ubuntu调用pythonhttps://blog.csdn.net/qq_39942341/article/details/129333969

我这里mingw是用msys2的
opencv也是msys2装的
安装msys2和opencv可以参考这个https://blog.csdn.net/qq_39942341/article/details/129380197?spm=1001.2014.3001.5502

环境变量里加入python路径，例如D:\Miniconda3\envs\DL

D:\Miniconda3\envs\DL\libs里，python37.lib复制一份改成python37_d.lib

有个玄学的问题，我用不了imgaug这个库

opencv+numpy+pytorch

main.cpp

load_model
加载模型

get_predict_xy
用C++的opencv读图片，转numpy传入python
python再用pytorch预测，返回一个numpy

simple_test
用C++的opencv读图片，转numpy传入python
python直接传回来给C++，转opencv

顺带提一下，import_array()一定要写

#include <Python.h>
#include <iostream>
#include <string>
#include <numpy/arrayobject.h>
#include <opencv2/opencv.hpp>void load_model(PyObject* pModule, const std::string& model_path){PyObject* init_model = PyObject_GetAttrString(pModule, "init_model");if (NULL == init_model || 0 == PyCallable_Check(init_model)) {std::cout << "not found function init_model" << std::endl;exit(-1);}PyObject *pArgs = PyTuple_New(1);PyTuple_SetItem(pArgs, 0, Py_BuildValue("s", model_path.c_str()));PyObject* result = PyObject_CallObject(init_model, pArgs);if(NULL == result){std::cout << "init_model failed" << std::endl;exit(-1);}int return_value = -1;PyArg_Parse(result, "i", &return_value);std::cout<<"returned "<<return_value<<std::endl;
}void get_predict_xy(PyObject* pModule, const std::string& img_path){cv::Mat img = cv::imread(img_path, 0);PyObject* predict = PyObject_GetAttrString(pModule, "get_predict_xy");if (NULL == predict || 0 == PyCallable_Check(predict)) {std::cout << "not found function get_predict_xy" << std::endl;exit(-1);}npy_intp dims[] = {img.rows, img.cols};PyObject* pValue = PyArray_SimpleNewFromData(2, dims, NPY_UINT8, img.data);PyObject *pArgs = PyTuple_New(1);// PyTuple_SetItem(pArgs, 0, Py_BuildValue("s", img_path.c_str()));PyTuple_SetItem(pArgs, 0, pValue);PyObject* result = PyEval_CallObject(predict, pArgs);if(NULL == result){std::cout << "get_predict_xy failed" << std::endl;exit(-1);}if(!PyArray_Check(result)){//Nonestd::cout << "didn't return numpy" << std::endl;exit(-1);}PyArrayObject* ret_array;PyArray_OutputConverter(result, &ret_array);if(2 != PyArray_NDIM(ret_array)){exit(-1);}npy_intp* shape = PyArray_SHAPE(ret_array);int n = shape[0];int m = shape[1];cv::Mat return_key_points(n,m,CV_32F,PyArray_DATA(ret_array));for(int i = 0; i < n; ++i){for(int j = 0; j < m; ++j){int* cur = reinterpret_cast<int*>(PyArray_GETPTR2(ret_array, i, j));std::cout<<*cur<<' ';}std::cout<<std::endl;}//PyArray_GETPTR2
}void simple_test(PyObject* pModule, const std::string& img_path){cv::Mat img = cv::imread(img_path, 0);PyObject* predict = PyObject_GetAttrString(pModule, "simple_test");if (NULL == predict || 0 == PyCallable_Check(predict)) {std::cout << "not found function simple_test" << std::endl;exit(-1);}npy_intp dims[] = {img.rows, img.cols};PyObject* pValue = PyArray_SimpleNewFromData(2, dims, NPY_UINT8, img.data);PyObject *pArgs = PyTuple_New(1);// PyTuple_SetItem(pArgs, 0, Py_BuildValue("s", img_path.c_str()));PyTuple_SetItem(pArgs, 0, pValue);PyObject* result = PyEval_CallObject(predict, pArgs);if(NULL == result){std::cout << "simple_test failed" << std::endl;exit(-1);}if(!PyArray_Check(result)){//Nonestd::cout << "didn't return numpy" << std::endl;exit(-1);}PyArrayObject* ret_array;PyArray_OutputConverter(result, &ret_array);if(2 != PyArray_NDIM(ret_array)){exit(-1);}npy_intp* shape = PyArray_SHAPE(ret_array);int n = shape[0];int m = shape[1];cv::Mat return_img(n,m,CV_8UC1,PyArray_DATA(ret_array));// cv::imshow("test", return_img);// cv::waitKey(0);// cv::destroyAllWindows();for(int i = 0; i < n; ++i){uchar* data1 = img.ptr<uchar>(i);uchar* data2 = return_img.ptr<uchar>(i);for(int j = 0; j < m; ++j){if(data1[j] != data2[j]){std::cout<<"not equal"<<std::endl;return;}}}std::cout<<"equal"<<std::endl;
}int main() {Py_SetPythonHome(L"D:\\Miniconda3\\envs\\DL");Py_Initialize();if (0 == Py_IsInitialized()) {std::cout << "python init fail" << std::endl;return -1;}import_array();PyRun_SimpleString("import sys");PyRun_SimpleString("import os");PyRun_SimpleString("print(os.path.abspath('.'))");PyRun_SimpleString("sys.path.append('../python_script')");//相当于importPyObject* pModule = PyImport_ImportModule("predict");if (NULL == pModule) {std::cout << "module not found" << std::endl;return -1;}simple_test(pModule, "../python_script/001.bmp");load_model(pModule, "../python_script/best.pth");get_predict_xy(pModule, "../python_script/001.bmp");get_predict_xy(pModule, "../python_script/001.bmp");Py_Finalize();return 0;
}

