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Move multiple demo files into one

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
This commit is contained in:
Davide Sapienza
2020-03-03 17:30:35 +01:00
parent 296a6cbc87
commit 01a42ffe27
5 changed files with 140 additions and 276 deletions
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CMakeLists.txt
+2 -12
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@@ -115,18 +115,8 @@ target_link_libraries(test_dla34_cnet tkDNN)
add_executable(test_rtinference tests/test_rtinference/rtinference.cpp) add_executable(test_rtinference tests/test_rtinference/rtinference.cpp)
target_link_libraries(test_rtinference tkDNN) target_link_libraries(test_rtinference tkDNN)
add_executable(yolo3_demo demo/demo/demo_yolo3.cpp) add_executable(demo demo/demo/demo.cpp)
target_link_libraries(yolo3_demo tkDNN) target_link_libraries(demo tkDNN)
add_executable(centernet_demo demo/demo/demo_centernet.cpp)
target_link_libraries(centernet_demo tkDNN)
add_executable(mobilenet_demo demo/demo/demo_mobilenet.cpp)
target_link_libraries(mobilenet_demo tkDNN)
add_executable(map_demo demo/demo/map.cpp)
target_link_libraries(map_demo tkDNN)
#------------------------------------------------------------------------------- #-------------------------------------------------------------------------------
# Install # Install
demo/demo/demo.cpp
+138
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@@ -0,0 +1,138 @@
#include <iostream>
#include <signal.h>
#include <stdlib.h> /* srand, rand */
#include <unistd.h>
#include <mutex>
#include "CenternetDetection.h"
#include "MobilenetDetection.h"
#include "Yolo3Detection.h"
bool gRun;
bool SAVE_RESULT = false;
void sig_handler(int signo) {
std::cout<<"request gateway stop\n";
gRun = false;
}
int main(int argc, char *argv[]) {
std::cout<<"detection\n";
signal(SIGINT, sig_handler);
char *net = "yolo3_berkeley.rt";
if(argc > 1)
net = argv[1];
char *input = "../demo/yolo_test.mp4";
if(argc > 2)
input = argv[2];
char ntype = 'y';
if(argc > 3)
ntype = argv[3][0];
tk::dnn::Yolo3Detection yolo;
tk::dnn::CenternetDetection cnet;
tk::dnn::MobilenetDetection mbnet;
switch(ntype)
{
case 'y':
yolo.init(net);
break;
case 'c':
cnet.init(net);
break;
case 'm':
mbnet.init(net);
break;
default:
FatalError("Network type not allowed (3rd parameter)\n");
}
gRun = true;
cv::VideoCapture cap(input);
if(!cap.isOpened())
gRun = false;
else
std::cout<<"camera started\n";
cv::VideoWriter resultVideo;
if(SAVE_RESULT) {
int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
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));
}
cv::Mat frame;
cv::Mat dnn_input;
cv::namedWindow("detection", cv::WINDOW_NORMAL);
std::vector<tk::dnn::box> detected_bbox;
while(gRun) {
cap >> frame;
if(!frame.data) {
break;
}
// this will be resized to the net format
dnn_input = frame.clone();
// TODO: async infer
switch(ntype)
{
case 'y':
yolo.update(dnn_input);
frame = yolo.draw(frame);
break;
case 'c':
cnet.update(dnn_input);
frame = cnet.draw(dnn_input);
break;
case 'm':
mbnet.update(dnn_input);
frame = mbnet.draw();
break;
default:
FatalError("Network type not allowed!\n");
}
cv::imshow("detection", frame);
cv::waitKey(1);
if(SAVE_RESULT)
resultVideo << frame;
}
std::cout<<"detection end\n";
double mean = 0;
switch(ntype)
{
case 'y':
std::cout<<COL_GREENB<<"\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
std::cout<<"Max: "<<*std::max_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
for(int i=0; i<yolo.stats.size(); i++) mean += yolo.stats[i]; mean /= yolo.stats.size();
std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
break;
case 'c':
std::cout<<COL_GREENB<<"\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(cnet.stats.begin(), cnet.stats.end())<<" ms\n";
std::cout<<"Max: "<<*std::max_element(cnet.stats.begin(), cnet.stats.end())<<" ms\n";
for(int i=0; i<cnet.stats.size(); i++) mean += cnet.stats[i]; mean /= cnet.stats.size();
std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
break;
case 'm':
std::cout<<COL_GREENB<<"\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(mbnet.stats.begin(), mbnet.stats.end())<<" ms\n";
std::cout<<"Max: "<<*std::max_element(mbnet.stats.begin(), mbnet.stats.end())<<" ms\n";
for(int i=0; i<mbnet.stats.size(); i++) mean += mbnet.stats[i]; mean /= mbnet.stats.size();
std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
break;
default:
FatalError("Network type not allowed!\n");
}
return 0;
}
demo/demo/demo_centernet.cpp
-88
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@@ -1,88 +0,0 @@
#include <iostream>
#include <signal.h>
#include <stdlib.h> /* srand, rand */
#include <unistd.h>
#include <mutex>
#include "utils.h"
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "CenternetDetection.h"
bool gRun;
bool SAVE_RESULT = false;
void sig_handler(int signo) {
