void Mod::LevSearch_( // do an ASM search at one level in the image pyr
Shape& shape, // io: the face shape for this pyramid level
int ilev, // in: pyramid level (0 is full size)
const Image& img, // in: image scaled to this pyramid level
const Shape& pinnedshape) // in: if no rows then no pinned landmarks, else
// points except those equal to 0,0 are pinned
const
{
TraceShape(shape, img, ilev, 0, "enterlevsearch");
InitHatLevData(img, ilev); // init internal HAT mats for this lev
VEC b(NSIZE(shapemod_.eigvals_), 1, 0.); // eigvec weights, init to 0
for (int iter = 0; iter < SHAPEMODEL_ITERS; iter++)
{
// suggest shape by descriptor matching at each landmark
SuggestShape_(shape,
ilev, img, pinnedshape);
TraceShape(shape, img, ilev, iter, "suggested");
// adjust suggested shape to conform to the shape model
if (pinnedshape.rows)
shape = shapemod_.ConformShapeToMod_Pinned_(b,
shape, ilev, pinnedshape);
else
shape = shapemod_.ConformShapeToMod_(b,
shape, ilev);
TraceShape(shape, img, ilev, iter, "conformed");
}
}
static void GenTrainingDescsForOneImg(
TRAIN_DISTS& train_dists, // io: [ipoint] [idesc] new distances will be added
TRAIN_DESCS& train_descs, // io: [ipoint] [idesc] new descriptors will be added
int ilev, // in: pyramid level (0 is full scale)
const ShapeFile& sh, // in
int ishape) // in: shape index in the shapefile
{
Image img; // image scaled to EYEMOUTH_DIST and ilev
Shape shape; // shape scaled ditto
GetTrainImg(img, shape, ilev, sh, ishape);
// init internal HAT mats for this lev so can call HatDesc later
InitHatLevData(img, ilev);
for (int ipoint = 0; ipoint < shape.rows; ipoint++)
{
if (PointUsableForTraining(shape, ipoint,
sh.bits_[ishape], sh.bases_[ishape].c_str()))
{
const bool is_hat = IsTasmHatDesc(ilev, ipoint);
const VEC desc(
is_hat? HatDesc(shape(ipoint, IX), shape(ipoint, IY)):
ClassicProf(img, shape, ipoint, TASM_1D_PROFLEN));
train_dists[ipoint].push_back(0); // positive case so distance is zero
train_descs[ipoint].push_back(desc);
if (is_hat) // get the negative descriptors too?
for (int ineg = 0; ineg < TASM_NNEG_TRAIN_DESCS; ineg++)
{
// get descriptor at at a random xy offset from the true position
int xneg, yneg; NegOffsets(xneg, yneg);
const VEC neg_desc(HatDesc(shape(ipoint, IX) + xneg,
shape(ipoint, IY) + yneg));
train_dists[ipoint].push_back(sqrt(double(SQ(xneg)+SQ(yneg))));
train_descs[ipoint].push_back(neg_desc);
}
}
}
}
