说明一下
我这边做表情识别和Socket，表情识别要实时，Socket要一直监听表情识别的结果，那么就只好用C++多线程来解决这个“两个功能一直并且同时运行”的问题。
否则，如果是单线程的话，只能运行表情识别一段时间，切换发送一段时间，又切换回来，这样没有多线程好。
还要说解决的难点
- 写成多个文件，是由于命名空间的原因，不是多线程的原因——因为多线程是可以写在一个文件里面的
- 如果多线程写在一个文件，那么参数传递进函数就很方便了，但是现在不同函数却写在不同文件里
- 为了解决第2点的问题，定义了全局变量
b_int，在别的文件里用extern来声明，全局变量哈哈哈哈哈，然后问题就解决了。用全局变量来做传递的参数，在不同的文件里面都可以用。
新建1.h 作为头文件
#pragma once
#ifndef XXX_H
#define XXX_H
void aaa(int ax);
int aaa2();
#endif
新建1.cpp Socket的代码
//#include "pch.h"
#include "1.h"
#include<iostream>
#include<winsock.h>
#pragma comment(lib,"ws2_32.lib")
using namespace std;
void initialization();
extern int b_int;
void aaa(int a)
{
//定义长度变量
int send_len = 0;
int recv_len = 0;
int len = 0;
//定义发送缓冲区和接受缓冲区
char send_buf[100];
char recv_buf[100];
//定义服务端套接字，接受请求套接字
SOCKET s_server;
SOCKET s_accept;
//服务端地址客户端地址
SOCKADDR_IN server_addr;
SOCKADDR_IN accept_addr;
initialization();
//填充服务端信息
server_addr.sin_family = AF_INET;
server_addr.sin_addr.S_un.S_addr = htonl(INADDR_ANY);
server_addr.sin_port = htons(5010);
//创建套接字
s_server = socket(AF_INET, SOCK_STREAM, 0);
if (bind(s_server, (SOCKADDR *)&server_addr, sizeof(SOCKADDR)) == SOCKET_ERROR) {
cout << "套接字绑定失败！" << endl;
WSACleanup();
}
else {
cout << "套接字绑定成功！" << endl;
}
//设置套接字为监听状态
if (listen(s_server, SOMAXCONN) < 0) {
cout << "设置监听状态失败！" << endl;
WSACleanup();
}
else {
cout << "设置监听状态成功！" << endl;
}
cout << "服务端正在监听连接，请稍候...." << endl;
//接受连接请求
len = sizeof(SOCKADDR);
s_accept = accept(s_server, (SOCKADDR *)&accept_addr, &len);
if (s_accept == SOCKET_ERROR) {
cout << "连接失败！" << endl;
WSACleanup();
//return 0;
}
cout << "连接建立，准备接受数据" << endl;
while (1)
{
a = b_int;
while (1)
{
a = b_int;
if (a == 1)
{
send_buf[0] = '1';
send_buf[1] = '\0';
a = b_int;
}
else if (a == 2)
{
send_buf[0] = '2';
send_buf[1] = '\0';
a = b_int;
}
else if (a == 3)
{
send_buf[0] = '3';
send_buf[1] = '\0';
a = b_int;
}
else if (a == 4)
{
send_buf[0] = '4';
send_buf[1] = '\0';
a = b_int;
}
cout << "b_int=" << b_int << endl;
a = b_int;
recv_len = recv(s_accept, recv_buf, 100, 0);
cout << "recv= " << recv_buf << endl;
a = b_int;
send(s_accept, send_buf, 100, 0);
cout << "send= " << send_buf << endl;
a = b_int;
break;
}
}
//关闭套接字
closesocket(s_server);
closesocket(s_accept);
//释放DLL资源
WSACleanup();
//return 0;
}
void initialization()
{
//初始化套接字库
WORD w_req = MAKEWORD(2, 2);//版本号
WSADATA wsadata;
int err;
err = WSAStartup(w_req, &wsadata);
if (err != 0) {
cout << "初始化套接字库失败！" << endl;
}
else {
cout << "初始化套接字库成功！" << endl;
}
//检测版本号
if (LOBYTE(wsadata.wVersion) != 2 || HIBYTE(wsadata.wHighVersion) != 2) {
cout << "套接字库版本号不符！" << endl;
WSACleanup();
}
else {
cout << "套接字库版本正确！" << endl;
}
//填充服务端地址信息
}
新建2.cpp 表情识别的代码
//#pragma comment(linker, "/subsystem:windows /entry:mainCRTStartup")//去除CMD窗口
#include <dlib/opencv.h>
#include <opencv2/opencv.hpp>
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
#include <dlib/gui_widgets.h>
using namespace dlib;
using namespace std;
using namespace cv::ml;
extern int b_int;
int aaa2()
{
try
{
cv::VideoCapture cap(0);
if (!cap.isOpened())
{
cerr << "Unable to connect to camera" << endl;
return 1;
}
//image_window win;
// Load face detection and pose estimation models.