predict.py
UNet我没放出来

#!/usr/bin/env python
# _*_ coding:utf-8 _*_
import os
import numpy as npfrom model.u2net import UNet
import torch
from cv2 import cv2#import imgaug.augmenters as iaamodel = UNet(in_channels=1, out_channels=19)
device = torch.device('cuda:0')# augmentation = iaa.Sequential([
#     iaa.Resize({"width": 416, "height": 512})
# ])def init_model(path):global model, deviceif not os.path.exists(path):print(f'not found {os.path.abspath(path)}')return -1model_state_dict = torch.load(path)model.load_state_dict(model_state_dict)model = model.to(device)return 0def get_img_aug(img):# global augmentationprint('----get_img_aug------')print(img.shape)print('------------------')# img = cv2.imread(path, 0)  # 2490*1935# img_aug = augmentation(image=img)img_aug = cv2.resize(img, (416, 512), interpolation=cv2.INTER_LINEAR)img_aug = (img_aug - img_aug.min()) / (img_aug.max() - img_aug.min())img_aug = torch.FloatTensor(img_aug).unsqueeze(0).unsqueeze(0)  # torch.Size([1, 1, 512, 416])return img_augdef get_heatmap_coordination_batch_numpy(heatmap):"""get heatmap coordination by batch:param heatmap: (B,C,H,W) or (B,C,H,W,D) (C is the num of landmark):return: coordination (B,C,2) or (B,C,3)"""origin_shape = heatmap.shapeheatmap = heatmap.reshape(*origin_shape[:2], -1)temp = np.argmax(heatmap, axis=-1)[..., np.newaxis]# unravel_indexout = []for dim in reversed(origin_shape[2:]):out.append(temp % dim)temp = np.floor_divide(temp, dim)out = np.concatenate(out[::-1], axis=-1)return outdef get_predict_xy(img):global model# if not os.path.exists(path):#     return Noneimg = get_img_aug(img).to(device)  # 1 * 1 * 512 * 416output = model(img)['output'].to('cpu').detach().numpy()  # 1 * 1 * 19 * 2predict_xy = get_heatmap_coordination_batch_numpy(output).squeeze(0)  # 19 * 2print(predict_xy)return predict_xydef simple_test(img):return imgif __name__ == '__main__':path = r'E:\PyCharmProject\pythonProject3\001.bmp'img = cv2.imread(path, 0)init_model('best.pth')print('finish_init')print(get_predict_xy(img).shape)print(get_predict_xy(img).dtype)

CMakeLists.txt

cmake_minimum_required(VERSION 3.24)
project(C_PLUS_PLUS VERSION 0.1.0)IF(NOT CMAKE_BUILD_TYPE)SET(CMAKE_BUILD_TYPE Release)
ENDIF()set(CMAKE_CXX_STANDARD 17)
set(PYTHON_INCLUDE_DIRS "D:/Miniconda3/envs/DL/include/")
set(NUMPY_INCLUDE_DIR "D:/Miniconda3/envs/DL/Lib/site-packages/numpy/core/include")
INCLUDE_DIRECTORIES(${PYTHON_INCLUDE_DIRS} ${NUMPY_INCLUDE_DIR})
link_directories("D:/Miniconda3/envs/DL/libs")
set(PYTHON_LIBRARIES "D:/Miniconda3/envs/DL/libs/python37.lib")
add_executable(${PROJECT_NAME} main.cpp)
target_link_libraries(${PROJECT_NAME} ${PYTHON_LIBRARIES})# Where to find CMake modules and OpenCV
# set(OpenCV_DIR "D:\\opencv-4.5.5\\opencv-4.5.5\\build")
find_package(OpenCV REQUIRED)
message(STATUS "OpenCV Include: ${OpenCV_INCLUDE_DIRS}")
message(STATUS "OpenCV LIBRARIES: ${OpenCV_LIBRARIES}")
message(STATUS "OpenCV Libs: ${OpenCV_LIBS}")INCLUDE_DIRECTORIES(${OpenCV_INCLUDE_DIRS})
target_link_libraries(${PROJECT_NAME}  ${OpenCV_LIBS})