void Gui_DisplayBaseClass::redraw(){
DEV_INFOS("redrawing");
cv::Mat tmp_img;
cv::Point2f offset;
drawBackground();
if(!m_processor_hand.getSourceImgAsRGB(tmp_img)){
if(!m_banner_pixbuf)
m_banner_pixbuf = Gui_PixbufOpener::pixbufOpen(BANNER_IMG);
offset = m_ROI.scaleToFitAllocation(m_banner_pixbuf, m_pixbuf);
}
else{
m_banner_pixbuf.clear();
cv::Point2f raw_img_dim(tmp_img.cols,tmp_img.rows);
m_ROI.update(raw_img_dim);
tmp_img(m_ROI).copyTo(tmp_img);
offset = m_ROI.scaleToFitAllocation(tmp_img, m_img_to_display);
m_pixbuf = Gdk::Pixbuf::create_from_data((guint8*)m_img_to_display.data,Gdk::COLORSPACE_RGB,false,
8,m_img_to_display.cols,m_img_to_display.rows,m_img_to_display.step);
//show mask
if(getMask(tmp_img) && m_show_mask){
DEV_INFOS("drawing mask "<<cv::Point2f(tmp_img.rows,tmp_img.cols)<<" vs "<<raw_img_dim);
tmp_img(m_ROI).copyTo(tmp_img);
cv::LUT(tmp_img,m_LUT,tmp_img);
m_ROI.scaleToFitAllocation(tmp_img, tmp_img,true);
m_mask_pixbuf = Gdk::Pixbuf::create_from_data((guint8*)tmp_img.data,Gdk::COLORSPACE_RGB,false,
8,tmp_img.cols,tmp_img.rows,tmp_img.step);
m_mask_pixbuf = m_mask_pixbuf->add_alpha(true,0,0,0);
m_mask_pixbuf->composite ( m_pixbuf,0,0,
m_mask_pixbuf->get_width(),m_mask_pixbuf->get_height(),
0,0,1,1,Gdk::INTERP_NEAREST,
m_alph_mask//int overall_alpha
);
}
}
m_pixbuf->render_to_drawable(get_window(), get_style()->get_black_gc(),0, 0,
offset.x, offset.y, m_pixbuf->get_width(), m_pixbuf->get_height(),Gdk::RGB_DITHER_NONE, 0, 0);
if(m_draw_result)
m_deco.decorate();
}
/**
* @brief Tests QR detection with a zero-sized image. Should return 0 qrs
*/
TEST_F(QrDetectionTest, zero_sized_image_test)
{
cv::Mat tmp_img(0, 0, CV_8UC1);
std::vector<QrCode> qrs;
qrs = qr_detector_->detectQrs(tmp_img);
EXPECT_EQ(0, qrs.size());
}
TEST_F(QrDetectionTest, zero_sized_image_test)
{
cv::Mat tmp_img(0, 0, CV_8UC1);
std::vector<cv::Point> points;
std::vector<std::string> messages;
qr_detector_->detectQrs(tmp_img, points, messages);
EXPECT_EQ(0, messages.size());
}
TEST_F(FaceDetectionTest, zero_sized_image_test)
{
cv::Mat tmp_img(0, 0, CV_8UC1);
std::vector<cv::Rect> faces = face_detector_->detectFaces(tmp_img);
EXPECT_EQ(0,faces.size());
}
ImageT<int> *relabelOutput (Image &Img, char *labelname, char *descr)
{
Image hist = Img.calcHistogram(0, 256, 256);
int max = 255;
while (hist.getInt (max, 0, 0) == 0 && max > 0)
max--;
if (!max) {
cout << "no texture classes in output segmentation!" << endl;
exit (-1);
}
else
cout << "identified " << max << " texture classes in segmentation result" << endl;
ImageT<int> *result_img = new ImageT<int>(Img.sizeX (), Img.sizeY ());
result_img->typeImage(_PFM_SINT);
ImageT<int> tmp_img(Img.sizeX(), Img.sizeY());
tmp_img.typeImage(_PFM_SINT);
cout << "neue Bilder angelegt" << endl;
int *dest, *source;
unsigned char *orig;
int sumlabel[max + 1];
memset(sumlabel, 0, sizeof (int) * (max + 1));
cout << "memset Befehl" << endl;
// sumlabel stores the number of labels found for each class,
// labelling should start with 1
sumlabel[0] = 1;
for (int i = 1; i <= max; i++) {
dest = tmp_img.data();
orig = (unsigned char *) Img.data();
cout << "Schleife über i" << endl;
// extract one class and prepare it for labelling
for (int j = 0; j < Img.sizeImage (); ++j, ++dest, ++orig)
if (*orig == i)
*dest = 0;
else
*dest = 1;
// label the current class and store the number of labels
// label 0 and 1 are background and label border --> throw them away (-2)!
sumlabel[i] = labelImage(tmp_img) - 2;
// sum up the labelnumbers for fusion of the different classes
sumlabel[i] += sumlabel[i - 1];
// shift the labels, so that they are unique (fusion)
source = tmp_img.data();
dest = result_img->data();
for (int j = 0; j < tmp_img.sizeImage(); ++j, ++dest, ++source) {
// if the label is not background or border (-2), add it to the result
if (*source > 1)
*dest = *source - 2 + sumlabel[i - 1];
}
tmp_img.clear();
}
cout << "image relabeled" << endl;
// generate the label description
ImageT<int> list;
calcBoundingBoxes(list, *result_img, sumlabel[max]);
FILE *fp = fopen (descr, "w");
if (!fp)
{
cout << "error opening file " << descr << " for writing." << endl;
exit (-1);
}
// list only the labels with value greater than zero (0 is background)
for (int i = 1, j = 0; i < sumlabel[max]; ++i)
{
if (i >= sumlabel[j + 1])
j ++;
fprintf(fp, "<region class=\"class%i\" id=\"%d\" p=\"0.7\" file=\"%s\" llx=\"%d\" lly=\"%d\" urx=\"%d\" ury=\"%d\" />\n",
j+1, i, labelname, list[0][i], list[1][i], list[2][i], list[3][i]);
}
cout << "Regionenbeschreibung erzeugt" << endl;
fclose(fp);
return (result_img);
}
