first docker
This commit is contained in:
root
+191
@@ -0,0 +1,191 @@
|
||||
|
||||
#include <iostream>
|
||||
#include <signal.h>
|
||||
#include <stdlib.h> /* srand, rand */
|
||||
#ifdef __linux__
|
||||
#include <unistd.h>
|
||||
#endif
|
||||
|
||||
#include <mutex>
|
||||
#include "utils.h"
|
||||
#include "baggageDetect.hpp"
|
||||
#include "handler.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>
|
||||
using namespace std;
|
||||
|
||||
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_path;
|
||||
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;
|
||||
//read parametersi
|
||||
handler::handler(utility::string_t url):m_listener(url)
|
||||
{
|
||||
m_listener.support(methods::POST, bind(&handler::handle_post, this, placeholders::_1));
|
||||
|
||||
}
|
||||
|
||||
string name_from_path(string path)
|
||||
{
|
||||
return path.substr(path.find_last_of("/\\")+1);
|
||||
}
|
||||
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;
|
||||
//std::vector<tk::dnn::Frame> images;
|
||||
//std::vector<tk::dnn::box> detected_bbox;
|
||||
|
||||
std::cout<<"Reading groundtruth and generating detections"<<std::endl;
|
||||
|
||||
if(show)
|
||||
cv::namedWindow("detection", cv::WINDOW_NORMAL);
|
||||
}
|
||||
// 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 handler::handle_post(http_request request){
|
||||
init_bag();
|
||||
|
||||
// const char * img_path=
|
||||
//tk::dnn::Frame f;
|
||||
BOOST_LOG_TRIVIAL(info) << "[" << name_from_path(string(__FILE__)) << " " << __LINE__ << "] " << request.to_string();
|
||||
|
||||
map<utility::string_t, utility::string_t> http_get_vars = uri::split_query(request.request_uri().query());
|
||||
map<utility::string_t, utility::string_t>::iterator it = http_get_vars.find("name");
|
||||
// std::cout<<request<<"\n";
|
||||
//If 'name' is not in the query.
|
||||
int len;
|
||||
if(it == http_get_vars.end())
|
||||
{
|
||||
BOOST_LOG_TRIVIAL(error) << "[" << name_from_path(string(__FILE__)) << " " << __LINE__ << "] " << "Image name not passed in query.";
|
||||
request.reply(status_codes::UnprocessableEntity,"Please pass image name in the query.");
|
||||
return;
|
||||
}
|
||||
std::cout<<http_get_vars["name"]<<"\n";
|
||||
string image_name = (string)http_get_vars["name"];
|
||||
string ustring;
|
||||
//reading binary data and storing it in a pointer
|
||||
request.extract_vector().then([image_name, &ustring, &len](vector<unsigned char> v) {
|
||||
ustring = {v.begin(),v.end()};
|
||||
len = ustring.size();
|
||||
}).wait();
|
||||
BOOST_LOG_TRIVIAL(info) << "[" << name_from_path(string(__FILE__)) << " " << __LINE__ << "] " << "Detection Started";
|
||||
|
||||
// img_path=(unsigned char *)ustring.c_str();
|
||||
//reading binary data and storing it in a pointer
|
||||
// std::string body = request.extract_string().get();
|
||||
//string img_data= (string)http_get_vars[:];
|
||||
|
||||
std::cout<<ustring<<"hi\n";
|
||||
cv::Mat frame = cv::imread(ustring, cv::IMREAD_COLOR);
|
||||
// cv::Mat frame=cv::imdecode((unsigned char *)ustring.c_str())
|
||||
std::vector<cv::Mat> batch_frames;
|
||||
batch_frames.push_back(frame);
|
||||
int height = frame.rows;
|
||||
int width = frame.cols;
|
||||
|
||||
// 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
|
||||
request.reply(status_codes::OK,response.serialize());
|
||||
// free(detectboxes);
|
||||
BOOST_LOG_TRIVIAL(info) << "[" << name_from_path(string(__FILE__)) << " " << __LINE__ << "] " << "Detection Completed and Response sent";
|
||||
}
|
||||
catch (exception const& e) {
|
||||
BOOST_LOG_TRIVIAL(error) << "[" << name_from_path(string(__FILE__)) << " " << __LINE__ << "] " << e.what();
|
||||
request.reply(status_codes::BadRequest, e.what());
|
||||
}
|
||||
// std::cout << timeSinceEpochMillisec() << std::endl;
|
||||
return ;
|
||||
}
|
||||
Reference in New Issue
Block a user