Qt调用darknet，供初学者使用

#include "mainwindow.h" #include "ui_mainwindow.h" #include <QSettings> MainWindow::MainWindow(QWidget *parent) : QMainWindow(parent), ui(new Ui::MainWindow) { ui->setupUi(this); connect(&timer, SIGNAL(timeout()), this, SLOT(Caculate())); timer.setSingleShot(true); timer.start(1000); } MainWindow::~MainWindow() { delete ui; } void MainWindow::Caculate() { list* options = read_data_cfg((char*)"cfg/coco.data"); char* name_list = option_find_str(options, (char*)"names", (char*)"data/names.list"); char** names = get_labels(name_list); image** alphabet = load_alphabet(); network* net = load_network((char*)"cfg/yolov2-tiny.cfg", (char*)"yolov2-tiny.weights", 0); set_batch_network(net, 1); srand(2222222); float nms = 0.45f; float thresh = 0.5f; float hier = 0.5f; IplImage* frame; qDebug()<<"endtime"<<QTime::currentTime().toString("HHmmss sss"); cv::Mat mat = cv::imread("data/dog"); IplImage imgTmp = mat; frame = cvCloneImage(&imgTmp); cvCvtColor(frame, frame, CV_BGR2RGB); image im = ipl_to_image(frame); image sized = letterbox_image(im, net->w, net->h); layer l = net->layers[net->n-1]; network_predict(net, sized.data); int nboxes = 0; detection* dets = get_network_boxes(net, im.w, im.h, thresh, hier, 0, 1, &nboxes); if(nms) do_nms_sort(dets, nboxes, l.classes, nms); draw_detections(im, dets, nboxes, thresh, names, alphabet, l.classes); save_image(im, "123"); int iCount = 0; for(int i=0; i<nboxes; ++i) { for(int j=0; j<l.classes; ++j) { if(dets[i].prob[j] > 0) { ++iCount; } } } free_detections(dets, nboxes); free_image(im); free_image(sized); qDebug()<<"detect count="<<iCount; qDebug()<<"starttime"<<QTime::currentTime().toString("HHmmss sss"); } image MainWindow::ipl_to_image(IplImage *src) { int h = src->height; int w = src->width; int c = src->nChannels; image out = make_image(w, h, c); ipl_into_image(src, out); return out; } image MainWindow::ipl_into_image(IplImage *src, image imag) { unsigned char* data = (unsigned char*)src->imageData; int h = src->height; int w = src->width; int c = src->nChannels; int step = src->widthStep; int i,j,k; for(i=0; i<h; ++i){ for(k=0; k<c; ++k){ for(j=0; j<w; ++j){ //imag.data[k*w*h + i*w + j] = data[i*step + j*c +k]/250.0; imag.data[k*w*h + i*w + j] = data[i*step + j*c +k]*0.003921569; } } } }