landmarks.cpp
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#include <opencv2/opencv.hpp>
#include "openbr_internal.h"
#include "openbr/core/qtutils.h"
#include "openbr/core/opencvutils.h"
#include "openbr/core/eigenutils.h"
#include <QString>
#include <Eigen/SVD>
using namespace std;
using namespace cv;
namespace br
{
/*!
* \ingroup transforms
* \brief Procrustes alignment of points
* \author Scott Klum \cite sklum
*/
class ProcrustesTransform : public Transform
{
Q_OBJECT
Q_PROPERTY(bool warp READ get_warp WRITE set_warp RESET reset_warp STORED false)
BR_PROPERTY(bool, warp, true)
Eigen::MatrixXf meanShape;
void train(const TemplateList &data)
{
QList< QList<QPointF> > normalizedPoints;
// Normalize all sets of points
foreach (br::Template datum, data) {
QList<QPointF> points = datum.file.points();
QList<QRectF> rects = datum.file.rects();
if (points.empty() || rects.empty()) continue;
// Assume rect appended last was bounding box
points.append(rects.last().topLeft());
points.append(rects.last().topRight());
points.append(rects.last().bottomLeft());
points.append(rects.last().bottomRight());
// Center shape at origin
Scalar mean = cv::mean(OpenCVUtils::toPoints(points).toVector().toStdVector());
for (int i = 0; i < points.size(); i++) points[i] -= QPointF(mean[0],mean[1]);
// Remove scale component
float norm = cv::norm(OpenCVUtils::toPoints(points).toVector().toStdVector());
for (int i = 0; i < points.size(); i++) points[i] /= norm;
normalizedPoints.append(points);
}
if (normalizedPoints.empty()) qFatal("Unable to calculate normalized points");
// Determine mean shape, assuming all shapes contain the same number of points
meanShape = Eigen::MatrixXf(normalizedPoints[0].size(), 2);
for (int i = 0; i < normalizedPoints[0].size(); i++) {
double x = 0;
double y = 0;
for (int j = 0; j < normalizedPoints.size(); j++) {
x += normalizedPoints[j][i].x();
y += normalizedPoints[j][i].y();
}
x /= (double)normalizedPoints.size();
y /= (double)normalizedPoints.size();
meanShape(i,0) = x;
meanShape(i,1) = y;
}
}
void project(const Template &src, Template &dst) const
{
QList<QPointF> points = src.file.points();
QList<QRectF> rects = src.file.rects();
if (points.empty() || rects.empty()) {
dst = src;
qWarning("Procrustes alignment failed because points or rects are empty.");
return;
}
// Assume rect appended last was bounding box
points.append(rects.last().topLeft());
points.append(rects.last().topRight());
points.append(rects.last().bottomLeft());
points.append(rects.last().bottomRight());
Scalar mean = cv::mean(OpenCVUtils::toPoints(points).toVector().toStdVector());
for (int i = 0; i < points.size(); i++) points[i] -= QPointF(mean[0],mean[1]);
Eigen::MatrixXf srcMat(points.size(), 2);
float norm = cv::norm(OpenCVUtils::toPoints(points).toVector().toStdVector());
for (int i = 0; i < points.size(); i++) {
points[i] /= norm;
srcMat(i,0) = points[i].x();
srcMat(i,1) = points[i].y();
}
Eigen::JacobiSVD<Eigen::MatrixXf> svd(srcMat.transpose()*meanShape, Eigen::ComputeThinU | Eigen::ComputeThinV);
Eigen::MatrixXf R = svd.matrixU()*svd.matrixV().transpose();
dst = src;
if (warp) {
Eigen::MatrixXf dstMat = srcMat*R;
for (int i = 0; i < dstMat.rows(); i++) {
dst.file.appendPoint(QPointF(dstMat(i,0),dstMat(i,1)));
}
}
dst.file.set("Procrustes_0_0", R(0,0));
dst.file.set("Procrustes_1_0", R(1,0));
dst.file.set("Procrustes_1_1", R(1,1));
dst.file.set("Procrustes_0_1", R(0,1));
dst.file.set("Procrustes_mean_0", mean[0]);
dst.file.set("Procrustes_mean_1", mean[1]);
dst.file.set("Procrustes_norm", norm);
}
void store(QDataStream &stream) const
{
stream << meanShape;
}
void load(QDataStream &stream)
{
stream >> meanShape;
}
};
BR_REGISTER(Transform, ProcrustesTransform)
/*!
