function out = resnet50_wrapper(im)
persistent yolov2Obj;
opencv_link_flags = '`pkg-config --cflags --libs opencv`';
coder.updateBuildInfo('addLinkFlags',opencv_link_flags);
if isempty(yolov2Obj)
yolov2Obj = coder.loadDeepLearningNetwork('C:\Users\josep\Desktop\Fall_2019\Senior_Design\Matlab_Tools\yolov2_5eps_128.mat');
end
[bboxes,~,labels] = yolov2Obj.detect(im,'Threshold',0.5);
out = insertObjectAnnotation(im,'rectangle',bboxes,labels);
end
/* The MathWorks Inc. 2019*/
/* ResNet50 demo main.cu file with OpenCV interfaces to read and display data. */
#include "resnet50_wrapper.h"
#include "main.h"
#include "resnet50_wrapper_terminate.h"
#include "resnet50_wrapper_initialize.h"
#include "opencv2/opencv.hpp"
#include <stdio.h>
#include <stdlib.h>
#define IMG_WIDTH 224
#define IMG_HEIGHT 224
#define IMG_CH 3
#define VID_DEV_ID 1
using namespace cv;
using namespace std;
static void main_resnet50_wrapper();
/*
* Convert BGR data to RGB data, without this conversion the predictions
* will be bad
*/
static void argInit_224x224x3_real32_T(real32_T *input, Mat & im)
{
for(int j=0;j<224*224;j++)
{
//BGR to RGB
input[2*224*224+j]=(float)(im.data[j*3+0]);
input[1*224*224+j]=(float)(im.data[j*3+1]);
input[0*224*224+j]=(float)(im.data[j*3+2]);
}
}
static void main_resnet50_wrapper(void)
{
static real32_T b[150528];
static real32_T out[150528];
Mat oFrame, cFrame;
/* Create a Video capture object */
VideoCapture cap(VID_DEV_ID);
if(!cap.isOpened())
{
cout << "can't open camera" << endl;
exit(0);
}
namedWindow("resnet Demo",CV_WINDOW_NORMAL);
resizeWindow("resnet Demo", 1000,1000);
float fps=0;
cudaEvent_t start, stop;
cudaEventCreate(&start);
cudaEventCreate(&stop);
while(1)
{
cap >> oFrame;
resize(oFrame,cFrame,Size(IMG_WIDTH,IMG_HEIGHT));
/* convert from BGR to RGB*/
argInit_224x224x3_real32_T(b,cFrame);
cudaEventRecord(start);
/* call the resnet predict function*/
// resnet50_wrapper(b, out);
resnet50_wrapper(b,out);
cudaEventRecord(stop);
cudaEventSynchronize(stop);
float milliseconds = -1.0;
cudaEventElapsedTime(&milliseconds, start, stop);
fps = fps*.9+1000.0/milliseconds*.1;
// convert out -> oFrame
// show display
imshow("Yolo Demo", oFrame);
if(waitKey(1)
}
}
int32_T main(int32_T argc, const char * const argv[])
{
(void)argc;
(void)argv;
/* Call the application intialize function */
resnet50_wrapper_initialize();
/* Call the resnet predict function */
main_resnet50_wrapper();
/* Call the application terminate function */
resnet50_wrapper_terminate();
return 0;
}