std::cout<<"request gateway stop\n";
gRun = false;
}
int main(int argc, char *argv[]) {
std::cout<<"detection\n";
signal(SIGINT, sig_handler);
char *net = "resnet101_cnet.rt";
if(argc > 1)
net = argv[1];
char *input = "../demo/yolo_test.mp4";
if(argc > 2)
input = argv[2];
tk::dnn::CenternetDetection cnet;
cnet.init(net);
gRun = true;
cv::VideoCapture cap(input);
if(!cap.isOpened())
gRun = false;
else
std::cout<<"camera started\n";
cv::VideoWriter resultVideo;
if(SAVE_RESULT) {
int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
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));
}
cv::Mat frame;
cv::Mat dnn_input;
cv::namedWindow("detection", cv::WINDOW_NORMAL);
while(gRun) {
cap >> frame;
if(!frame.data) {
break;
}
// this will be resized to the net format
dnn_input = frame.clone();
// TODO: async infer
cnet.update(dnn_input);
// draw dets
frame = cnet.draw(dnn_input);
cv::imshow("detection", frame);
cv::waitKey(1);
if(SAVE_RESULT)
resultVideo << frame;
}
std::cout<<"detection end\n";
std::cout<<COL_GREENB<<"\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(cnet.stats.begin(), cnet.stats.end())<<" ms\n";
std::cout<<"Max: "<<*std::max_element(cnet.stats.begin(), cnet.stats.end())<<" ms\n";
double mean = 0; for(int i=0; i<cnet.stats.size(); i++) mean += cnet.stats[i]; mean /= cnet.stats.size();
std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
return 0;
}
demo/demo/demo_mobilenet.cpp
-88
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@@ -1,88 +0,0 @@
#include <iostream>
#include <signal.h>
#include <stdlib.h> /* srand, rand */
#include <unistd.h>
#include <mutex>
#include "MobilenetDetection.h"
bool gRun;
bool SAVE_RESULT = false;
void sig_handler(int signo)
{
std::cout << "request gateway stop\n";
gRun = false;
}
int main(int argc, char *argv[])
{
std::cout << "detection\n";
signal(SIGINT, sig_handler);
char *net = "mobilenetv2ssd.rt";
if (argc > 1)
net = argv[1];
char *input = "../demo/yolo_test.mp4";
if (argc > 2)
input = argv[2];
tk::dnn::MobilenetDetection mbnet;
mbnet.init(net);
gRun = true;
cv::VideoCapture cap(input);
if (!cap.isOpened())
gRun = false;
else
std::cout << "camera started\n";
cv::VideoWriter resultVideo;
if (SAVE_RESULT)
{
int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
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));
}
cv::Mat frame;
cv::Mat dnn_input;
cv::namedWindow("detection", cv::WINDOW_NORMAL);
while (gRun)
{
cap >> frame;
if (!frame.data)
{
break;
}
// this will be resized to the net format
dnn_input = frame.clone();
// TODO: async infer
mbnet.update(dnn_input);
// draw dets
frame = mbnet.draw();
cv::imshow("detection", frame);
cv::waitKey(1);
if (SAVE_RESULT)
resultVideo << frame;
}
std::cout << "detection end\n";
std::cout << COL_GREENB << "\n\nTime stats:\n";
std::cout << "Min: " << *std::min_element(mbnet.stats.begin(), mbnet.stats.end()) << " ms\n";
std::cout << "Max: " << *std::max_element(mbnet.stats.begin(), mbnet.stats.end()) << " ms\n";
double mean = 0;
for (int i = 0; i < mbnet.stats.size(); i++)
mean += mbnet.stats[i];
mean /= mbnet.stats.size();
std::cout << "Avg: " << mean << " ms\n"
<< COL_END;
return 0;
}
demo/demo/demo_yolo3.cpp
-88
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@@ -1,88 +0,0 @@
#include <iostream>
#include <signal.h>
#include <stdlib.h> /* srand, rand */
#include <unistd.h>
#include <mutex>
#include "utils.h"
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include "Yolo3Detection.h"
bool gRun;
bool SAVE_RESULT = false;
void sig_handler(int signo) {
std::cout<<"request gateway stop\n";
gRun = false;
}
int main(int argc, char *argv[]) {
std::cout<<"detection\n";
signal(SIGINT, sig_handler);
char *net = "yolo3_berkeley.rt";
if(argc > 1)
net = argv[1];
char *input = "../demo/yolo_test.mp4";
if(argc > 2)
input = argv[2];
tk::dnn::Yolo3Detection yolo;
yolo.init(net);
gRun = true;
cv::VideoCapture cap(input);
if(!cap.isOpened())
gRun = false;
else
std::cout<<"camera started\n";
cv::VideoWriter resultVideo;
if(SAVE_RESULT) {
int w = cap.get(cv::CAP_PROP_FRAME_WIDTH);
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));
}
cv::Mat frame;
cv::Mat dnn_input;
cv::namedWindow("detection", cv::WINDOW_NORMAL);
while(gRun) {
cap >> frame;
if(!frame.data) {
break;
}
// this will be resized to the net format
dnn_input = frame.clone();
// TODO: async infer
yolo.update(dnn_input);
frame = yolo.draw(frame);
cv::imshow("detection", frame);
cv::waitKey(1);
if(SAVE_RESULT)
resultVideo << frame;
}
std::cout<<"detection end\n";
std::cout<<COL_GREENB<<"\n\nTime stats:\n";
std::cout<<"Min: "<<*std::min_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
std::cout<<"Max: "<<*std::max_element(yolo.stats.begin(), yolo.stats.end())<<" ms\n";
double mean = 0; for(int i=0; i<yolo.stats.size(); i++) mean += yolo.stats[i]; mean /= yolo.stats.size();
std::cout<<"Avg: "<<mean<<" ms\n"<<COL_END;
return 0;
}