* \ingroup transforms
* \brief Creates a Delaunay triangulation based on a set of points
* \author Scott Klum \cite sklum
*/
class DelaunayTransform : public UntrainableTransform
{
Q_OBJECT
Q_PROPERTY(float scaleFactor READ get_scaleFactor WRITE set_scaleFactor RESET reset_scaleFactor STORED false)
Q_PROPERTY(bool warp READ get_warp WRITE set_warp RESET reset_warp STORED false)
Q_PROPERTY(bool draw READ get_draw WRITE set_draw RESET reset_draw STORED false)
BR_PROPERTY(float, scaleFactor, 1)
BR_PROPERTY(bool, warp, true)
BR_PROPERTY(bool, draw, false)
void project(const Template &src, Template &dst) const
{
Subdiv2D subdiv(Rect(0,0,src.m().cols,src.m().rows));
QList<QPointF> points = src.file.points();
QList<QRectF> rects = src.file.rects();
if (points.empty() || rects.empty()) {
dst = src;
qWarning("Delauney triangulation failed because points or rects are empty.");
return;
}
// Assume rect appended last was bounding box
points.append(rects.last().topLeft());
points.append(rects.last().topRight());
points.append(rects.last().bottomLeft());
points.append(rects.last().bottomRight());
for (int i = 0; i < points.size(); i++) {
if (points[i].x() < 0 || points[i].y() < 0 || points[i].y() >= src.m().rows || points[i].x() >= src.m().cols) {
dst = src;
qWarning("Delauney triangulation failed because points lie on boundary.");
return;
}
subdiv.insert(OpenCVUtils::toPoint(points[i]));
}
vector<Vec6f> triangleList;
subdiv.getTriangleList(triangleList);
QList< QList<Point> > validTriangles;
for (size_t i = 0; i < triangleList.size(); ++i) {
vector<Point> pt(3);
pt[0] = Point(cvRound(triangleList[i][0]), cvRound(triangleList[i][1]));
pt[1] = Point(cvRound(triangleList[i][2]), cvRound(triangleList[i][3]));
pt[2] = Point(cvRound(triangleList[i][4]), cvRound(triangleList[i][5]));
bool inside = true;
for (int j = 0; j < 3; j++) {
if (pt[j].x > src.m().cols || pt[j].y > src.m().rows || pt[j].x < 0 || pt[j].y < 0) inside = false;
}
if (inside) validTriangles.append(QList<Point>()<< pt[0] << pt[1] << pt[2]);
}
dst.m() = src.m().clone();
if (draw) {
foreach(const QList<Point>& triangle, validTriangles) {
line(dst.m(), triangle[0], triangle[1], Scalar(0,0,0), 1);
line(dst.m(), triangle[1], triangle[2], Scalar(0,0,0), 1);
line(dst.m(), triangle[2], triangle[0], Scalar(0,0,0), 1);
}
}
if (warp) {
Eigen::MatrixXf R(2,2);
R(0,0) = src.file.get<float>("Procrustes_0_0");
R(1,0) = src.file.get<float>("Procrustes_1_0");
R(1,1) = src.file.get<float>("Procrustes_1_1");
R(0,1) = src.file.get<float>("Procrustes_0_1");
cv::Scalar mean(2);
mean[0] = src.file.get<float>("Procrustes_mean_0");
mean[1] = src.file.get<float>("Procrustes_mean_1");
float norm = src.file.get<float>("Procrustes_norm");
dst.m() = Mat::zeros(src.m().rows,src.m().cols,src.m().type());
QList<Point2f> mappedPoints;
dst.file = src.file;
for (int i = 0; i < validTriangles.size(); i++) {
Eigen::MatrixXf srcMat(validTriangles[i].size(), 2);
for (int j = 0; j < 3; j++) {
srcMat(j,0) = (validTriangles[i][j].x-mean[0])/norm;
srcMat(j,1) = (validTriangles[i][j].y-mean[1])/norm;
}
Eigen::MatrixXf dstMat = srcMat*R;
Point2f srcPoints[3];
for (int j = 0; j < 3; j++) srcPoints[j] = validTriangles[i][j];
Point2f dstPoints[3];
for (int j = 0; j < 3; j++) {
// Scale and shift destination points
Point2f warpedPoint = Point2f(dstMat(j,0)*scaleFactor+src.m().cols/2,dstMat(j,1)*scaleFactor+src.m().rows/2);
dstPoints[j] = warpedPoint;
mappedPoints.append(warpedPoint);
}
Mat buffer(src.m().rows,src.m().cols,src.m().type());
warpAffine(src.m(), buffer, getAffineTransform(srcPoints, dstPoints), Size(src.m().cols,src.m().rows));
Mat mask = Mat::zeros(src.m().rows, src.m().cols, CV_8UC1);
Point maskPoints[1][3];
maskPoints[0][0] = dstPoints[0];
maskPoints[0][1] = dstPoints[1];
maskPoints[0][2] = dstPoints[2];
const Point* ppt = { maskPoints[0] };
fillConvexPoly(mask, ppt, 3, Scalar(255,255,255), 8);
Mat output(src.m().rows,src.m().cols,src.m().type());
// Optimization needed
if (i > 0) {
Mat overlap;
bitwise_and(dst.m(),mask,overlap);
for (int j = 0; j < overlap.rows; j++) {
for (int k = 0; k < overlap.cols; k++) {
if (overlap.at<uchar>(j,k) != 0) {
mask.at<uchar>(j,k) = 0;
}
}
}
}
bitwise_and(buffer,mask,output);
dst.m() += output;
}
// Overwrite any rects
Rect boundingBox = boundingRect(mappedPoints.toVector().toStdVector());
dst.file.setRects(QList<QRectF>() << OpenCVUtils::fromRect(boundingBox));
}
}
};
BR_REGISTER(Transform, DelaunayTransform)
} // namespace br
#include "landmarks.moc"