frontal_face_detector detector = get_frontal_face_detector();
shape_predictor pose_model;
deserialize("shape_predictor_68_face_landmarks.dat") >> pose_model;
cv::Ptr<SVM> svm = StatModel::load<SVM>("SVM_DATA.xml");
// Grab and process frames until the main window is closed by the user.
while (cv::waitKey(30) != 27)
{
// Grab a frame
cv::Mat temp;
cap >> temp;
cv_image<bgr_pixel> cimg(temp);
// Detect faces
std::vector<rectangle> faces = detector(cimg);
// Find the pose of each face.
std::vector<full_object_detection> shapes;
for (unsigned long i = 0; i < faces.size(); ++i)
shapes.push_back(pose_model(cimg, faces[i]));
if (!shapes.empty()) {
float testData[1][136];
float 系数 = -(faces[0].top() - faces[0].bottom()) / 300.0;
for (int i = 0; i < 68; i++) {
circle(temp, cvPoint(shapes[0].part(i).x(), shapes[0].part(i).y()), 2, cv::Scalar(255, 0, 0), -1);
testData[0][i * 2] = (shapes[0].part(i).x() - faces[0].left()) / 系数;
testData[0][i * 2 + 1] = (shapes[0].part(i).y() - faces[0].top()) / 系数;
// shapes[0].part(i).x();//68个
}
cv::Mat 结果;
cv::Mat query(1, 136, CV_32FC1, testData);
if (svm->predict(query) == 250) {
cv::putText(temp, "Happy", cv::Point(20, 60), 3, 2, cvScalar(0, 0, 255));
//cout << "高兴" << endl;
b_int = 1;
}
if (svm->predict(query) == 170) {
cv::putText(temp, "Common", cv::Point(20, 60), 3, 2, cvScalar(0, 0, 255));
//cout << "平静" << endl;
b_int = 2;
}
if (svm->predict(query) == 300) {
cv::putText(temp, "Disgust", cv::Point(20, 60), 3, 2, cvScalar(0, 0, 255));
//cout << "厌恶" << endl;
b_int = 3;
}
// cout<< svm->predict(query)<<endl;
// cout << 结果 << endl;
}
//Display it all on the screen
imshow("表情识别 ESC退出", temp);
}
}
catch (serialization_error& e)
{
cout << "You need dlib's default face landmarking model file to run this example." << endl;
cout << "You can get it from the following URL: " << endl;
cout << " http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
cout << endl << e.what() << endl;
}
catch (exception& e)
{
cout << e.what() << endl;
}
}
新建test.cpp main()函数
#include"1.h"
#include <iostream>
#include <thread>
#include<math.h>
using namespace std;
int b_int ;
extern void aaa(int a);
int main()
{
int ccc = 2 ;
std::thread t(aaa, b_int);
std::thread t2(aaa2);
t.join();
t2.join();
return 0;
}