def _predict_neighbours(self, a, b, new_corners):
if a == b + 1 or (b == 3 and a == 0):
a, b = b, a
na = (a + 3) % 4
v1 = new_corners[na].get_prediction_vector(False, self.corners[na])
nb = (b + 1) % 4
v2 = new_corners[nb].get_prediction_vector(True, self.corners[nb])
ap = add(new_corners[na].p, v1)
bp = add(new_corners[nb].p, v2)
cor_a = Corner([new_corners[na].p, ap, bp], 1,
imgtime=new_corners[na].time)
cor_b = Corner([ap, bp, new_corners[nb].p], 1,
imgtime=new_corners[na].time)
cor_b.is_predicted = cor_a.is_predicted = True
cor_a.compute_change(self.corners[a], self.image)
cor_b.compute_change(self.corners[b], self.image)
if cor_a.different:
if cor_b.different: return
else:
new_corners[b] = cor_b
self._predict_one(a, new_corners)
else:
new_corners[a] = cor_a
if cor_b.different:
self._predict_one(b, new_corners)
else:
new_corners[b] = cor_b
def _predict_from_one(self, a, new_corners):
vec = new_corners[a].get_prediction_vector(True, self.corners[a])
pa = (a + 3) % 4
p1 = add(new_corners[a].p, vec)
vec = (-vec[0],-vec[1])
vec=rotateVec(vec, self.corners[pa].angle)
pp1= add(p1,vec)
cor_p = Corner([pp1, p1, new_corners[a].p], 1,
imgtime=new_corners[a].time)
vec = new_corners[a].get_prediction_vector(False, self.corners[a])
na = (a + 1) % 4
p2 = add(new_corners[a].p, vec)
vec = (-vec[0],-vec[1])
vec=rotateVec(vec, self.corners[na].angle)
np2= add(p1,vec)
cor_n = Corner([new_corners[a].p, p2, np2], 1,
imgtime=new_corners[a].time)
cor_p.is_predicted = cor_n.is_predicted = True
cor_p.compute_change(self.corners[pa], self.image)
cor_n.compute_change(self.corners[na], self.image)
da= (a + 2) % 4
if cor_p.different:
if cor_n.different: return
else:
new_corners[na] = cor_n
self._predict_neighbours(pa, da, new_corners)
else:
new_corners[pa] = cor_p
if cor_n.different:
self._predict_neighbours(na, da, new_corners)
else:
new_corners[na] = cor_n
self._predict_one(da, new_corners)
def _predict_one(self, index, new_corners):
'''
predict position of corner index
@param index:
@param new_corners:
'''
# predicting by taking vectors form near corners along the sides
# and solving linear equation for intersection
L = len(new_corners)
nb = (index + 1) % L
b = new_corners[nb]
nd = (index - 1 + L) % L
d = new_corners[nd]
assert isinstance(b, Corner)
v1 = b.get_prediction_vector(True, self.corners[nb])
v2 = d.get_prediction_vector(False, self.corners[nd])
p1 = b.p
p2 = d.p
(p, _) = solve_linear(v1, v2, p1, p2)
point = add(b.p, v1, p)
cor = Corner([d.p, point, b.p], imgtime=b.time)
cor.compute_change(self.corners[index])
cor.is_predicted = True
if cor.similarity < self.avg_sim * 2:
new_corners[index] = cor
