better grid-fitting

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index dcffd92..0c5b68f 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -1,7 +1,6 @@
 """Imago grid-fitting module"""
 
 import multiprocessing
-import itertools
 
 import Image, ImageDraw, ImageFilter
 
@@ -38,6 +37,16 @@ def job_br2(args):
                     get_grid([v1, v2], [h1, h2], size),
                     size), x, y) 
 
+def job_4(args):
+    im_l, v1, v2, h1, h2, x, y, w, z, dv, dh, size = args
+    v1 = (v1[0] + x * dv, v1[1] + x)
+    v2 = (v2[0] + y * dv, v2[1] + y)
+    h1 = (h1[0] + w * dh, h1[1] + w)
+    h2 = (h2[0] + z * dh, h2[1] + z)
+    return (distance(im_l, 
+                    get_grid([v1, v2], [h1, h2], size),
+                    size), x, y, w, z) 
+
 def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
     l1 = line_from_angl_dist(l1, size)
     l2 = line_from_angl_dist(l2, size)
@@ -64,18 +73,36 @@ def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
     #GaussianBlur is undocumented class, may not work in future versions of PIL
     im_l_s = im_l.tostring()
 
-    #let's try the bruteforce aproach:
-    k = 30
-
+    #let's try the ULTRA bruteforce aproach:
     pool = multiprocessing.Pool(None)
 
-    tasks = [(im_l_s, v1, v2, h1, h2, x, y, delta_v, delta_h, size) for (x, y) in
-             itertools.product(xrange(-k, k), xrange(-k, k))]
+    #import time
+    #start = time.time()
 
-    opt_v = pool.map(job_br1, tasks, 8)
-    opt_h = pool.map(job_br2, tasks, 8)
-    _, x_v, y_v = max(opt_v)
-    _, x_h, y_h = max(opt_h)
+    k = 30 
+    tasks = [(im_l_s, v1, v2, h1, h2, x, y, w, z, delta_v, delta_h, size) 
+             for x in xrange(-k, k, 2)
+             for y in xrange(-k, k, 2)
+             for z in xrange(-k, k, 2)
+             for w in xrange(-k, k, 2)]
+
+    opt = pool.map(job_4, tasks)
+    _, x_v, y_v, x_h, y_h = max(opt)
+
+    v1 = (v1[0] + x_v * delta_v, v1[1] + x_v)
+    v2 = (v2[0] + y_v * delta_v, v2[1] + y_v)
+    h1 = (h1[0] + x_h * delta_h, h1[1] + x_h)
+    h2 = (h2[0] + y_h * delta_h, h2[1] + y_h)
+
+    k = 5 
+    tasks = [(im_l_s, v1, v2, h1, h2, x, y, w, z, delta_v, delta_h, size) 
+             for x in xrange(-k, k)
+             for y in xrange(-k, k)
+             for z in xrange(-k, k)
+             for w in xrange(-k, k)]
+
+    opt = pool.map(job_4, tasks)
+    _, x_v, y_v, x_h, y_h = max(opt)
 
     v1 = (v1[0] + x_v * delta_v, v1[1] + x_v)
     v2 = (v2[0] + y_v * delta_v, v2[1] + y_v)
@@ -89,6 +116,8 @@ def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
     pool.terminate()
     pool.join()
     
+    #print time.time() - start
+    
 ### Show error surface
 #
 #    from gridf_analyzer import error_surface