Rect haarPatternDetection(CascadeClassifier classifier, Mat image, int imageWidthforDetection, Rect parentRect=Rect()) {
double imageSizeScale = 1.0*image.size().width*1.0/image.size().height;
Mat color_img = image.clone();
Mat face_img, gray_img;
imresize(color_img, imageWidthforDetection,face_img);
cvtColor(face_img, gray_img, CV_BGR2GRAY);
equalizeHist(gray_img, gray_img);
vector<Rect> faceRectsVector;
classifier.detectMultiScale(gray_img, faceRectsVector,1.2,3,
CV_HAAR_FIND_BIGGEST_OBJECT | CV_HAAR_SCALE_IMAGE );
Rect faceRect(0,0,0,0);
for (int i = 0; i < faceRectsVector.size(); i++) {
drawBox(face_img, faceRectsVector[i]);
if (faceRect.area() < faceRectsVector[i].area())
faceRect = faceRectsVector[i];
}
drawBox(face_img, faceRect);
// imshow("rect",face_img);
double x = 1.0*faceRect.x/(double)imageWidthforDetection;
double y = 1.0*faceRect.y/(double)cvRound(imageWidthforDetection/imageSizeScale);
double w = 1.0*faceRect.width/(double)imageWidthforDetection;
double h = 1.0*faceRect.height/(double)cvRound(imageWidthforDetection/imageSizeScale);
int bx = cvRound(x*image.size().width) ;;//+ parentRect.tl().x;
int by = cvRound(y*image.size().height) ;//+ parentRect.tl().y;
int bw = cvRound(w*image.size().width);
int bh = cvRound(h*image.size().height);
Rect biggerRect(bx,by,bw,bh);
biggerRect += parentRect.tl();
return biggerRect;
}
QRect DigikamImageFaceDelegate::largerFaceRect(const QModelIndex& index) const
{
QRect rect = faceRect(index);
if (rect.isNull())
{
return rect;
}
const int margin = FaceUtils::faceRectDisplayMargin();
return rect.adjusted(-margin, -margin, margin, margin);
}
Mat Detector::detect(string imgname){
//cout<<"Debug: "<<debug<<endl;
Mat resized;
IplImage *frame = cvLoadImage(imgname.data(), 2|4);
if (frame == NULL)
{
fprintf(stderr, "Cannot open image %s.Returning empty Mat...\n", imgname.data());
return resized;
}
else if (frame->width < 100 || frame->height < 100)
{
fprintf(stderr, "image %s too small.Returning empty Mat...\n", imgname.data());
cvReleaseImage(&frame);
return resized;
}
else if (frame->width > 100000 || frame->height > 100000)
{
fprintf(stderr, "image %s too large.Returning empty Mat...\n", imgname.data());
cvReleaseImage(&frame);
return resized;
}
// convert image to grayscale
IplImage *frame_bw = cvCreateImage(cvSize(frame->width, frame->height), IPL_DEPTH_8U, 1);
cvConvertImage(frame, frame_bw);
Mat frame_mat(frame, 1);
// Smallest face size.
CvSize minFeatureSize = cvSize(100, 100);
int flags = CV_HAAR_DO_CANNY_PRUNING;
// How detailed should the search be.
float search_scale_factor = 1.1f;
CvMemStorage* storage;
CvSeq* rects;
int nFaces;
storage = cvCreateMemStorage(0);
cvClearMemStorage(storage);
// Detect all the faces in the greyscale image.
rects = cvHaarDetectObjects(frame_bw, faceCascade, storage, search_scale_factor, 2, flags, minFeatureSize);
//rects = MBLBPDetectMultiScale(frame_bw, faceCascade, storage, 1229, 1, 50, 500);
nFaces = rects->total;
if (nFaces != 1){
if (debug)
printf("%d faces detected\n", nFaces);
storage = cvCreateMemStorage(0);
cvReleaseMemStorage(&storage);
cvReleaseImage(&frame_bw);
cvReleaseImage(&frame);
return resized;
}
int iface = 0;
CvRect *r = (CvRect*)cvGetSeqElem(rects, iface);
double* landmarks = new double[2*fmodel->data.options.M];
int bbox[4];
bbox[0] = r->x;
bbox[1] = r->y;
bbox[2] = r->x + r->width;
bbox[3] = r->y + r->height;
// Detect landmarks
flandmark_detect(frame_bw, bbox, fmodel, landmarks);
//align faces
double angle[3];
angle[0] = atan((landmarks[7]-landmarks[9])/(landmarks[6]-landmarks[8]));
angle[1] = atan((landmarks[11]-landmarks[13])/(landmarks[10]-landmarks[12]));
angle[2] = atan((landmarks[3]-landmarks[5])/(landmarks[2]-landmarks[4]));
//cout<<angle[0]*180<<" "<<angle[1]*180<<" "<<angle[2]*180<<endl;
double angle_rotate = 0;
if (angle[0] > angle[1]){
if (angle[1] > angle[2])
angle_rotate = angle[1];
else if (angle[0] > angle[2])
angle_rotate = angle[2];
else
angle_rotate = angle[0];
}
else{
if (angle[1] < angle[2])
angle_rotate = angle[1];
else if (angle[2] < angle[0])
angle_rotate = angle[0];
else
angle_rotate = angle[2];
}
Rect faceRect(r->x, r->y,r->width, r->height);
//save face to tmp if debug
if (debug){
cvRectangle(frame, cvPoint(bbox[0], bbox[1]), cvPoint(bbox[2], bbox[3]), CV_RGB(255,0,0) );
cvRectangle(frame, cvPoint(fmodel->bb[0], fmodel->bb[1]), cvPoint(fmodel->bb[2], fmodel->bb[3]), CV_RGB(0,0,255) );
cvCircle(frame, cvPoint((int)landmarks[0], (int)landmarks[1]), 3, CV_RGB(0,0,255), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[2]), int(landmarks[3])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[4]), int(landmarks[5])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[6]), int(landmarks[7])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[8]), int(landmarks[9])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[10]), int(landmarks[11])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[12]), int(landmarks[13])), 3, CV_RGB(255,0,0), CV_FILLED);
cvCircle(frame, cvPoint(int(landmarks[14]), int(landmarks[15])), 3, CV_RGB(255,0,0), CV_FILLED);
Mat face(frame, 0);
Mat croppedFaceImage = face(faceRect).clone();
Mat rotated = rotateImage(croppedFaceImage, angle_rotate * 180 / PI);
resize(rotated, resized, Size(100, 100));
imwrite( "./tmp/face.jpg" , resized );
}
delete [] landmarks;
storage = cvCreateMemStorage(0);
cvReleaseMemStorage(&storage);
cvReleaseImage(&frame_bw);
cvReleaseImage(&frame);
if (faceRect.height < 50 && faceRect.width < 50){
printf("Face too small: %d x %d\n", faceRect.height, faceRect.width);
return resized;
}
Mat croppedFaceImage = frame_mat(faceRect).clone();
Mat rotated = rotateImage(croppedFaceImage, angle_rotate * 180 / PI);
resize(rotated, resized, Size(100, 100));
return resized;
}
