def __init__(self, radius, image, center=None, position=None):
"""
Arguments: *radius* is 3 or 5, *image* is an OpenCV Mat, optional args
are (x, y) tuples.
Note: *center* takes precedence over conflicting *position*.
"""
self.radius = radius
self.height = self.width = radius + 1 + radius
self.image = image
if center != None:
self.center = center
self.position = Point(get_x(center) - radius, get_y(center) - radius)
elif position != None:
self.position = position
self.center = Point(get_x(position) + radius, get_y(position) + radius)
else:
self.position = Point(0, 0)
self.center = Point(radius, radius)
if(radius==3):
self.points = [ Point( 6, 3),
Point( 5, 1),
Point( 3, 0),
Point( 1, 1),
Point( 0, 3),
Point( 1, 5),
Point( 3, 6),
Point( 5, 5) ]
elif(radius==5):
self.points = [ Point(10, 5),
Point(10, 3),
Point( 9, 1),
Point( 7, 0),
Point( 5, 0),
Point( 3, 0),
Point( 1, 1),
Point( 0, 3),
Point( 0, 5),
Point( 0, 7),
Point( 1, 9),
Point( 3, 10),
Point( 5, 10),
Point( 7, 10),
Point( 9, 9),
Point(10, 7) ]
else:
print('Error: radius value' + radius + 'unsupported')
exit()
def at3(self, x, y):
"""
Returns intensity of pixel in *self.image* corresponding to (*x*, *y*) in
sample window.
"""
absx = x + get_x(self.position)
absy = y + get_y(self.position)
return sum(self.image[absy][absx])
def cornerfind_from_ChESS(self):
"""
todo
"""
points = [Point(x, y, sum(self.img[y][x])) for y in range(self.rows) for x in range(self.cols)]
clusters = kmeans_tc(points, [Point(0, 0), Point(self.cols - 1, 0)])
identify_boards(clusters)
for cluster in clusters:
print str(cluster.size())
for corner in cluster.corners:
print "\t" + str(get_x(corner)) + "," + str(get_y(corner))
def savetxt(self, fstem):
(rowlen, nrows) = self.dims
P = []
i = 0
for rownum in range(nrows):
row = []
for pos in range(rowlen):
point = self.points[i]
x = get_x(point)
y = get_y(point)
row.append([x, y])
i += 1
P.insert(0, row)
np.save(fstem, np.asarray(P))
np.savetxt(fstem+"hom.txt", self.H)
def calc_center(self):
"""
Finds the average coordinates of *self.points*, weighted by pixel intensity,
and saves them in *self.center*.
"""
N = 0
Ex = 0
Ey = 0
for point in self.points:
x = get_x(point)
y = get_y(point)
z = get_z(point)
N += z
Ex += z*x
Ey += z*y
self.prevcenter = self.center
self.center = Point(Ex/N, Ey/N)
def at2(self, point):
"""
Returns intensity of pixel in *self.image* corresponding to tuple *point*
in sample window.
"""
return self.at3(get_x(point), get_y(point))
