X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/f1094e68978c348e13ddc4f1da0af6d481ec7cf0..be7942c3c75a64979e60b50cf76aa1000ec57413:/src/intrsc.py?ds=sidebyside

diff --git a/src/intrsc.py b/src/intrsc.py
index 977ad84..7455d0c 100644
--- a/src/intrsc.py
+++ b/src/intrsc.py
@@ -2,6 +2,7 @@
 
 from math import cos, tan, pi
 from operator import itemgetter
+import colorsys
 
 import ImageDraw
 
@@ -57,18 +58,15 @@ def board(image, lines, show_all, do_something):
     board_raw = sum(board_raw, [])
 
     ### Show color distribution
-    luma = [s[0] for s in board_raw]
-    saturation = [s[1] for s in board_raw]
 
     if show_all:
         import matplotlib.pyplot as pyplot
         import Image
         fig = pyplot.figure(figsize=(8, 6))
+        luma = [s[0] for s in board_raw]
+        saturation = [s[1] for s in board_raw]
         pyplot.scatter(luma, saturation, 
-                       color=[(s[2][0]/255.,
-                               s[2][1]/255.,
-                               s[2][2]/255., 1.) 
-                                   for s in board_raw])
+                       color=[s[2] for s in board_raw])
         pyplot.xlim(0,1)
         pyplot.ylim(0,1)
         fig.canvas.draw()
@@ -77,7 +75,19 @@ def board(image, lines, show_all, do_something):
         image_p = Image.fromstring('RGB', size, buff, 'raw')
         do_something(image_p, "color distribution")
 
-    clusters = k_means.cluster(3, 2,zip(zip(luma, saturation), range(len(luma))),
+    #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]
+
+    clusters = k_means.cluster(3, 2,zip(color_data, range(len(color_data))),
                                [[0., 0.5], [0.5, 0.5], [1., 0.5]])
 
     if show_all:
@@ -118,7 +128,7 @@ def board(image, lines, show_all, do_something):
     return output.Board(19, board_r)
 
 def mean_luma(cluster):
-    """Return mean luma of the *cluster* of points."""
+    """Return mean luminanace of the *cluster* of points."""
     return sum(c[0][0] for c in cluster) / float(len(cluster))
 
 def to_general(line, size):
@@ -148,7 +158,7 @@ def intersections_from_angl_dist(lines, size, get_all=True):
     return intersections
    
 def rgb2lumsat(color):
-    """Convert RGB to luma and HSI model saturation."""
+    """Convert RGB to luminance and HSI model saturation."""
     r, g, b = color
     luma = (0.30 * r + 0.59 * g + 0.11 * b) / 255.0
     max_diff = max(color) - min(color)
@@ -179,8 +189,10 @@ def stone_color_raw(image, (x, y)):
     norm = float(len(points))
     if norm == 0:
         return 0, 0, (0, 0, 0) #TODO trow exception here
+    norm = float(norm*255)
     color = (sum(p[0] for p in points) / norm,
              sum(p[1] for p in points) / norm,
              sum(p[2] for p in points) / norm)
-    luma, saturation = rgb2lumsat(color)
-    return luma, saturation, color
+    hue, luma, saturation = colorsys.rgb_to_hls(*color)
+    color = colorsys.hls_to_rgb(hue, 0.5, 1.)
+    return luma, saturation, color, hue