bool GeoMapEditor::addMouseObject( // пытаемся добавить новый объект вытянув или кликнув мышкой
cv::Rect& rect, // note: in-out -- подкручиваем ректангл по законам первого рождения для данного объекта
int flags )
{
if (objType() == "AGM_Segm")
{
Point xyTL = rect.tl();
Point xyBR = rect.br();
GeoSheet& sh = gm.sheets[ cur_sheet ];
Point2d enTL = sh.xy2en( xyTL );
Point2d enBR = sh.xy2en( xyBR );
AGM_Segm* ps = new AGM_Segm(enTL, enBR);
gm.objects.push_back(cv::Ptr<AGM_Segm>(ps));
}
else
{
Point xy = center( rect );
GeoSheet& sh = gm.sheets[ cur_sheet ];
Point2d en = sh.xy2en( xy );
AGM_Point* pp = new AGM_Point( en );
gm.objects.push_back(cv::Ptr<AGM_Point>(pp));
}
return true;
};
static bool checkColision(const cv::Rect &a, const cv::Rect &b){
if (b.contains(a.tl())) return true;
if (b.contains(a.br())) return true;
if (b.contains(cv::Point(a.x+a.width,a.y))) return true;
if (b.contains(cv::Point(a.x,a.y+a.height))) return true;
return false;
}
void LevelTracker::setRegion(const cv::Rect &roi)
{
topLeft=roi.tl();
bottonRight=roi.br();
if(topLeft.x<bottonRight.x && topLeft.y<bottonRight.y)
regOk=true;
}
bool findTop(cv::Point& top, int& topVal, cv::Mat* src, cv::Rect rect){
cv::Point res(0, 0);
int x = 0, y = 0;
bool bFound = false;
topVal = 65535;
if (!src->empty()){
try
{
for (int i = rect.tl().y; i < rect.br().y; ++i){
for (int j = rect.tl().x; j < rect.br().x; ++j){
{
Int16 curVarVec = Convert::ToInt16((src->at<Int16>(cv::Point(j, i))) * 255.0f / 8191.0f);
if (curVarVec < topVal && curVarVec > 0)
{
topVal = curVarVec;
x = j;
y = i;
bFound = true;
}
}
}
}
}
catch(...)
{
// DO NOTHING
}
}
//ht.nNose = src->at<Int16>(0,0);
if(bFound) top = cv::Point(x,y);
return bFound;
}
double overlapJaccard(cv::Rect& r1,cv::Rect& r2){
double overlap=(r1 & r2).area();
double overlapJaccard=overlap/(r1.area()+r2.area()-overlap);
return overlapJaccard;
}
inline static cv::Point center(const cv::Rect &rc)
{
std::vector<cv::Point> pts;
pts.push_back(rc.tl());
pts.push_back(rc.br());
return center(pts);
}
// A litte subroutine to draw a box onto an image
//
void draw_box(cv::Mat& img, cv::Rect box) {
cv::rectangle(
img,
box.tl(),
box.br(),
cv::Scalar(0x00, 0x00, 0xff) /* red */
);
}
//[0; 1] (0.5 when different_area == common_area)
inline float rect_similarity(const cv::Rect &r1, const cv::Rect &r2)
{
float common = (r1 & r2).area();
float different = (r1.area() + r2.area() - 2.0f * common);
if (different > FLT_EPSILON)
return std::min(0.5f * common / different, 1.0f);
else
return 1.0f;
}
void BlobPeople::update(const cv::Rect& track) {
cur = toOf(track).getCenter();
smooth.interpolate(cur, 0.5);
height = track.tl().y-track.br().y;
bottom = track.br().y;
left = track.tl().x;
right = track.br().x;
}
void Rectangle::set(const cv::Rect &_rect)
{
rect = _rect;
tl = _rect.tl();
br = _rect.br();
left->set(tl, cv::Point(tl.x, br.y));
top->set(tl, cv::Point(br.x, tl.y));
bottom->set(tl, cv::Point(tl.x, br.y));
right->set(cv::Point(br.x, tl.y), cv::Point(tl.x, br.y));
info.set(_rect);
}
/**
* @brief Scales and translates a facebox. Useful for converting
* between face boxes from different face detectors.
