hough transform in C

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index 17be372..83a9771 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -1,6 +1,6 @@
 import Image, ImageDraw, ImageFilter
 
-from manual import lines as g_grid, l2ad
+from manual import lines as g_grid, l2ad, intersection, line as g_line
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist
 
@@ -32,12 +32,25 @@ class V():
     def t(self):
         return (self.x, self.y)
 
+    def normal(self):
+        return V(-self.y, self.x)
+
+def projection(point, line, vector):
+    n = vector.normal()
+    l2 = g_line(point.t(), (point + n).t())
+    return V(*intersection(l2, g_line(*line)))
+    
+
 def find(lines, size, l1, l2, bounds, hough, do_something):
     a, b, c, d = [V(*a) for a in bounds]
     l1 = line_from_angl_dist(l1, size)
     l2 = line_from_angl_dist(l2, size)
     v1 = V(*l1[0]) - V(*l1[1])
     v2 = V(*l2[0]) - V(*l2[1])
+    a = projection(a, l1, v1) 
+    b = projection(b, l1, v1) 
+    c = projection(c, l2, v2) 
+    d = projection(d, l2, v2) 
     grid = get_grid(a, b, c, d, hough, size)
     dist = distance(lines, grid, size)
     print dist
@@ -105,6 +118,7 @@ def distance(lines, grid, size):
     dr_g = ImageDraw.Draw(im_g)
     for line in grid[0] + grid[1]:
         dr_g.line(line, width=1, fill=255)
+    #im_g = im_g.filter(MyGaussianBlur(radius=3))
     im_d, distance = combine(im_l, im_g)
     return distance
 
@@ -120,7 +134,7 @@ def combine(bg, fg):
     for x in xrange(fg.size[0]):
         for y in xrange(fg.size[1]):
             if fg_l[x, y]:
-                res_l[x, y] = bg_l[x, y]
+                res_l[x, y] = bg_l[x, y] * fg_l[x, y]
                 score +=  bg_l[x, y]
                 area += 1