mmr/tkDNN
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Update demo.cpp

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Added HTTP stream over multi-client MJPEG  sever, added ESC Key quit and resizable cv window
This commit is contained in:
Biparnak Roy
2020-07-18 05:06:22 +05:30
committed by GitHub
parent f4970d1e6f
commit d957d9af07
1 changed files with 85 additions and 63 deletions
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demo/demo/demo.cpp
+85 -63
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@@ -1,8 +1,9 @@
#include <iostream> #include <iostream>
#include <signal.h> #include <signal.h>
#include <stdlib.h> /* srand, rand */ #include <stdlib.h> /* srand, rand */
#include <unistd.h> #include <unistd.h>
#include <mutex> #include <mutex>
#include <https_stream.h> //https_stream
#include "CenternetDetection.h" #include "CenternetDetection.h"
#include "MobilenetDetection.h" #include "MobilenetDetection.h"
@@ -11,61 +12,65 @@
bool gRun; bool gRun;
bool SAVE_RESULT = false; bool SAVE_RESULT = false;
void sig_handler(int signo) { void sig_handler(int signo)
std::cout<<"request gateway stop\n"; {
std::cout << "request gateway stop\n";
gRun = false; gRun = false;
} }
int main(int argc, char *argv[]) { int main(int argc, char *argv[])
{
std::cout<<"detection\n"; std::cout << "detection\n";
signal(SIGINT, sig_handler); signal(SIGINT, sig_handler);
std::string net = "yolo3_berkeley.rt"; std::string net = "yolo3_berkeley.rt";
if(argc > 1) if (argc > 1)
net = argv[1]; net = argv[1];
std::string input = "../demo/yolo_test.mp4"; std::string input = "../demo/yolo_test.mp4";
if(argc > 2) if (argc > 2)
input = argv[2]; input = argv[2];
char ntype = 'y'; char ntype = 'y';
if(argc > 3) if (argc > 3)
ntype = argv[3][0]; ntype = argv[3][0];
int n_classes = 80; int n_classes = 80;
if(argc > 4) if (argc > 4)
n_classes = atoi(argv[4]); n_classes = atoi(argv[4]);
int n_batch = 1; int n_batch = 1;
if(argc > 5) if (argc > 5)
n_batch = atoi(argv[5]); n_batch = atoi(argv[5]);
bool show = true; bool show = true;
if(argc > 6) if (argc > 6)
show = atoi(argv[6]); show = atoi(argv[6]);
int port = 0;
if (argc > 7)
port = atoi(argv[7]);
if(n_batch < 1 || n_batch > 64) if (n_batch < 1 || n_batch > 64)
FatalError("Batch dim not supported"); FatalError("Batch dim not supported");
if(!show) if (!show)
SAVE_RESULT = true; SAVE_RESULT = true;
tk::dnn::Yolo3Detection yolo; tk::dnn::Yolo3Detection yolo;
tk::dnn::CenternetDetection cnet; tk::dnn::CenternetDetection cnet;
tk::dnn::MobilenetDetection mbnet; tk::dnn::MobilenetDetection mbnet;
tk::dnn::DetectionNN *detNN; tk::dnn::DetectionNN *detNN;
switch(ntype) switch (ntype)
{ {
case 'y': case 'y':
detNN = &yolo; detNN = &yolo;
break; break;
case 'c': case 'c':
detNN = &cnet; detNN = &cnet;
break; break;
case 'm': case 'm':
detNN = &mbnet; detNN = &mbnet;
n_classes++; n_classes++;
break; break;
default: default:
FatalError("Network type not allowed (3rd parameter)\n"); FatalError("Network type not allowed (3rd parameter)\n");
} }
@@ -74,66 +79,83 @@ int main(int argc, char *argv[]) {
gRun = true; gRun = true;
cv::VideoCapture cap(input); cv::VideoCapture cap(input);
