X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/145417a1698105ca84eeb57c650181f8777667e5..2b3e40c0c1702b8519531cd76df28c6ec207ac33:/hough.py?ds=sidebyside

diff --git a/hough.py b/hough.py
index 0e9fe2d..ec8058c 100644
--- a/hough.py
+++ b/hough.py
@@ -2,6 +2,8 @@ from math import sin, cos, pi
 
 from PIL import Image
 
+import pcf
+
 class Hough:
     def __init__(self, size):
         self.size = size
@@ -9,42 +11,9 @@ class Hough:
         self.initial_angle = (pi / 4) + (self.dt / 2)
 
     def transform(self, image):
-        image_l = image.load()
-        size = image.size
-        
-        matrix = [[0]*size[1] for _ in xrange(size[0])]
-
-        dt = self.dt
-        initial_angle = self.initial_angle
-
-        for x in xrange(size[0]):
-            for y in xrange(size[1]):
-                if image_l[x, y]:
-                    # for every angle:
-                    for a in xrange(size[1]):
-                        # find the distance:
-                        # distance is the dot product of vector (x, y) - centerpoint
-                        # and a unit vector orthogonal to the angle
-                        distance = (((x - (size[0] / 2)) * sin((dt * a) + initial_angle)) + 
-                                    ((y - (size[1] / 2)) * -cos((dt * a) + initial_angle)) +
-                                    size[0] / 2)
-                        # column of the matrix closest to the distance
-                        column = int(round(distance)) 
-                        if 0 <= column < size[0]:
-                            matrix[column][a] += 1
-
-        new_image = Image.new('L', size)
-        new_image_l = new_image.load()
-
-        minimum = min([min(m) for m in matrix])
-
-        maximum = max([max(m) for m in matrix]) - minimum
-
-        for y in xrange(size[1]):
-            for x in xrange(size[0]):
-                new_image_l[x, y] = (float(matrix[x][y] - minimum) / maximum) * 255
-            
-        return new_image
+        image_s = pcf.hough(image.size, image.tostring(), self.initial_angle, self.dt)
+        image = Image.fromstring('L', image.size, image_s)
+        return image
 
     def lines_from_list(self, p_list):
         lines = []