X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/f38706a873ac4411716c32986b17f339dc68ea57..666ac3553431948203df831afe240beb3fcaec32:/src/intrsc.py?ds=inline

diff --git a/src/intrsc.py b/src/intrsc.py
index 546d0f2..91801fe 100644
--- a/src/intrsc.py
+++ b/src/intrsc.py
@@ -4,7 +4,7 @@ from math import cos, tan, pi
 from operator import itemgetter
 import colorsys
 
-import ImageDraw
+from PIL import ImageDraw
 
 import filters
 import k_means
@@ -26,10 +26,11 @@ def dst_sort(lines):
     lines.sort(key=itemgetter(1))
     return lines
 
-def board(image, lines, show_all, do_something):
-    """Compute intersections, find stone colors and return board situation."""
+def b_intersects(image, lines, show_all, do_something, logger):
+    """Compute intersections."""
     # TODO refactor show_all, do_something
     # TODO refactor this into smaller functions
+    logger("finding the stones")
     lines = [dst_sort(l) for l in lines]
     an0 = (sum([l[0] for l in lines[0]]) / len(lines[0]) - pi / 2)
     an1 = (sum([l[0] for l in lines[1]]) / len(lines[1]) - pi / 2)
@@ -46,9 +47,15 @@ def board(image, lines, show_all, do_something):
                 draw.point((x , y), fill=(120, 255, 120))
         do_something(image_g, "intersections")
 
-    image_c = filters.color_enhance(image)
-    if show_all:
-        do_something(image_c, "white balance")
+    return intersections
+
+def board(image, intersections, show_all, do_something, logger):
+    """Find stone colors and return board situation."""
+
+#    image_c = filters.color_enhance(image)
+#    if show_all:
+#        do_something(image_c, "white balance")
+    image_c = image
     
     board_raw = []
     
@@ -61,7 +68,7 @@ def board(image, lines, show_all, do_something):
 
     if show_all:
         import matplotlib.pyplot as pyplot
-        import Image
+        from PIL import Image
         fig = pyplot.figure(figsize=(8, 6))
         luma = [s[0] for s in board_raw]
         saturation = [s[1] for s in board_raw]
@@ -75,20 +82,29 @@ def board(image, lines, show_all, do_something):
         image_p = Image.fromstring('RGB', size, buff, 'raw')
         do_something(image_p, "color distribution")
 
-    max_s0 = max(s[0] for s in board_raw)
-    min_s0 = min(s[0] for s in board_raw)
-    norm_s0 = lambda x: (x - min_s0) / (max_s0 - min_s0)
-    max_s1 = max(s[1] for s in board_raw)
-    min_s1 = min(s[1] for s in board_raw)
-    norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1)
-    max_s1 = max(s[1] for s in board_raw)
-    min_s1 = min(s[1] for s in board_raw)
-    norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1)
-    color_data = [(norm_s0(s[0]), norm_s1(s[1])) for s in board_raw]
-
-    clusters = k_means.cluster(3, 2,zip(color_data, range(len(color_data))),
-                               [[0., 0.5], [0.5, 0.5], [1., 0.5]])
-
+    #max_s0 = max(s[0] for s in board_raw)
+    #min_s0 = min(s[0] for s in board_raw)
+    #norm_s0 = lambda x: (x - min_s0) / (max_s0 - min_s0)
+    #max_s1 = max(s[1] for s in board_raw)
+    #min_s1 = min(s[1] for s in board_raw)
+    #norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1)
+    #max_s1 = max(s[1] for s in board_raw)
+    #min_s1 = min(s[1] for s in board_raw)
+    #norm_s1 = lambda x: (x - min_s1) / (max_s1 - min_s1)
+    #color_data = [(norm_s0(s[0]), norm_s1(s[1])) for s in board_raw]
+    color_data = [(s[0], s[1]) for s in board_raw]
+
+    init_x = sum(c[0] for c in color_data) / float(len(color_data))
+
+    clusters, score = k_means.cluster(3, 2,zip(color_data, range(len(color_data))),
+                               [[0., 0.5], [init_x, 0.5], [1., 0.5]])
+#    clusters1, score1 = k_means.cluster(1, 2,zip(color_data, range(len(color_data))),
+#                               [[0.5, 0.5]])
+#    clusters2, score2 = k_means.cluster(2, 2,zip(color_data, range(len(color_data))),
+#                               [[0., 0.5], [0.75, 0.5]])
+#    import sys
+#    print >> sys.stderr, score1, score2, score
+#
     if show_all:
         fig = pyplot.figure(figsize=(8, 6))
         pyplot.scatter([d[0][0] for d in clusters[0]], [d[0][1] for d in clusters[0]],
@@ -123,7 +139,6 @@ def board(image, lines, show_all, do_something):
     except StopIteration:
         pass
     
-
     return output.Board(19, board_r)
 
 def mean_luma(cluster):
@@ -194,5 +209,4 @@ def stone_color_raw(image, (x, y)):
              sum(p[2] for p in points) / norm)
     hue, luma, saturation = colorsys.rgb_to_hls(*color)
     color = colorsys.hls_to_rgb(hue, 0.5, 1.)
-    print color
     return luma, saturation, color, hue