def stats(points):
global prop_max, prop_min, angle_max, angle_min, rot_max, angle_diff_max, angle_diff_min
a = length(vector(points[0], points[1]))
b = length(vector(points[1], points[2]))
c = length(vector(points[2], points[3]))
d = length(vector(points[3], points[0]))
if a > c:
a, c = c, a
if b > d:
b, d = d, b
if c == 0.0:
pass
else:
# print "sides a/c:", a/c
if (c - a) / c > prop_max:
prop_max = (c - a) / c
if (c - a) / c < prop_min:
prop_min = (c - a) / c
if d == 0.0:
pass
else:
# print "sides b/d", b/d
if (d - b) / d > prop_max:
prop_max = (d - b) / d
if (d - b) / d < prop_min:
prop_min = (d - b) / d
corners = Corner.get_corners(points)
for cor in corners:
if cor.angle < angle_min:
angle_min = cor.angle
if cor.angle > angle_max:
angle_max = cor.angle
if cor.rotation > rot_max:
rot_max = cor.rotation
a, b, c, d = [c.angle for c in corners]
if a > c:
a, c = c, a
if b > d:
b, d = d, b
if (c - a) / c > angle_diff_max:
angle_diff_max = (c - a) / c
if (c - a) / c < angle_diff_min:
angle_diff_min = (c - a) / c
# print "angle diff a/c", (c-a)/c
if (d - b) / d > angle_diff_max:
angle_diff_max = (d - b) / d
if (d - b) / d < angle_diff_min:
angle_diff_min = (d - b) / d
# print "angle diff b/d", (d-b)/d
if angle_diff_max > 0.90:
pass
def _predict(self,npoints):
cv.FillConvexPoly(self.draw_img, npoints, (0,0,0))
corners = Corner.get_corners(npoints)
tcorners = list(corners)
for i,cor in enumerate(corners):
print cor.p
if not(0<=cor.p[0]<self.size and 0<=cor.p[1]<self.size):
tcorners[i]=None
CP = CornerPredictor(self.corners, 1, self.tmp_img, self.timg, self.draw_img)
print "predicting....",tcorners
ncorners = CP.predict_corners(tcorners)
print 'done'
for i,cor in enumerate(ncorners):
v=vector(corners[i].p,cor.p)
print length(v), cor.toString()
self.assertTrue(length(v)<5,"Wrong prediction!Corner: %d \
Expected: (%d,%d) received (%d,%d)" \
%(i,corners[i].p[0],corners[i].p[1],cor.p[0],cor.p[1]))
print ncorners
def stats(points):
global prop_max, prop_min, angle_max, angle_min, rot_max, angle_diff_max, angle_diff_min
a = length(vector(points[0], points[1]))
b = length(vector(points[1], points[2]))
c = length(vector(points[2], points[3]))
d = length(vector(points[3], points[0]))
if a > c:
a, c = c, a
if b > d:
b, d = d, b
if c == 0.0:
pass
else:
#print "sides a/c:", a/c
if (c - a) / c > prop_max: prop_max = (c - a) / c
if (c - a) / c < prop_min: prop_min = (c - a) / c
if d == 0.0:
pass
else:
#print "sides b/d", b/d
if (d - b) / d > prop_max: prop_max = (d - b) / d
if (d - b) / d < prop_min: prop_min = (d - b) / d
corners = Corner.get_corners(points)
for cor in corners:
if cor.angle < angle_min: angle_min = cor.angle
if cor.angle > angle_max: angle_max = cor.angle
if cor.rotation > rot_max: rot_max = cor.rotation
a, b, c, d = [c.angle for c in corners]
if a > c:
a, c = c, a
if b > d:
b, d = d, b
if (c - a) / c > angle_diff_max: angle_diff_max = (c - a) / c
if (c - a) / c < angle_diff_min: angle_diff_min = (c - a) / c
#print "angle diff a/c", (c-a)/c
if (d - b) / d > angle_diff_max: angle_diff_max = (d - b) / d
if (d - b) / d < angle_diff_min: angle_diff_min = (d - b) / d
#print "angle diff b/d", (d-b)/d
if angle_diff_max > 0.90:
pass
def set_new_position(self, points_or_corners, offset=True, scale=1):
'''
Sets new position for this marker using points (in order)
@param points_or_corners: list of points or corners
@param offset: if true, image ROI is checked and points are shifted
'''
if len(points_or_corners) > 0 and type(points_or_corners[0]) == tuple:
self.predicted = -1
points = points_or_corners
img = self.m_d.img
(x, y, _, _) = rect = cv.GetImageROI(img)
if offset and (x, y) <> (0, 0):
points = map(lambda z: add((x, y), z), points)
cv.ResetImageROI(img)
crit = (cv.CV_TERMCRIT_EPS + cv.CV_TERMCRIT_ITER, 30, 0.1)
if (scale > 1):
points = cv.FindCornerSubPix(self.m_d.gray_img, points,
(scale * 2 + 4, scale * 2 + 4),
(-1, -1), crit)
else:
points = cv.FindCornerSubPix(self.m_d.gray_img, points, (3, 3),
(-1, -1), crit)
ncorners = Corner.get_corners(points, self.m_d.time)
if len(self.corners) <> 0:
for i, cor in enumerate(ncorners):
cor.compute_change(self.corners[i])
cv.SetImageROI(img, rect)
else:
ncorners = points_or_corners
self.predicted += len(filter(lambda x: x.is_predicted, ncorners))
for i, c in enumerate(ncorners):
c.black_inside = self.black_inside
# if len(self.corners)==4:
# if dist_points(c.p, self.corners[i].p)<4:
# c.p=self.corners[i].p
self.corners = ncorners
self.area = abs(cv.ContourArea(self.points))
self.last_seen = self.m_d.time
self.model_view = None
def set_new_position(self, points_or_corners, offset=True, scale=1):
'''
Sets new position for this marker using points (in order)
@param points_or_corners: list of points or corners
@param offset: if true, image ROI is checked and points are shifted
'''
if len(points_or_corners) > 0 and type(points_or_corners[0]) == tuple:
self.predicted = -1
points = points_or_corners
img = self.m_d.img
(x, y, _, _) = rect = cv.GetImageROI(img)
if offset and (x, y) <> (0, 0):
points = map(lambda z: add((x, y), z), points)
cv.ResetImageROI(img)
crit = (cv.CV_TERMCRIT_EPS + cv.CV_TERMCRIT_ITER, 30, 0.1)
if (scale > 1):
points = cv.FindCornerSubPix(self.m_d.gray_img, points, (scale * 2 + 4, scale * 2 + 4), (-1, -1), crit)
else:
points = cv.FindCornerSubPix(self.m_d.gray_img, points, (3, 3), (-1, -1), crit)
ncorners = Corner.get_corners(points, self.m_d.time)
if len(self.corners) <> 0:
for i, cor in enumerate(ncorners):
cor.compute_change(self.corners[i])
cv.SetImageROI(img, rect)
else:
ncorners = points_or_corners
self.predicted += len(filter(lambda x:x.is_predicted, ncorners))
for i,c in enumerate(ncorners):
c.black_inside=self.black_inside
# if len(self.corners)==4:
# if dist_points(c.p, self.corners[i].p)<4:
# c.p=self.corners[i].p
self.corners = ncorners
self.area = abs(cv.ContourArea(self.points))
self.last_seen = self.m_d.time
self.model_view = None
