X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/f2cbb185a9e09efb970203c376e5abcaa872c867..b1b5232a3561e92a40a26ff586ee3496b080692c:/hough.py?ds=inline

diff --git a/hough.py b/hough.py
index a8f64b2..0e9fe2d 100644
--- a/hough.py
+++ b/hough.py
@@ -2,8 +2,6 @@ from math import sin, cos, pi
 
 from PIL import Image
 
-from commons import clear
-
 class Hough:
     def __init__(self, size):
         self.size = size
@@ -20,8 +18,6 @@ class Hough:
         initial_angle = self.initial_angle
 
         for x in xrange(size[0]):
-            clear()
-            print "hough transform: {0:>3}/{1}".format(x + 1, size[0])
             for y in xrange(size[1]):
                 if image_l[x, y]:
                     # for every angle:
@@ -34,7 +30,7 @@ class Hough:
                                     size[0] / 2)
                         # column of the matrix closest to the distance
                         column = int(round(distance)) 
-                        if column >= 0 and column < size[0]:
+                        if 0 <= column < size[0]:
                             matrix[column][a] += 1
 
         new_image = Image.new('L', size)
@@ -50,6 +46,26 @@ class Hough:
             
         return new_image
 
+    def lines_from_list(self, p_list):
+        lines = []
+        for p in p_list:
+            lines.append(self.angle_distance(p))
+        return lines
+
+    def all_lines_h(self, image):
+        im_l = image.load()
+        lines1 = []
+        for x in xrange(image.size[0] / 2):
+            for y in xrange(image.size[1]):
+                if im_l[x, y]:
+                    lines1.append(self.angle_distance((x, y)))
+        lines2 = []
+        for x in xrange(image.size[0] / 2, image.size[0]):
+            for y in xrange(image.size[1]):
+                if im_l[x, y]:
+                    lines2.append(self.angle_distance((x, y)))
+        return [lines1, lines2]
+
     def all_lines(self, image):
         im_l = image.load()
         lines = []