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#include <opencv2/xobjdetect.hpp>
#include <opencv2/imgcodecs/imgcodecs_c.h>
#include <opencv2/imgproc.hpp>
#include <iostream>
#include <cstdio>
using namespace std;
using namespace cv;
using namespace cv::xobjdetect;
int main(int argc, char **argv)
{
if (argc < 5) {
cerr << "Usage: " << argv[0] << " train <model_filename> <pos_path> <neg_path>" << endl;
cerr << " " << argv[0] << " detect <model_filename> <img_filename> <out_filename> <labelling_filename>" << endl;
return 0;
}
string mode = argv[1];
Ptr<WBDetector> detector = WBDetector::create();
if (mode == "train") {
assert(argc == 5);
detector->train(argv[3], argv[4]);
FileStorage fs(argv[2], FileStorage::WRITE);
fs << "waldboost";
detector->write(fs);
} else if (mode == "detect") {
assert(argc == 6);
vector<Rect> bboxes;
vector<double> confidences;
Mat img = imread(argv[3], CV_LOAD_IMAGE_GRAYSCALE);
FileStorage fs(argv[2], FileStorage::READ);
detector->read(fs.getFirstTopLevelNode());
detector->detect(img, bboxes, confidences);
FILE *fhandle = fopen(argv[5], "a");
for (size_t i = 0; i < bboxes.size(); ++i) {
Rect o = bboxes[i];
fprintf(fhandle, "%s;%u;%u;%u;%u;%lf\n",
argv[3], o.x, o.y, o.width, o.height, confidences[i]);
}
for (size_t i = 0; i < bboxes.size(); ++i) {
rectangle(img, bboxes[i], Scalar(255, 0, 0));
}
imwrite(argv[4], img);
}
}
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