cut-out experiment

[imago.git] / src / intrsc.py

diff --git a/src/intrsc.py b/src/intrsc.py
index 7455d0c..a2e0cd7 100644 (file)
--- a/src/intrsc.py
+++ b/src/intrsc.py
@@ -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 +47,56 @@ 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
+
+    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 = []
     
@@ -85,11 +133,17 @@ def board(image, lines, show_all, do_something):
     #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]])
+    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]],
@@ -124,7 +178,6 @@ def board(image, lines, show_all, do_something):
     except StopIteration:
         pass
     
-
     return output.Board(19, board_r)
 
 def mean_luma(cluster):
@@ -195,4 +248,28 @@ 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.)
-    return luma, saturation, color, hue
+
+    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