matrix(int *matrix, int rows, int columns) {
int row, col;
for (row = 0; row < rows; row++) {
for (col = 0; col < columns; col++) {
printf("matrix[%d][%d] = %d\n", row, col, matrix[row * columns + col]);
}
}
}
void Execute::show_uchar_matrix(uchar *matrix, int rows, int columns) {
int row, col;
for (row = 0; row < rows; row++) {
for (col = 0; col < columns; col++) {
printf("matrix[%d][%d] = %d\n", row, col, int(matrix[row * columns + col]));
}
}
}
void Execute::transfer_image(uchar *frame_data, int height, int width, int channel) {
int type = CV_8UC1;
if (channel == 3) {
type = CV_8UC3;
}
cv::Mat image(height, width, type);
for (int row = 0; row < height; row++) {
uchar *pxvec = image.ptr(row);
for (int col = 0; col < width; col++) {
for (int c = 0; c < channel; c++) {
pxvec[col * channel + c] = frame_data[row * width * channel + channel * col + c];
}
}
}
cv::imshow("image", image);
cv::waitKey(0);
}
float Execute::sum_array(float *data, int len) {
float sum = 0;
for (int i = 0; i < len; i++) {
sum += data[i];
}
return sum;
}
void Execute::change_array(float *data, int len) {
for (int i = 0; i < len; i++) {
data[i] += len;
}
}
result Execute::transfer_struct(result t) {
t.a = t.a + t.a;
printf("%s\n",t.b);
t.b = "new string from c++";
return t;
}
1. python 传递数组到 c++ 端
import ctypes
import cv2
import numpy as np
ll = ctypes.cdll.LoadLibrary
lib = ll("./libc_opencv.so")
arr = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11]])
tmp = np.asarray(arr, dtype=np.uint8)
rows, cols = tmp.shape
dataptr = tmp.ctypes.data_as(ctypes.c_char_p)
lib.show_uchar_matrix(dataptr, rows, cols)
传递的numpy数组类型需要与c++端接收的数组类型相同, 具体对应关系可以查询 python的ctypes文档
2. python端传递图片到 c++ 端
ll = ctypes.cdll.LoadLibrary
lib = ll("./libc_opencv.so")
tmp = cv2.imread("full_finish.jpg", cv2.IMREAD_GRAYSCALE)
rows, cols = tmp.shape
dataptr = tmp.ctypes.data_as(ctypes.c_char_p)
lib.transfer_image(dataptr, rows, cols, 1)
3. 传递数组到 c++ 端并返回值
ll = ctypes.cdll.LoadLibrary
lib = ll("./libc_opencv.so")
pyarray = [1., 2., 3., 4., 5.1]
carray = (ctypes.c_float * len(pyarray))(*pyarray)
# 定义返回值类型
lib.sum_array.restype = ctypes.c_float
sum = lib.sum_array(carray, len(pyarray))
print(sum)
默认python端读到的是 c++ 返回值的地址,需要显式地定义返回值类型
4. 传递数组到 c++ 端并返回数组
需要先在Python端将返回数组定义出来,一同传入 c++ 端,在 c++ 端将数据写入,再通过np.array将 c++ 数组转回numpy数组类型
ll = ctypes.cdll.LoadLibrary
lib = ll("./libc_opencv.so")
pyarray = [1., 2., 3., 4., 5.1]
carray = (ctypes.c_float * len(pyarray))(*pyarray)
lib.change_array(carray, len(pyarray))
print(np.array(carray))
5. 传递结构体到 c++ 端并返回结构体
在c++端定义结构体
typedef struct Result {
int a;
char *b;
} result;
在python端定义相同的结构体
class Result(Structure):
_fields_ = [('a', c_int),
('b', c_char_p)]
在python端调用
ll = ctypes.cdll.LoadLibrary
lib = ll("./libc_opencv.so")
# 赋予结构体的数据必须转成 ctype 格式
a = ctypes.c_int(220)
b = ctypes.c_char_p('Hello'.encode())
t = Result()
t.a = a
t.b = b
# 定义返回类型为结构体类型
lib.transfer_struct.restype = Result
t = lib.transfer_struct(t)
print(t.a)
print(t.b.decode())
转播
