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tkDNN/bag_server.cpp
T
2021-06-09 08:27:32 +00:00

249 lines
7.1 KiB
C++

#define STB_IMAGE_IMPLEMENTATION
#include <iostream>
#include <signal.h>
#include <stdlib.h> /* srand, rand */
#ifdef __linux__
#include <unistd.h>
#endif
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"
#include "stb_image.h"
#include <mutex>
#include "utils.h"
#include <vector>
#include <random>
#include <climits>
#include <algorithm>
#include <functional>
#include <string>
#include <fstream>
#include <stdio.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "Yolo3Detection.h"
//#include "CenternetDetection.h"
//#include "MobilenetDetection.h"
#include "evaluation.h"
#include <chrono>
#include <cstdint>
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include <iostream>
#include "opencv2/core/core.hpp"
#include <opencv2/highgui/highgui.hpp>
#include<sys/socket.h> //socket
#include<sys/types.h>
#include<netinet/in.h>
using namespace std;
using namespace cv;
#define PORT 8080
#define FRAME_WIDTH 640
#define FRAME_HEIGHT 480
void error(const char *msg)
{
perror(msg);
exit(1);
} int sockfd, newsockfd, portno, n, imgSize, bytes=0, IM_HEIGHT, IM_WIDTH;;
socklen_t clilen;
char buffer[256];
// struct sockaddr_in serv_addr, cli_addr;
// sockfd=socket(AF_INET, SOCK_STREAM, 0);
cv::Mat img;
char ntype = 'y';
const char *config_filename = "../demo/config.yaml";
const char * net = "../demo/yolo4_fp32.rt";
// const char * img_path = "../demo/demo.jpg";
char * img_data;
bool show = false;
bool verbose;
int classes, map_points, map_levels;
float map_step, IoU_thresh, conf_thresh;
tk::dnn::Yolo3Detection yolo;
// tk::dnn::CenternetDetection cnet;
// tk::dnn::MobilenetDetection mbnet;
tk::dnn::DetectionNN *detNN;
int n_classes = classes;
std::vector<tk::dnn::Frame> images;
std::vector<tk::dnn::box> detected_bbox;
tk::dnn::Frame f;
void init_bag(){tk::dnn::readmAPParams(config_filename, classes, map_points, map_levels, map_step,
IoU_thresh, conf_thresh, verbose);
//extract network name from rt path
std::string net_name;
removePathAndExtension(net, net_name);
std::cout<<"Network: "<<net_name<<std::endl;
//open files (if needed)
//std::ofstream times, memory, coco_json;
int n_classes = classes;
// float conf_threshold=0.001;
detNN = &yolo;
detNN->init(net, n_classes, 1, conf_thresh);
//read images
// std::ifstream all_labels(labels_path);
// std::cout << timeSinceEpochMillisec() << std::endl;
std::string l_filename;
if(show)
cv::namedWindow("detection", cv::WINDOW_NORMAL);
return;}
// init_bag();
// int images_done;
// for (images_done=0 ; std::getline(all_labels, l_filename) && images_done < n_images ; ++images_done) {
// std::cout <<COL_ORANGEB<< "Images done:\t" << images_done<< "\n"<<COL_END;
void infr(cv::Mat image){
cv::Mat frame = image;
cv::imwrite("/home/baggageai/files/build/test.png", frame);
std::cout<<frame.channels();
std::vector<cv::Mat> batch_frames;
batch_frames.push_back(frame);
int height = frame.rows;
int width = frame.cols;
std::cout<<height<<"width"<<width<<"\n";
// if(!frame.data)
// break;
std::vector<cv::Mat> batch_dnn_input;
batch_dnn_input.push_back(frame.clone());
std::cout<<"test1"<<"\n";
//inference
