C++调用tensorflow教程

bash Anaconda3-4.3.1-Linux-x86_64.sh

gedit ~/.bashrc

export PATH=/<你的anaconda路径>/bin:$PATH

#include <Python.h>
#include <iostream>
int main(int argc, char** argv)
{
  char* picpath ="/home/pdd/PD/c++/c++python/pic/0.0.jpg";
  Py_Initialize(); 
    if ( !Py_IsInitialized() ) { 
    return -1; 
    } 
    PyRun_SimpleString("import sys");
    PyRun_SimpleString("sys.path.append('./')");
  PyObject* pMod = NULL;
  PyObject* pFunc = NULL;
  PyObject* pParm = NULL;
  PyObject* pRetVal = NULL;
  int iRetVal = -999;
  char* modulName="classify";  //这个是被调用的py文件模块名字
  pMod = PyImport_ImportModule(modulName); 
  if(!pMod)
  {
    return -1;
  }
  char* funcName="evaluate"; //这是此py文件模块中被调用的函数名字
  pFunc = PyObject_GetAttrString(pMod, funcName); 
  if(!pFunc) 
  {  
    return -2; 
  } 
  pParm = PyTuple_New(1);
  PyTuple_SetItem(pParm, 0, Py_BuildValue("s",picpath));//传入的参数，是图片的路径
  pRetVal = PyEval_CallObject(pFunc, pParm);//这里开始执行py脚本
  PyArg_Parse(pRetVal, "i", &iRetVal);//py脚本返回值给iRetVal
  //PyErr_Print();
  std::cout<<iRetVal;
  return iRetVal;
}

from PIL import Image
import numpy as np
import tensorflow as tf
def evaluate(pic):
  image = Image.open(pic)
  image = image.resize([256, 256])
  image_array = np.array(image)
  with tf.Graph().as_default():
    里面就是对图像读取模型，预测，得到prediction……
      max_index = np.argmax(prediction)
      return max_index

main:c++python.cpp
  g++ -o out c++python.cpp -I/home/pdd/anaconda3/include/python3.6m -lpython3.6m -L /home/pdd/anaconda3/lib
clean:
  rm -rf *.o