*
* To convert from V&J faceboxes to ibug faceboxes, use a scaling
* of 0.85 and a translation_y of 0.2.
* Ideally, we would learn the exact parameters from data.
*
* @param[in] facebox Input facebox.
* @param[in] scaling The input facebox will be scaled by this factor.
* @param[in] translation_y How much, in percent of the original facebox's width, the facebox will be translated in y direction. A positive value means facebox moves downwards.
* @return The rescaled facebox.
*/
cv::Rect rescale_facebox(cv::Rect facebox, float scaling, float translation_y)
{
// Assumes a square input facebox to work? (width==height)
const auto new_width = facebox.width * scaling;
const auto smaller_in_px = facebox.width - new_width;
const auto new_tl = facebox.tl() + cv::Point2i(smaller_in_px / 2.0f, smaller_in_px / 2.0f);
const auto new_br = facebox.br() - cv::Point2i(smaller_in_px / 2.0f, smaller_in_px / 2.0f);
cv::Rect rescaled_facebox(new_tl, new_br);
rescaled_facebox.y += facebox.width * translation_y;
return rescaled_facebox;
};
float jaccardSimilarity(cv::Rect bbox1, cv::Rect bbox2) {
cv::Vec4i bi(std::max(bbox1.x, bbox2.x), std::max(bbox1.y,bbox2.y), std::min(bbox1.br().x,bbox2.br().x), std::min(bbox1.br().y,bbox2.br().y));
int iw = bi[2] - bi[0];
int ih = bi[3] - bi[1];
if (iw > 0 && ih > 0) {
int un = (bbox1.br().x - bbox1.x) * (bbox1.br().y - bbox1.y) +
(bbox2.br().x - bbox2.x) * (bbox2.br().y - bbox2.y) - iw * ih;
return iw * ih / float(un);
}
return 0.f;
}
void CallBackFunc(int evnt, int x, int y, int flags, void* userdata) {
if (evnt == cv::EVENT_LBUTTONDOWN) {
mouseButtonDown = true;
targetSelected = false;
boundingRect = cv::Rect(0,0,0,0);
point1 = cv::Point(x,y);
cv::destroyWindow(targetName);
cv::destroyWindow(ColorTracker.getColorSquareWindowName());
targetImage.release();
}
if (evnt == cv::EVENT_MOUSEMOVE) {
if (x < 0) x = 0;
else if (x > image.cols) x = image.cols;
if (y < 0) y = 0;
else if (y > image.rows) y = image.rows;
point2 = cv::Point(x,y);
if (mouseButtonDown) {
boundingRect = cv::Rect(point1,point2);
}
cv::imshow(imageName,image);
}
if (evnt == cv::EVENT_LBUTTONUP) {
mouseButtonDown = false;
if (boundingRect.area() != 0) {
targetImage = image(calibratedRect(boundingRect));
cv::imshow(targetName, targetImage);
}
else {
boundingRect = cv::Rect(point1-cv::Point(5,5),point1+cv::Point(5,5));
targetImage = image(calibratedRect(boundingRect));
cv::imshow(targetName, targetImage);
}
targetSelected = true;
}
}
void drawQuadrants(cv::Point targetCoord) {
cv::line(image, cv::Point(0, centerPoint.y), cv::Point(frameWidth, centerPoint.y), blackColor);
cv::line(image, cv::Point(centerPoint.x, 0), cv::Point(centerPoint.x, frameHeight), blackColor);
if (targetCoord != cv::Point(999,999)) {
if (centerRectangle.contains(targetCoord)) {
targetCentered = true;
