int main()
{
std::vector<Segment> input;
// Prepare point generator for the horizontal segment, length 200.
P1 p1( Point(-100,0), Point(100,0));
// Prepare point generator for random points on circle, radius 250.
P2 p2( 250);
// Create segments.
Seg_iterator g( p1, p2);
CGAL::cpp11::copy_n( g, 200, std::back_inserter(input));
// splitting results with Dispatch_output_iterator
std::vector<Point> points;
std::vector<Segment> segments;
typedef CGAL::Dispatch_output_iterator<
CGAL::cpp11::tuple<Point,Segment>, CGAL::cpp11::tuple< std::back_insert_iterator<std::vector<Point> >,
std::back_insert_iterator<std::vector<Segment> > > >
Dispatcher;
Dispatcher disp = CGAL::dispatch_output<Point,Segment>( std::back_inserter(points),
std::back_inserter(segments) );
// intersects the first segment of input with all other segments
// The resulting points or segments are written in the vectors with the same names
std::transform( input.begin(), input.end(), disp,
Intersector(input.front()) );
std::cout << "Point intersections: " << points.size() << std::endl;
std::cout << "Segment intersections: " << segments.size() << std::endl;
return 0;
}
void CFFLD::detect(const Mixture & mixture, int width, int height, const HOGPyramid & pyramid, double threshold, double overlap, const string image, ostream & out, const string & images, vector<Detection> & detections, vector<DetectionResult> & vResult )
{
// Compute the scores
vector<HOGPyramid::Matrix> scores;
vector<Mixture::Indices> argmaxes;
vector<vector<vector<Model::Positions> > > positions;
if (!images.empty())
{
mixture.convolve(pyramid, scores, argmaxes, &positions);
}
else
{
mixture.convolve(pyramid, scores, argmaxes);
}
//cout<<"conv"<<endl;
// Cache the size of the models
vector<pair<int, int> > sizes(mixture.models().size());
for (int i = 0; i < sizes.size(); ++i)
{
sizes[i] = mixture.models()[i].rootSize();
}
// For each scale
for (int i = pyramid.interval(); i < scores.size(); ++i)
{
// Scale = 8 / 2^(1 - i / interval)
const double scale = pow(2.0, static_cast<double>(i) / pyramid.interval() + 2.0);
const int rows = scores[i].rows();
const int cols = scores[i].cols();
for (int y = 0; y < rows; ++y)
{
for (int x = 0; x < cols; ++x)
{
const float score = scores[i](y, x);
if (score > threshold)
{
if (((y == 0) || (x == 0) || (score > scores[i](y - 1, x - 1))) &&
((y == 0) || (score > scores[i](y - 1, x))) &&
((y == 0) || (x == cols - 1) || (score > scores[i](y - 1, x + 1))) &&
((x == 0) || (score > scores[i](y, x - 1))) &&
((x == cols - 1) || (score > scores[i](y, x + 1))) &&
((y == rows - 1) || (x == 0) || (score > scores[i](y + 1, x - 1))) &&
((y == rows - 1) || (score > scores[i](y + 1, x))) &&
((y == rows - 1) || (x == cols - 1) || (score > scores[i](y + 1, x + 1))))
{
FFLD::Rectangle bndbox((x - pyramid.padx()) * scale + 0.5,
(y - pyramid.pady()) * scale + 0.5,
sizes[argmaxes[i](y, x)].second * scale + 0.5,
sizes[argmaxes[i](y, x)].first * scale + 0.5);
// Truncate the object
bndbox.setX(max(bndbox.x(), 0));
bndbox.setY(max(bndbox.y(), 0));
bndbox.setWidth(min(bndbox.width(), width - bndbox.x()));
bndbox.setHeight(min(bndbox.height(), height - bndbox.y()));
if (!bndbox.empty())
{
detections.push_back(Detection(score, i, x, y, bndbox));
}
}
}
}
}
}
// Non maxima suppression
sort(detections.begin(), detections.end());
for (int i = 1; i < detections.size(); ++i)
detections.resize(remove_if(detections.begin() + i, detections.end(),
Intersector(detections[i - 1], overlap, true)) -
detections.begin());
// Print the detection
const size_t lastDot = image.find_last_of('.');
string id = image.substr(0, lastDot);
const size_t lastSlash = id.find_last_of("/\\");
if (lastSlash != string::npos)
id = id.substr(lastSlash + 1);
if (out)
{
#pragma omp critical
for (int i = 0; i < detections.size(); ++i)
{
out << id << ' ' << detections[i].score << ' ' << (detections[i].left() + 1) << ' '
<< (detections[i].top() + 1) << ' ' << (detections[i].right() + 1) << ' '
<< (detections[i].bottom() + 1) << endl;
}
}
// Output the result to OpenCV Rect
for( int j = 0; j < detections.size(); j ++ )
{
DetectionResult result;
// The position of the root one octave below
const int argmax = argmaxes[detections[j].l](detections[j].y, detections[j].x);
const int x2 = detections[j].x * 2 - pyramid.padx();
const int y2 = detections[j].y * 2 - pyramid.pady();
const int l = detections[j].l - pyramid.interval();
const double scale = pow(2.0, static_cast<double>(l) / pyramid.interval() + 2.0);
//cout<<positions[argmax].size()<<endl;
for (int k = 0; k < positions[argmax].size(); ++k)
{
const FFLD::Rectangle bndbox((positions[argmax][k][l](y2, x2)(0) -
pyramid.padx()) * scale + 0.5,
(positions[argmax][k][l](y2, x2)(1) - pyramid.pady()) * scale + 0.5,
mixture.models()[argmax].partSize().second * scale + 0.5,
mixture.models()[argmax].partSize().second * scale + 0.5 );
Rect rtPart( bndbox.x_, bndbox.y_, bndbox.width_, bndbox.height_ );
//cout<<rtPart<<endl;
result.vParts.push_back( rtPart );
}
Rect rtRoot( detections[j].x_, detections[j].y_, detections[j].width_, detections[j].height_ );
result.rtRoot = rtRoot;
vResult. push_back(result);
}
}
