普通

目录结构

main.py
等会用c++调用func()

#!/usr/bin/env python
# _*_ coding:utf-8 _*_
import osdef func():print('hello world')if __name__ == '__main__':func()

main.cpp
其中Py_SetPythonHome的路径是anaconda中环境的路径，最开始的L一定要加（因为代表wchar_t)
sys.path.append是用来找你的python文件路径的，其中"."".""."表示可执行文件的路径

#include 
#include int main() {Py_SetPythonHome(L"/home/icml/miniconda3/envs/DL");Py_Initialize();if (0 == Py_IsInitialized()) {std::cout << "python init fail" << std::endl;return -1;}PyRun_SimpleString("import sys");PyRun_SimpleString("sys.path.append('../python_script')");//相当于importPyObject* pModule = PyImport_ImportModule("main");if (NULL == pModule) {std::cout << "module not found" << std::endl;return -1;}PyObject* pFunc = PyObject_GetAttrString(pModule, "func");if (NULL == pFunc || 0 == PyCallable_Check(pFunc)) {std::cout << "not found function func" << std::endl;return -1;}PyObject_CallObject(pFunc, NULL);Py_Finalize();return 0;
}

CMakeLists.txt
稍微对照着修改一下就行

cmake_minimum_required(VERSION 3.0.0)
project(C_PLUS_PLUS VERSION 0.1.0)# IF(NOT CMAKE_BUILD_TYPE)
#   SET(CMAKE_BUILD_TYPE Release)
# ENDIF()set(PYTHON_INCLUDE_DIRS "/home/icml/miniconda3/envs/DL/include/python3.8")
INCLUDE_DIRECTORIES(${PYTHON_INCLUDE_DIRS})
link_directories("/home/icml/miniconda3/envs/DL/lib/python3.8/config-3.8-x86_64-linux-gnu")
set(PYTHON_LIBRARIES "/home/icml/miniconda3/envs/DL/lib/libpython3.8.so")
add_executable(${PROJECT_NAME} main.cpp)
target_link_libraries(${PROJECT_NAME} ${PYTHON_LIBRARIES})

我这里cmake最后产生到build目录里

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 
#include 
#include 
#include 
#include 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 "<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(PyArray_GETPTR2(ret_array, i, j));std::cout<<*cur<<' ';}std::cout<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(i);uchar* data2 = return_img.ptr(i);for(int j = 0; j < m; ++j){if(data1[j] != data2[j]){std::cout<<"not equal"<Py_SetPythonHome(L"/home/icml/miniconda3/envs/DL");Py_Initialize();if (0 == Py_IsInitialized()) {std::cout << "python init fail" << std::endl;return -1;}import_array(); //这句一定要写PyRun_SimpleString("import sys");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, "/mnt/data/datasets/landmark/ISBI2015_ceph/raw/001.bmp");load_model(pModule, "../python_script/best.pth");get_predict_xy(pModule, "/mnt/data/datasets/landmark/ISBI2015_ceph/raw/001.bmp");get_predict_xy(pModule, "/mnt/data/datasets/landmark/ISBI2015_ceph/raw/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*1935img_aug = augmentation(image=img)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 = '/mnt/data/datasets/landmark/ISBI2015_ceph/raw/001.bmp'init_model('best.pth')print('finish_init')print(get_predict_xy(path).shape)print(get_predict_xy(path).dtype)

CMakeLists.txt

cmake_minimum_required(VERSION 3.0.0)
project(C_PLUS_PLUS VERSION 0.1.0)IF(NOT CMAKE_BUILD_TYPE)SET(CMAKE_BUILD_TYPE Release)
ENDIF()set(PYTHON_INCLUDE_DIRS "/home/icml/miniconda3/envs/DL/include/python3.8")
set(NUMPY_INCLUDE_DIR "/home/icml/miniconda3/envs/DL/lib/python3.8/site-packages/numpy/core/include")
INCLUDE_DIRECTORIES(${PYTHON_INCLUDE_DIRS} ${NUMPY_INCLUDE_DIR})
link_directories("/home/icml/miniconda3/envs/DL/lib/python3.8/config-3.8-x86_64-linux-gnu")
set(PYTHON_LIBRARIES "/home/icml/miniconda3/envs/DL/lib/libpython3.8.so")
add_executable(${PROJECT_NAME} main.cpp)
target_link_libraries(${PROJECT_NAME} ${PYTHON_LIBRARIES})find_package(OpenCV REQUIRED)
message(STATUS "OpenCV library status:")
message(STATUS "  config: ${OpenCV_DIR}")
message(STATUS "  version: ${OpenCV_VERSION}")
message(STATUS "  libraries: ${OpenCV_LIBS}")
message(STATUS "  include path: ${OpenCV_INCLUDE_DIRS}")
INCLUDE_DIRECTORIES(${OpenCV_INCLUDE_DIRS})
target_link_libraries(${PROJECT_NAME}  ${OpenCV_LIBS})

目录结构

运行