targetInQ1 = targetInQ2 = targetInQ3 = targetInQ4 = false;
highlightAllQuadrants();
}
else if (targetCoord.x >= centerPoint.x) {
if (targetCoord.y <= centerPoint.y) {
targetInQ1 = true;
targetInQ2 = targetInQ3 = targetInQ4 = targetCentered = false;
highlightQuadrant(1);
}
else if (targetCoord.y > centerPoint.y) {
targetInQ4 = true;
targetInQ1 = targetInQ2 = targetInQ3 = targetCentered = false;
highlightQuadrant(4);
}
}
else if (targetCoord.x < centerPoint.x) {
if (targetCoord.y <= centerPoint.y) {
targetInQ2 = true;
targetInQ1 = targetInQ3 = targetInQ4 = targetCentered = false;
highlightQuadrant(2);
}
else if (targetCoord.y > centerPoint.y) {
targetInQ3 = true;
targetInQ1 = targetInQ2 = targetInQ4 = targetCentered = false;
highlightQuadrant(3);
}
}
}
}
bool Target::init(KVConfig *cfg, int id, const cv::Rect &roi, const cv::Mat &curr_gray,
double stamp, double min_dis_5frames, int min_pts, int max_feature_pts, double qualitylevel)
{
first_rc_ = roi;
outer_.x = 0, outer_.y = 0, outer_.width = curr_gray.cols, outer_.height = curr_gray.rows;
stamp_ = stamp;
cfg_ = cfg;
id_ = id;
min_dis_5frames_ = min_dis_5frames;
min_pts_ = min_pts;
stopped_dis_ = atof(cfg->get_value("pd_target_stopped_dis", "2.0"));
//int max_features_pts = atoi(cfg->get_value("pd_max_features_pts", "300"));
int max_features_pts = 200;
PTS pts;
//cv::goodFeaturesToTrack(curr_gray(roi), pts, max_feature_pts, qualitylevel, 1.5);
hi_goodFeaturesToTrack(curr_gray(roi), pts, 200, qualitylevel, 1.5);
if ((int)pts.size() < min_pts_) {
return false;
}
l2g(pts, roi.tl());
layers_.push_back(pts);
brc_ = roi;
last_rc_ = cv::boundingRect(pts);
return true;
}
void TrackFace::drawFace(cv::Mat & frame, cv::Rect & face_n, string box_text)
{
rectangle(frame, face_n, CV_RGB(0,255,0),1);
int pos_x=std::max(face_n.tl().x-10, 0);
int pos_y=std::max(face_n.tl().y-10, 0);
putText(frame, box_text, Point(pos_x, pos_y), FONT_HERSHEY_PLAIN, 1.0, CV_RGB(0,255,0),2.0);
}
vector<cv::Point2d> MapShape(cv::Rect original_face_rect,
const vector<cv::Point2d> original_landmarks, cv::Rect new_face_rect)
{
vector<cv::Point2d> result;
for (const cv::Point2d &landmark: original_landmarks)
{
result.push_back(landmark);
result.back() -= static_cast<cv::Point2d>(original_face_rect.tl());
result.back().x *=
static_cast<double>(new_face_rect.width) / original_face_rect.width;
result.back().y *=
static_cast<double>(new_face_rect.height) / original_face_rect.height;
result.back() += static_cast<cv::Point2d>(new_face_rect.tl());
}
return result;
}
void prepare(cv::Rect dst_roi)
{
using namespace cv;
dst_roi_final_ = dst_roi;
// Crop unnecessary bands
double max_len = static_cast<double>(max(dst_roi.width, dst_roi.height));
num_bands_ = min(actual_num_bands_, static_cast<int>(ceil(log(max_len) / log(2.0))));