if(!cap.isOpened()) if (!cap.isOpened())
gRun = false; gRun = false;
else else
std::cout<<"camera started\n"; std::cout << "camera started\n";
cv::VideoWriter resultVideo; cv::VideoWriter resultVideo;
if(SAVE_RESULT) { if (SAVE_RESULT)
{
int w = cap.get(cv::CAP_PROP_FRAME_WIDTH); int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
int h = cap.get(cv::CAP_PROP_FRAME_HEIGHT); int h = cap.get(cv::CAP_PROP_FRAME_HEIGHT);
resultVideo.open("result.mp4", cv::VideoWriter::fourcc('M','P','4','V'), 30, cv::Size(w, h)); resultVideo.open("result.mp4", cv::VideoWriter::fourcc('M', 'P', '4', 'V'), 30, cv::Size(w, h));
} }
cv::Mat frame; cv::Mat frame;
if(show) if (show)
cv::namedWindow("detection", cv::WINDOW_NORMAL); cv::namedWindow("detection", cv::WINDOW_NORMAL);
cv::moveWindow("detection", 0, 0);
cv::resizeWindow("detection", 1352, 1013);
std::vector<cv::Mat> batch_frame; std::vector<cv::Mat> batch_frame;
std::vector<cv::Mat> batch_dnn_input; std::vector<cv::Mat> batch_dnn_input;
while(gRun) { while (gRun)
{
batch_dnn_input.clear(); batch_dnn_input.clear();
batch_frame.clear(); batch_frame.clear();
for(int bi=0; bi< n_batch; ++bi){ for (int bi = 0; bi < n_batch; ++bi)
cap >> frame; {
if(!frame.data) cap >> frame;
if (!frame.data)
break; break;
batch_frame.push_back(frame); batch_frame.push_back(frame);
// this will be resized to the net format // this will be resized to the net format
batch_dnn_input.push_back(frame.clone()); batch_dnn_input.push_back(frame.clone());
} }
if(!frame.data) if (!frame.data)
break; break;
//inference //inference
detNN->update(batch_dnn_input, n_batch); detNN->update(batch_dnn_input, n_batch);
detNN->draw(batch_frame); detNN->draw(batch_frame);
if(show){ if (show)
for(int bi=0; bi< n_batch; ++bi){ {
for (int bi = 0; bi < n_batch; ++bi)
{
cv::imshow("detection", batch_frame[bi]); cv::imshow("detection", batch_frame[bi]);
cv::waitKey(1);
} }
} }
if(n_batch == 1 && SAVE_RESULT) if (cv::waitKey(1) == 27)
{
break;
}
if (n_batch == 1 && SAVE_RESULT)
resultVideo << frame; resultVideo << frame;
if (port > 0)
{
send_mjpeg(batch_frame[0], port, 400000, 40);
}
} }
std::cout<<"detection end\n"; std::cout << "detection end\n";
double mean = 0; double mean = 0;
std::cout<<COL_GREENB<<"\n\nTime stats:\n"; std::cout << COL_GREENB << "\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(detNN->stats.begin(), detNN->stats.end())/n_batch<<" ms\n"; std::cout << "Min: " << *std::min_element(detNN->stats.begin(), detNN->stats.end()) / n_batch << " ms\n";
std::cout<<"Max: "<<*std::max_element(detNN->stats.begin(), detNN->stats.end())/n_batch<<" ms\n"; std::cout << "Max: " << *std::max_element(detNN->stats.begin(), detNN->stats.end()) / n_batch << " ms\n";
for(int i=0; i<detNN->stats.size(); i++) mean += detNN->stats[i]; mean /= detNN->stats.size(); for (int i = 0; i < detNN->stats.size(); i++)
std::cout<<"Avg: "<<mean/n_batch<<" ms\t"<<1000/(mean/n_batch)<<" FPS\n"<<COL_END; mean += detNN->stats[i];
mean /= detNN->stats.size();
std::cout << "Avg: " << mean / n_batch << " ms\t" << 1000 / (mean / n_batch) << " FPS\n"
<< COL_END;
return 0; return 0;
} }