for( iter = 0; iter < niters; iter++ )
{
- int i, goodCount, nmodels;
+ int i, nmodels;
if( count > modelPoints )
{
bool found = getSubset( m1, m2, ms1, ms2, rng, 10000 );
for( i = 0; i < nmodels; i++ )
{
Mat model_i = model.rowRange( i*modelSize.height, (i+1)*modelSize.height );
- goodCount = findInliers( m1, m2, model_i, err, mask, threshold );
+ int goodCount = findInliers( m1, m2, model_i, err, mask, threshold );
if( goodCount > MAX(maxGoodCount, modelPoints-1) )
{
int d1 = m1.channels() > 1 ? m1.channels() : m1.cols;
int d2 = m2.channels() > 1 ? m2.channels() : m2.cols;
int count = m1.checkVector(d1), count2 = m2.checkVector(d2);
- double minMedian = DBL_MAX, sigma;
+ double minMedian = DBL_MAX;
RNG rng((uint64)-1);
if( minMedian < DBL_MAX )
{
- sigma = 2.5*1.4826*(1 + 5./(count - modelPoints))*std::sqrt(minMedian);
+ double sigma = 2.5*1.4826*(1 + 5./(count - modelPoints))*std::sqrt(minMedian);
sigma = MAX( sigma, 0.001 );
count = findInliers( m1, m2, bestModel, err, mask, sigma );
{
Point2f pt[4] = {Point2f(0,0), Point2f(w,0), Point2f(w,h), Point2f(0,h)};
Point2f Mpt[4];
- float z;
for (int i = 0; i < 4; ++i)
{
Mpt[i].x = M[0]*pt[i].x + M[1]*pt[i].y + M[2];
Mpt[i].y = M[3]*pt[i].x + M[4]*pt[i].y + M[5];
- z = M[6]*pt[i].x + M[7]*pt[i].y + M[8];
+ float z = M[6]*pt[i].x + M[7]*pt[i].y + M[8];
Mpt[i].x /= z;
Mpt[i].y /= z;
}
Size ncells((frameSize.width + cellSize_.width - 1) / cellSize_.width,
(frameSize.height + cellSize_.height - 1) / cellSize_.height);
- int cx, cy;
-
// fill grid cells
grid_.assign(ncells.area(), Cell());
for (int i = 0; i < npoints; ++i)
{
- cx = std::min(cvRound(points0_[i].x / cellSize_.width), ncells.width - 1);
- cy = std::min(cvRound(points0_[i].y / cellSize_.height), ncells.height - 1);
+ int cx = std::min(cvRound(points0_[i].x / cellSize_.width), ncells.width - 1);
+ int cy = std::min(cvRound(points0_[i].y / cellSize_.height), ncells.height - 1);
grid_[cy * ncells.width + cx].push_back(i);
}
RNG rng(0);
int niters = ransacParams_.niters();
- int ninliers, ninliersMax;
std::vector<int> inliers;
- float dx, dy, dxBest, dyBest;
- float x1, y1;
- int idx;
for (size_t ci = 0; ci < grid_.size(); ++ci)
{
// estimate translation model at the current cell using RANSAC
+ float x1, y1;
const Cell &cell = grid_[ci];
- ninliersMax = 0;
- dxBest = dyBest = 0.f;
+ int ninliers, ninliersMax = 0;
+ float dxBest = 0.f, dyBest = 0.f;
// find the best hypothesis
{
for (int iter = 0; iter < niters; ++iter)
{
- idx = cell[static_cast<unsigned>(rng) % cell.size()];
- dx = points1_[idx].x - points0_[idx].x;
- dy = points1_[idx].y - points0_[idx].y;
+ int idx = cell[static_cast<unsigned>(rng) % cell.size()];
+ float dx = points1_[idx].x - points0_[idx].x;
+ float dy = points1_[idx].y - points0_[idx].y;
ninliers = 0;
for (size_t i = 0; i < cell.size(); ++i)