// Add border to the final image, to ensure sizes are divided by (1 << num_bands_)
dst_roi.width += ((1 << num_bands_) - dst_roi.width % (1 << num_bands_)) % (1 << num_bands_);
dst_roi.height += ((1 << num_bands_) - dst_roi.height % (1 << num_bands_)) % (1 << num_bands_);
Blender::prepare(dst_roi);
dst_pyr_laplace_.resize(num_bands_ + 1);
dst_pyr_laplace_[0] = dst_;
dst_band_weights_.resize(num_bands_ + 1);
dst_band_weights_[0].create(dst_roi.size(), weight_type_);
dst_band_weights_[0].setTo(0);
for (int i = 1; i <= num_bands_; ++i)
{
dst_pyr_laplace_[i].create((dst_pyr_laplace_[i - 1].rows + 1) / 2,
(dst_pyr_laplace_[i - 1].cols + 1) / 2, CV_16SC3);
dst_band_weights_[i].create((dst_band_weights_[i - 1].rows + 1) / 2,
(dst_band_weights_[i - 1].cols + 1) / 2, weight_type_);
dst_pyr_laplace_[i].setTo(Scalar::all(0));
dst_band_weights_[i].setTo(0);
}
}
inline void CalcVarianceAndSD(cv::Rect &block, cv::Mat &sum, cv::Mat &sqsum, double &mean, double &stdvar)
{
double brs = sum.at<int>(block.y+block.height,block.x+block.width); // D
double bls = sum.at<int>(block.y+block.height,block.x); // C
double trs = sum.at<int>(block.y,block.x+block.width); // B
double tls = sum.at<int>(block.y,block.x); // A
double brsq = sqsum.at<double>(block.y+block.height,block.x+block.width); // D
double blsq = sqsum.at<double>(block.y+block.height,block.x); // C
double trsq = sqsum.at<double>(block.y,block.x+block.width); // B
double tlsq = sqsum.at<double>(block.y,block.x); // A
mean = (brs + tls-trs-bls)/((double)block.area() + 1); // D + A - B - C
double sqmean = (brsq+tlsq-trsq-blsq)/((double)block.area() + 1); // D + A - B - C
stdvar = sqrt(sqmean - mean * mean);
return;
}
//RETURNS THE TOP-LEFT CORNER OF THE REFLECTION OF sourceTemplate ON image
cv::Rect findBestMatchLocation( const cv::Mat& image, const cv::Rect& source_rect,
double* nsigma, const cv::Mat& mask )
{
cv::Mat image_gray;
cvtColor( image, image_gray, CV_RGB2GRAY, 1 );
cv::Mat image_copy = image_gray.clone();
// Create template.
cv::Mat image_template_copy = image_gray.clone();
cv::Mat sourceTemplate = image_template_copy( source_rect );
flip( sourceTemplate, sourceTemplate, 0 );
// Creates results matrix where the top left corner of the
// template is slid across each pixel of the source
int result_cols = image.cols-sourceTemplate.cols+1;
int result_rows = image.rows-sourceTemplate.rows+1;
cv::Mat result;
result.create( result_cols,result_rows, CV_32FC1 );
// Mask image to match only in selected ROI.
if( !mask.empty() )
{
cv::Mat tmp;
image_copy.copyTo( tmp, mask );
image_copy = tmp;
}
//0:CV_TM_SQDIFF
//1:CV_TM_SQDIFF_NORMED
//2:CV_TM_CORR
//3:CV_TM_CCOR_NORMED
//4:CV_TM_CCOEFF
//5:CV_TM_CCOEFF_NORMED <----Most succesful at finding reflections
int match_method = CV_TM_CCOEFF_NORMED; // 4 seemed good for stddev thresholding.
