1 from math import sin, cos, pi
6 def __init__(self, size):
9 self.initial_angle = (pi / 4) + (self.dt / 2)
11 def transform(self, image):
12 image_l = image.load()
15 matrix = [[0]*size[1] for _ in xrange(size[0])]
18 initial_angle = self.initial_angle
20 for x in xrange(size[0]):
21 for y in xrange(size[1]):
24 for a in xrange(size[1]):
26 # distance is the dot product of vector (x, y) - centerpoint
27 # and a unit vector orthogonal to the angle
28 distance = (((x - (size[0] / 2)) * sin((dt * a) + initial_angle)) +
29 ((y - (size[1] / 2)) * -cos((dt * a) + initial_angle)) +
31 # column of the matrix closest to the distance
32 column = int(round(distance))
33 if 0 <= column < size[0]:
34 matrix[column][a] += 1
36 new_image = Image.new('L', size)
37 new_image_l = new_image.load()
39 minimum = min([min(m) for m in matrix])
41 maximum = max([max(m) for m in matrix]) - minimum
43 for y in xrange(size[1]):
44 for x in xrange(size[0]):
45 new_image_l[x, y] = (float(matrix[x][y] - minimum) / maximum) * 255
49 def lines_from_list(self, p_list):
52 lines.append(self.angle_distance(p))
55 def all_lines_h(self, image):
58 for x in xrange(image.size[0] / 2):
59 for y in xrange(image.size[1]):
61 lines1.append(self.angle_distance((x, y)))
63 for x in xrange(image.size[0] / 2, image.size[0]):
64 for y in xrange(image.size[1]):
66 lines2.append(self.angle_distance((x, y)))
67 return [lines1, lines2]
69 def all_lines(self, image):
72 for x in xrange(image.size[0]):
73 for y in xrange(image.size[1]):
75 lines.append(self.angle_distance((x, y)))
78 def angle_distance(self, point):
79 return (self.dt * point[1] + self.initial_angle, point[0] - self.size[0] / 2)