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#include "opencv2/datasets/pd_inria.hpp"
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
#include <iostream>
using namespace std;
using namespace cv;
using namespace cv::datasets;
int main(int argc, char *argv[])
{
const char *keys =
"{ help h usage ? | | show this message }"
"{ path p |true | path to dataset }"
"{ save s |false| save resized positive images }"
"{ rwidth rw |64 | width of resized positive images }"
"{ rheight rh |128 | height of resized positive images }"
"{ padding |8 | vertical padding of resized positive images }";
CommandLineParser parser(argc, argv, keys);
bool savebbox = parser.get<bool>("save");
int rwidth = parser.get<int>("rwidth");
int rheight = parser.get<int>("rheight");
int padding = parser.get<int>("padding");
string path(parser.get<string>("path"));
if (parser.has("help") || path=="true")
{
parser.printMessage();
return -1;
}
Ptr<PD_inria> dataset = PD_inria::create();
dataset->load(path);
size_t train_size = dataset->getTrain().size();
size_t test_size = dataset->getTest().size();
cout << "train size: " << train_size << endl;
cout << "test size: " << test_size << endl;
int bbox_count = 0;
for( size_t i = 0; i < train_size; i++ )
{
PD_inriaObj *example = static_cast<PD_inriaObj *>(dataset->getTrain()[i].get());
cout << "\ntrain object index: " << i << endl;
cout << "file name: " << example->filename << endl;
// image size
cout << "image size: " << endl;
cout << " - width: " << example->width << endl;
cout << " - height: " << example->height << endl;
cout << " - depth: " << example->depth << endl;
Mat img = imread( example->filename );
// bounding boxes
for ( size_t j = 0; j < example->bndboxes.size(); j++ )
{
Rect obj_bndbox = example->bndboxes[j]; // bounding box of object
cout << " - bounding box: " << j << " - " << obj_bndbox << endl;
int vpadding, hpadding;
Rect ex_bndbox; // variable used for calculating expanded bounding box
vpadding = cvRound(padding * obj_bndbox.height / rheight); // calculate vertical padding
ex_bndbox.y = obj_bndbox.y - vpadding;
ex_bndbox.height = 2 * vpadding + obj_bndbox.height;
ex_bndbox.x = obj_bndbox.x + (obj_bndbox.width / 2);
ex_bndbox.width = ex_bndbox.height * rwidth / rheight;
ex_bndbox.x -= (ex_bndbox.width + 1) / 2;
if (obj_bndbox.width > ex_bndbox.width)
{
obj_bndbox.x += (obj_bndbox.width - ex_bndbox.width + 1) / 2;
obj_bndbox.width = ex_bndbox.width;
}
hpadding = obj_bndbox.x - ex_bndbox.x; // calculate horizontal padding
if(savebbox)
{
Mat dst;
copyMakeBorder(img(obj_bndbox), dst, vpadding, vpadding, hpadding, hpadding, BORDER_REFLECT);
resize(dst, dst, Size(rwidth, rheight), 0, 0, INTER_AREA);
imwrite(path + format("person_%04d.png", bbox_count++), dst);
}
else
rectangle(img, obj_bndbox, Scalar(0, 0, 255), 2);
}
if (savebbox)
continue; // skip UI updates
imshow("INRIAPerson Dataset Train Images", img);
cout << "\nPress a key to continue or ESC to exit." << endl;
int key = waitKey();
if( key == 27 ) break;
}
return 0;
}
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