detected_bbox.clear();
detNN->update(batch_dnn_input,1);
detNN->draw(batch_frames);
detected_bbox = detNN->detected;
std::cout<<"test2"<<"\n";
//try{
//json::value response;
//vector<json::value> jsonArray;
// save detections labels
for(auto d:detected_bbox){
//convert detected bb in the same format as label
//<x_center>/<image_width> <y_center>/<image_width> <width>/<image_width> <height>/<image_width>
tk::dnn::BoundingBox b;
b.x = (d.x + d.w/2) / width;
b.y = (d.y + d.h/2) / height;
b.w = d.w / width;
b.h = d.h / height;
b.prob = d.prob;
b.cl = d.cl;
//f.det.push_back(b);
/*json::value detection;
detection["label"] = json::value::number(b.cl);
detection["x"] = json::value::number(b.x);
detection["y"] = json::value::number(b.y);
detection["w"] = json::value::number(b.w);
detection["h"] = json::value::number(b.h);
detection["prob"] = json::value::number(b.prob);
jsonArray.push_back(detection);*/
std::cout<< d.cl << " "<< d.prob << " "<< b.x << " "<< b.y << " "<< b.w << " "<< b.h <<"\n";
if(show)// draw rectangle for detection
cv::rectangle(batch_frames[0], cv::Point(d.x, d.y), cv::Point(d.x + d.w, d.y + d.h), cv::Scalar(0, 0, 255), 2);
}
//images.push_back(f);
if(show){
cv::imshow("detection", batch_frames[0]);
cv::waitKey(0);
}
// response["detections"] = json::value::array(jsonArray); //JSON Response
// std::cout << timeSinceEpochMillisec() << std::endl;
return ;
}
int main()
{
// int sockfd, newsockfd, portno, n, imgSize, bytes=0, IM_HEIGHT, IM_WIDTH;;
// socklen_t clilen;
char buffer[256];
struct sockaddr_in serv_addr, cli_addr;
//init_bag()
// cv::Mat img;
sockfd=socket(AF_INET, SOCK_STREAM, 0);
if(sockfd<0) error("ERROR opening socket");
bzero((char*)&serv_addr, sizeof(serv_addr));
portno = PORT;
serv_addr.sin_family=AF_INET;
serv_addr.sin_addr.s_addr=INADDR_ANY;
serv_addr.sin_port=htons(portno);
if(bind(sockfd, (struct sockaddr *) &serv_addr,
sizeof(serv_addr))<0) error("ERROR on binding");
listen(sockfd,5);
clilen=sizeof(cli_addr);
newsockfd=accept(sockfd, (struct sockaddr *) &cli_addr, &clilen);
if(newsockfd<0) error("ERROR on accept");
uchar sock[3];
cout << sock <<endl;
cout << sock+3 <<endl;
// bzero(buffer,1024);
// n = read(newsockfd, buffer, 1023);
// if(n<0) error("ERROR reading from socket");
//printf("Here is the message: %s\n", buffer);
// n=write(newsockfd, "I got your message", 18);
// if(n<0) error("ERROR writing to socket");
bool running = true;
while(running)
{ std::cout<<"t"<<"\n";
IM_HEIGHT = FRAME_HEIGHT;
IM_WIDTH = FRAME_WIDTH;
img = Mat::zeros(FRAME_HEIGHT, FRAME_WIDTH, CV_8UC3);
imgSize = img.total()*img.elemSize();
uchar sockData[imgSize];
std::cout<<"t2"<<"\n";
for(int i=0;i<imgSize;i+=bytes)
if ((bytes=recv(newsockfd, sockData+i, imgSize-i,0))==-1) error("recv failed");
int ptr=0;
for(int i=0;i<img.rows;++i)
for(int j=0;j<img.cols;++j)
{
img.at<Vec3b>(i,j) = Vec3b(sockData[ptr+0],sockData[ptr+1],sockData[ptr+2]);
ptr=ptr+3;
}
std::cout<<"t3"<<"\n";
int height = img.cols;
std::cout<<height;
infr(img)
// namedWindow( "Server", CV_WINDOW_AUTOSIZE );// Create a window for display.
// imshow( "Server", img );
// char key = waitKey(30);
// running = key;
//esc
// if(key==27) running =false;
}
close(newsockfd);
close(sockfd);
return 0;
}
}