cut-out experiment
[imago.git] / src / intrsc.py
index 977ad84..a2e0cd7 100644 (file)
@@ -2,6 +2,7 @@
 
 from math import cos, tan, pi
 from operator import itemgetter
 
 from math import cos, tan, pi
 from operator import itemgetter
+import colorsys
 
 import ImageDraw
 
 
 import ImageDraw
 
@@ -25,10 +26,11 @@ def dst_sort(lines):
     lines.sort(key=itemgetter(1))
     return 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
     # 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)
     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)
@@ -45,9 +47,56 @@ def board(image, lines, show_all, do_something):
                 draw.point((x , y), fill=(120, 255, 120))
         do_something(image_g, "intersections")
 
                 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
+
+    image_l = image_c.load()
+    import Image, sys
+    new_image = Image.new('RGB', (19 * 7, 19 * 7))
+    image_nl = new_image.load()
+    new_image2 = Image.new('L', (19 * 7, 19 * 7))
+    image_nll = new_image2.load()
+    y = 3
+    for line in intersections:
+        x = 3
+        for (xi, yi) in line:
+            for xx in [-3,-2,-1,0,1,2,3]:
+                for yy in [-3,-2,-1,0,1,2,3]:
+                    try:
+                        image_nl[x + xx, y + yy] = image_l[xi + xx, yi + yy]
+                    except IndexError:
+                        pass
+            for xx in [-2,-1,0,1,2]:
+                for yy in [-2,-1,0,1,2]:
+                    try:
+                        z = xi + xx
+                        w = yi + yy
+                        luma = lambda ((r,g,b)): colorsys.rgb_to_hls(r / 255., g /
+                                                                   255. ,b /
+                                                                   255.)[1]
+                        image_nll[x + xx, y + yy] = (luma(image_l[z, w]) * (-8)  +
+                                                     luma(image_l[z - 1, w - 1]) +
+                                                     luma(image_l[z - 1, w]) +
+                                                     luma(image_l[z - 1, w + 1]) +
+                                                     luma(image_l[z, w - 1]) +
+                                                     luma(image_l[z, w + 1]) +
+                                                     luma(image_l[z + 1, w - 1]) +
+                                                     luma(image_l[z + 1, w]) +
+                                                     luma(image_l[z + 1, w + 1])) * 255
+                    except IndexError:
+                        pass
+            x += 7
+        y += 7
+    do_something(new_image, "intersections")
+    do_something(new_image2, "intersections")
+
     
     board_raw = []
     
     
     board_raw = []
     
@@ -57,18 +106,15 @@ def board(image, lines, show_all, do_something):
     board_raw = sum(board_raw, [])
 
     ### Show color distribution
     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))
 
     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, 
         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()
         pyplot.xlim(0,1)
         pyplot.ylim(0,1)
         fig.canvas.draw()
@@ -77,9 +123,27 @@ def board(image, lines, show_all, do_something):
         image_p = Image.fromstring('RGB', size, buff, 'raw')
         do_something(image_p, "color distribution")
 
         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))),
-                               [[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],s[4]) for s in board_raw]
 
 
+    clusters, score = k_means.cluster(3, 3,zip(color_data, range(len(color_data))),
+                               [[0., 0.5,0.0], [0.5, 0.5, 0.], [1., 0.5, 0.]])
+#    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]],
     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]],
@@ -114,11 +178,10 @@ def board(image, lines, show_all, do_something):
     except StopIteration:
         pass
     
     except StopIteration:
         pass
     
-
     return output.Board(19, board_r)
 
 def mean_luma(cluster):
     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):
     return sum(c[0][0] for c in cluster) / float(len(cluster))
 
 def to_general(line, size):
@@ -148,7 +211,7 @@ def intersections_from_angl_dist(lines, size, get_all=True):
     return intersections
    
 def rgb2lumsat(color):
     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)
     r, g, b = color
     luma = (0.30 * r + 0.59 * g + 0.11 * b) / 255.0
     max_diff = max(color) - min(color)
@@ -179,8 +242,34 @@ 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(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)
     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.)
+
+    der = 0
+    image_l = image.load()
+    for xx in [-2,-1,0,1,2]:
+        for yy in [-2,-1,0,1,2]:
+            try:
+                z = x + xx
+                w = y + yy
+                lumal = lambda ((r,g,b)): colorsys.rgb_to_hls(r / 255., g /
+                                                           255. ,b /
+                                                           255.)[1]
+                der += (lumal(image_l[z, w]) * (-8)  +
+                         lumal(image_l[z - 1, w - 1]) +
+                         lumal(image_l[z - 1, w]) +
+                         lumal(image_l[z - 1, w + 1]) +
+                         lumal(image_l[z, w - 1]) +
+                         lumal(image_l[z, w + 1]) +
+                         lumal(image_l[z + 1, w - 1]) +
+                         lumal(image_l[z + 1, w]) +
+                         lumal(image_l[z + 1, w + 1]))
+            except IndexError:
+                pass
+
+    der = max(der / 36., 0)
+    return luma, saturation, color, hue, der