lines.sort(key=itemgetter(1))
return lines
-def board(image, lines, show_all, do_something, logger):
- """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")
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 = []
#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))),
+ clusters, score = k_means.cluster(3, 2,zip(color_data, range(len(color_data))),
[[0., 0.5], [0.5, 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]],
except StopIteration:
pass
-
return output.Board(19, board_r)
def mean_luma(cluster):