//matchTemplate( masked_scene, sourceTemplate, result, match_method );
matchTemplate( image_gray, sourceTemplate, result, match_method );
double minVal, maxVal;
cv::Point minLoc, maxLoc, matchLoc;
minMaxLoc( result, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat() );
if( match_method == CV_TM_SQDIFF || match_method == CV_TM_SQDIFF_NORMED )
{
matchLoc = minLoc;
}
else
{
matchLoc = maxLoc;
}
cv::Scalar mean, stddev;
meanStdDev( result, mean, stddev, cv::Mat() );
*nsigma = ( maxVal-mean[0] )/ stddev[0];
// matchLoc is the location of the top left corner of the reflection
// that matchTemplate found
return cv::Rect( matchLoc, source_rect.size() );
}
bool MotionDetector::isInMotion(cv::Rect boundingBox, float interSection)
{
if (cv::sum(m_motionMap(boundingBox))[0] > interSection * boundingBox.area())
return true;
else
return false;
}
bool
ARC_Pair::set_reflection ( cv::Mat img, cv::Rect r, cv::Size s )
{
roi.reflection = convert_to_point( r, img, s );
if( roi.reflection==cv::Point( -1, -1 ) )
roi.reflection=r.tl()-0.5*cv::Point(s);
return true;
} /* ----- end of method ARC_Pair::set_reflection ----- */
std::pair<double, cv::Point> DescribeMaximum(const cv::Mat &surface,
const cv::Rect &boundingBox) {
// assert surface double
cv::Point position = boundingBox.tl();
cv::Point end = boundingBox.br();
size_t x = position.x, y = position.y;
double value = surface.at<double>(position);
for (; x <= end.x; x++) {
for (; y <= end.y; y++) {
if (surface.at<double>(y, x) > value) {
value = surface.at<double>(y, x);
position = cv::Point(x, y);
}
}
}
return std::make_pair(value, position);
}
Face::Face(cv::Rect &r)
{
cv::Point tl = r.tl();
m_center = cv::Point(tl.x + r.width/2, tl.y + r.height/2);
m_width = r.width;
m_height = r.height;
m_weight = 1;
}
bool EndToEndTest::rectMatches(cv::Rect actualPlate, PlateRegion candidate)
{
// Determine if this region matches our plate in the image
// Do this simply by verifying that the center point of the plate is within the region
// And that the plate region is not x% larger or smaller
const float MAX_SIZE_PERCENT_LARGER = 0.65;
//int plateCenterX = actualPlate.x + (int) (((float) actualPlate.width) / 2.0);
//int plateCenterY = actualPlate.y + (int) (((float) actualPlate.height) / 2.0);
//Point centerPoint(plateCenterX, plateCenterY);
vector<Point> requiredPoints;
requiredPoints.push_back(Point( actualPlate.x + (int) (((float) actualPlate.width) * 0.2),
actualPlate.y + (int) (((float) actualPlate.height) * 0.15)
));
requiredPoints.push_back(Point( actualPlate.x + (int) (((float) actualPlate.width) * 0.8),
actualPlate.y + (int) (((float) actualPlate.height) * 0.15)
));
requiredPoints.push_back(Point( actualPlate.x + (int) (((float) actualPlate.width) * 0.2),
actualPlate.y + (int) (((float) actualPlate.height) * 0.85)
));
requiredPoints.push_back(Point( actualPlate.x + (int) (((float) actualPlate.width) * 0.8),
actualPlate.y + (int) (((float) actualPlate.height) * 0.85)
));
float sizeDiff = 1.0 - ((float) actualPlate.area()) / ((float) candidate.rect.area());
//cout << "Candidate: " << candidate.rect.x << "," << candidate.rect.y << " " << candidate.rect.width << "-" << candidate.rect.height << endl;
//cout << "Actual: " << actualPlate.x << "," << actualPlate.y << " " << actualPlate.width << "-" << actualPlate.height << endl;
//cout << "size diff: " << sizeDiff << endl;
bool hasAllPoints = true;
for (int z = 0; z < requiredPoints.size(); z++)
{
if (candidate.rect.contains(requiredPoints[z]) == false)
hasAllPoints = false;
break;
}
if ( hasAllPoints &&
(sizeDiff < MAX_SIZE_PERCENT_LARGER) )
{
return true;
}
else
{
for (int i = 0; i < candidate.children.size(); i++)
{
if (rectMatches(actualPlate, candidate.children[i]))
return true;
}
}
return false;
}
bool MotionDetector::containsBoundingBox(cv::Rect outer, cv::Rect inner)
{
float intersectionParam = 0.45;
cv::Rect intersect = outer & inner;
if (intersect .area() >= intersectionParam * inner.area())
return true;
else
return false;
}
// === FUNCTION ======================================================================
// Name: get_masked_frame
// Description: Masks the frame based on slope and roi. Mask returned by pointer.
