static Shape AlignMeanShapeToFaceDetRect(
const DetPar& detpar, // in
const Shape& meanshape, // in
double scale, // in: scale the face rectangle
const Image& img) // io: the image (grayscale)
{
if (trace_g)
lprintf("AlignToFaceDetBox ");
DetPar detpar1(detpar);
if (IsLeftFacing(detpar.eyaw))
detpar1 = FlipDetPar(detpar, img.cols);
CV_Assert(meanshape.rows > 0 && meanshape.cols == 2);
const double xscale = detpar1.width * scale / DET_FACE_WIDTH;
const double yscale = detpar1.height * scale / DET_FACE_WIDTH;
Shape startshape = AlignShape(meanshape,
xscale, 0, detpar1.x,
0, yscale, detpar1.y);
return startshape;
}
static void FlipIfLeftFacing(
Shape& shape, // io
EYAW eyaw, // in
int ncols) // in
{
if (IsLeftFacing(eyaw))
shape = FlipShape(shape, ncols);
}
void PinnedStartShapeAndRoi( // use the pinned landmarks to init the start shape
Shape& startshape, // out: the start shape (in ROI frame)
Image& face_roi, // out: ROI around face, possibly rotated upright
DetPar& detpar_roi, // out: detpar wrt to face_roi
DetPar& detpar, // out: detpar wrt to img
Shape& pinned_roi, // out: pinned arg translated to ROI frame
const Image& img, // in: the image (grayscale)
const vec_Mod& mods, // in: a vector of models, one for each yaw range
const Shape& pinned) // in: manually pinned landmarks
{
double rot, yaw;
EstRotAndYawFrom5PointShape(rot, yaw, As5PointShape(pinned, mods[0]->MeanShape_()));
const EYAW eyaw = DegreesAsEyaw(yaw, NSIZE(mods));
const int imod = EyawAsModIndex(eyaw, mods); // select ASM model based on yaw
if (trace_g)
lprintf("%-6.6s yaw %3.0f rot %3.0f ", EyawAsString(eyaw), yaw, rot);
pinned_roi = pinned; // use pinned_roi as a temp shape we can change
Image workimg(img); // possibly flipped image
if (IsLeftFacing(eyaw)) // left facing? (our models are for right facing faces)
{
pinned_roi = FlipShape(pinned_roi, workimg.cols);
FlipImgInPlace(workimg);
}
const Mod* mod = mods[ABS(imod)];
startshape = PinMeanShape(pinned_roi, mod->MeanShape_());
startshape = mod->ConformShapeToMod_Pinned_(startshape, pinned_roi);
detpar = PseudoDetParFromStartShape(startshape, rot, yaw, NSIZE(mods));
if (IsLeftFacing(eyaw))
detpar.rot *= -1;
FaceRoiAndDetPar(face_roi, detpar_roi, workimg, detpar, false);
startshape = ImgShapeToRoiFrame(startshape, detpar_roi, detpar);
pinned_roi = ImgShapeToRoiFrame(pinned_roi, detpar_roi, detpar);
// following line not strictly necessary because don't actually need eyes/mouth
InitDetParEyeMouthFromShape(detpar_roi, startshape);
if (IsLeftFacing(eyaw))
{
detpar = FlipDetPar(detpar, img.cols);
detpar.rot = -detpar.rot;
detpar_roi.x += 2. * (face_roi.cols/2. - detpar_roi.x);
}
}
Shape RoiShapeToImgFrame( // return shape in image frame
const Shape& shape, // in: shape in roi frame
const Image& face_roi, // in
const DetPar& detpar_roi, // in: detpar wrt the ROI
const DetPar& detpar) // in: detpar wrt the image
{
Shape outshape(shape.clone());
if (IsLeftFacing(detpar.eyaw))
outshape = FlipShape(outshape, face_roi.cols);
if (Valid(detpar.rot) && detpar.rot)
{
const MAT rotmat =
getRotationMatrix2D(cv::Point2f(float(detpar_roi.x),
float(detpar_roi.y)),
detpar.rot, 1.);
TransformShapeInPlace(outshape, rotmat);
}
return ShiftShape(outshape, detpar.x - detpar_roi.x,
detpar.y - detpar_roi.y);
}
static void StartShapeAndRoi( // we have the facerect, now get the rest
Shape& startshape, // out: the start shape we are looking for
Image& face_roi, // out: ROI around face, possibly rotated upright
DetPar& detpar_roi, // out: detpar wrt to face_roi
DetPar& detpar, // io: detpar wrt to img (has face rect on entry)
const Image& img, // in: the image (grayscale)
const vec_Mod& mods, // in: a vector of models, one for each yaw range
// (use only estart, and meanshape)
StasmCascadeClassifier cascade)
{
PossiblySetRotToZero(detpar.rot); // treat small rots as zero rots
FaceRoiAndDetPar(face_roi, detpar_roi, // get ROI around face
img, detpar, false);
DetectEyesAndMouth(detpar_roi, // use OpenCV eye and mouth detectors
face_roi, cascade);
// Some face detectors return the face rotation, some don't (in
// the call to NextFace_ just made via NextStartShapeAndRoi).
// If we don't have the rotation, then estimate it from the eye
// angle, if the eyes are available.
if (!Valid(detpar.rot)) // don't have the face rotation?
{
detpar_roi.rot = EstRotFromEyeAngle(detpar_roi);
PossiblySetRotToZero(detpar_roi.rot);
detpar.rot = detpar_roi.rot;
if (detpar.rot != 0)
{
// face is rotated: rotate ROI and re-get the eyes and mouth
// TODO: Prevent bogus OpenCV assert fail face_roi.data == img.data.
face_roi = Image(0,0);
FaceRoiAndDetPar(face_roi, detpar_roi,
img, detpar, false);
DetectEyesAndMouth(detpar_roi, // use OpenCV eye and mouth detectors
face_roi, cascade);
}
}
if (trace_g)
lprintf("%-6.6s yaw %3.0f rot %3.0f ",
EyawAsString(detpar_roi.eyaw), detpar_roi.yaw, detpar_roi.rot);
else
logprintf("%-6.6s yaw %3.0f rot %3.0f ",
EyawAsString(detpar_roi.eyaw), detpar_roi.yaw, detpar_roi.rot);
// select an ASM model based on the face's yaw
const Mod* mod = mods[ABS(EyawAsModIndex(detpar_roi.eyaw, mods))];
const ESTART estart = mod->Estart_();
CV_Assert(estart == ESTART_EYES || estart == ESTART_EYE_AND_MOUTH);
startshape = StartShapeFromDetPar(detpar_roi,
face_roi, mod->MeanShape_(), estart);
if (IsLeftFacing(detpar_roi.eyaw))
FlipImgInPlace(face_roi);
JitterPointsAt00(startshape);
}
