parameters

[imago.git] / src / intrsc.py

diff --git a/src/intrsc.py b/src/intrsc.py
index 7455d0c..91801fe 100644 (file)
--- 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]
@@ -87,9 +94,17 @@ def board(image, lines, show_all, do_something):
     #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]
 
-    clusters = k_means.cluster(3, 2,zip(color_data, range(len(color_data))),
-                               [[0., 0.5], [0.5, 0.5], [1., 0.5]])
-
+    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]],
@@ -124,7 +139,6 @@ def board(image, lines, show_all, do_something):
     except StopIteration:
         pass
     
-
     return output.Board(19, board_r)
 
 def mean_luma(cluster):