// =====================================================================================
cv::Mat get_masked_frame ( cv::Rect roi, double slope, cv::Mat* frame, cv::Mat* mask )
{
cv::Point corners[1][4];
//Set the frame
*mask=cv::Mat::zeros( frame->size(), CV_8UC1 );
cv::Mat masked_frame;
if( slope==0 )
{
// TODO: Could use direction handling here.
corners[0][0] = roi.br();
corners[0][1] = cv::Point( frame->cols, roi.y+roi.height );
corners[0][2] = corners[0][1]-cv::Point( 0, roi.height );
corners[0][3] = corners[0][0]-cv::Point( 0, roi.height );
}
else if( isinf( slope ) )
{
{
corners[0][0] = cv::Point( roi.x, frame->rows );
corners[0][1] = cv::Point( roi.x, roi.y+roi.height);
}
{
corners[0][0] = roi.tl();
corners[0][1] = cv::Point( roi.x, 0 );
}
corners[0][2] = corners[0][1]+cv::Point( roi.width, 0);
corners[0][3] = corners[0][0]+cv::Point( roi.width, 0 );
}
else
{
corners[0][0].x = ( int ) ( (frame->rows + slope*roi.x-roi.y)/slope );
corners[0][0].y = frame->rows;
corners[0][1] = cv::Point( ( int )( (-roi.y + slope * roi.x ) / slope ), 0 );
corners[0][2] = corners[0][1] + cv::Point(roi.width, 0);
corners[0][3] = corners[0][0] + cv::Point(roi.width, 0);
}
// This is weird, but follows OpenCV docs.
const cv::Point* ppt[1] = { corners[0] };
const int npt[] = { 4 };
fillPoly( *mask, ppt, npt, 1, 255 );
frame->copyTo(masked_frame, *mask);
return masked_frame;
} // ----- end of function get_masked_frame -----
/** determine if a rectangle contains "blank" pixels **/
bool Cropper::rectHasBlankPixels(const cv::Rect &roi) {
Point2i tr(roi.x + roi.width - 1, roi.y);
Point2i bl(roi.x, roi.y + roi.height - 1);
Point2i br(roi.x + roi.width - 1, roi.y + roi.height - 1);
if(lineHasBlankPixels(roi.tl(), tr))
return true;
if(lineHasBlankPixels(tr, br))
return true;
if(lineHasBlankPixels(bl, br))
return true;
if(lineHasBlankPixels(roi.tl(), bl))
return true;
return false;
}
bool fusionRects(cv::Rect prevRectK, cv::Rect rectK)
{
if(prevRectK.area() == 0)
return false;
if(rectK.width > 1.8*prevRectK.width)
return true;
else
return false;
}
Point computeIntersect(cv::Vec4i a, cv::Vec4i b, cv::Rect ROI)
{
int x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3];
int x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3];
Point p1 = Point(x1,y1);
Point p2 = Point(x2,y2);
Point p3 = Point(x3,y3);
Point p4 = Point(x4,y4);
if( !ROI.contains(p1) || !ROI.contains(p2)
|| !ROI.contains(p3) || !ROI.contains(p4) )
return Point(-1,-1);
Point vec1 = p1-p2;
Point vec2 = p3-p4;
float vec1_norm2 = vec1.x*vec1.x + vec1.y*vec1.y;
float vec2_norm2 = vec2.x*vec2.x + vec2.y*vec2.y;
float cosTheta = (vec1.dot(vec2))/sqrt(vec1_norm2*vec2_norm2);
float den = ((float)(x1-x2) * (y3-y4)) - ((y1-y2) * (x3-x4));
if(den != 0)
{
cv::Point2f pt;
pt.x = ((x1*y2 - y1*x2) * (x3-x4) - (x1-x2) * (x3*y4 - y3*x4)) / den;
pt.y = ((x1*y2 - y1*x2) * (y3-y4) - (y1-y2) * (x3*y4 - y3*x4)) / den;
if( !ROI.contains(pt) )
return Point(-1,-1);
// no-confidence metric
float d1 = MIN( dist2(p1,pt), dist2(p2,pt) )/vec1_norm2;
float d2 = MIN( dist2(p3,pt), dist2(p4,pt) )/vec2_norm2;
float no_confidence_metric = MAX(sqrt(d1),sqrt(d2));
if( no_confidence_metric < 0.5 && cosTheta < 0.707 )
return Point(int(pt.x+0.5), int(pt.y+0.5));
}
return cv::Point(-1, -1);
}
