h2 = (h2[0] + z * dh, h2[1] + z)
return (distance(im_l, get_grid([v1, v2], [h1, h2], size), size))
-def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
+def find(lines, size, l1, l2, bounds, hough, show_all, do_something):
l1 = line_from_angl_dist(l1, size)
l2 = line_from_angl_dist(l2, size)
v1 = V(*l1[0]) - V(*l1[1])
#GaussianBlur is undocumented class, may not work in future versions of PIL
im_l_s = im_l.tostring()
- import time
- start = time.time()
+ #import time
+ #start = time.time()
f_dist = partial(job_4, im_l=im_l_s, v1=v1, v2=v2, h1=h1, h2=h2,
dv=delta_v, dh=delta_h, size=size)
grid_lines = [[l2ad(l, size) for l in grid[0]],
[l2ad(l, size) for l in grid[1]]]
- print time.time() - start
+ #print time.time() - start
### Show error surface
#
# delta_v, delta_h, x_v, y_v, x_h, y_h, size)
###
+ if show_all:
+
### Show grid over lines
#
- im_t = Image.new('RGB', im_l.size, None)
- im_t_l = im_t.load()
- im_l_l = im_l.load()
- for x in xrange(im_t.size[0]):
- for y in xrange(im_t.size[1]):
- im_t_l[x, y] = (im_l_l[x, y], 0, 0)
-
- im_t_d = ImageDraw.Draw(im_t)
- for l in grid[0] + grid[1]:
- im_t_d.line(l, width=1, fill=(0, 255, 0))
-
- do_something(im_t, "lines and grid")
+ im_t = Image.new('RGB', im_l.size, None)
+ im_t_l = im_t.load()
+ im_l_l = im_l.load()
+ for x in xrange(im_t.size[0]):
+ for y in xrange(im_t.size[1]):
+ im_t_l[x, y] = (im_l_l[x, y], 0, 0)
+
+ im_t_d = ImageDraw.Draw(im_t)
+ for l in grid[0] + grid[1]:
+ im_t_d.line(l, width=1, fill=(0, 255, 0))
+
+ do_something(im_t, "lines and grid")
###
return grid, grid_lines
lines, l1, l2, bounds, hough, im_h = linef.find_lines(image, show_all, do_something, verbose)
grid, lines = gridf.find(lines, image.size, l1, l2, bounds, hough,
- do_something, im_h)
+ show_all, do_something)
if show_all:
im_g = image.copy()
draw = ImageDraw.Draw(im_g)
draw.line(l, fill=(64, 255, 64), width=1)
do_something(im_g, "grid", name="grid")
- board, board_raw = intrsc.board(image, lines, show_all, do_something)
-
- ### Show color distribution
- #import matplotlib.pyplot as pyplot
- #luma = [(0.30 * s[0] + 0.59 * s[1] + 0.11 * s[2]) / 255.
- # for s in sum(board_raw, [])]
- #pyplot.scatter(luma,
- # [(max(s) - min(s)) / (255 - abs(max(s) + min(s) - 255))
- # for s in sum(board_raw, [])],
- # color=[(s[0]/255., s[1]/255., s[2]/255., 1.) for s in sum(board_raw, [])])
- #pyplot.show()
- ###
+ board = intrsc.board(image, lines, show_all, do_something)
#simple ASCII output:
for line in board:
import ImageDraw
+import k_means
+
def dst(line):
"""Return normalized line."""
if line[0] < pi / 2:
draw.point((x , y), fill=(120, 255, 120))
do_something(image_g, "intersections")
- board_r = []
board_raw = []
for line in intersections:
- board_r.append([stone_color(image, intersection) for intersection in
- line])
board_raw.append([stone_color_raw(image, intersection) for intersection in
line])
- return board_r, board_raw
+ board_raw = sum(board_raw, [])
+
+ ### Show color distribution
+ luma = [(0.30 * s[0] + 0.59 * s[1] + 0.11 * s[2]) / 255.
+ for s in board_raw]
+ saturation = [(max(s) - min(s)) / (255 - abs(max(s) + min(s) - 255))
+ for s in board_raw]
+ if show_all:
+ import matplotlib.pyplot as pyplot
+ pyplot.scatter(luma, saturation, color=[(s[0]/255., s[1]/255., s[2]/255., 1.)
+ for s in board_raw])
+ pyplot.show()
+
+ clusters = k_means.cluster(3, 2,zip(zip(luma, saturation), range(len(luma))),
+ [[0., 0.], [0.5, 0.25], [1., 0.5]])
+ #clusters.sort(key=mean_luma)
+
+ if show_all:
+ pyplot.scatter([d[0][0] for d in clusters[0]], [d[0][1] for d in clusters[0]],
+ color=(1,0,0,1))
+ pyplot.scatter([d[0][0] for d in clusters[1]], [d[0][1] for d in clusters[1]],
+ color=(0,1,0,1))
+ pyplot.scatter([d[0][0] for d in clusters[2]], [d[0][1] for d in clusters[2]],
+ color=(0,0,1,1))
+ pyplot.show()
+
+ clusters[0] = [(p[1], 'B') for p in clusters[0]]
+ clusters[1] = [(p[1], '.') for p in clusters[1]]
+ clusters[2] = [(p[1], 'W') for p in clusters[2]]
+
+ board_rl = sum(clusters, [])
+ board_rl.sort()
+ board_rg = (p[1] for p in board_rl)
+
+ board_r = []
+
+ try:
+ for i in xrange(19):
+ board_r.append([])
+ for _ in xrange(19):
+ board_r[i].append(board_rg.next())
+ except StopIteration:
+ pass
+
+ return board_r
+
+def mean_luma(cluster):
+ return sum(c[0][0] for c in cluster) / float(len(cluster))
def intersections_from_angl_dist(lines, size, get_all=True):
"""Take grid-lines and size of the image. Return intersections."""
intersections.append(line)
return intersections
-def stone_color(image, (x, y)):
- """Given image and coordinates, return stone color."""
- suma = 0.
- for i in range(-2, 3):
- for j in range(-2, 3):
- try:
- suma += sum(image.getpixel((x + i, y + j)))
- except IndexError:
- pass
- suma /= 3 * 25
- if suma < 55:
- return 'B'
- elif suma < 200:
- return '.'
- else:
- return 'W'
-
def stone_color_raw(image, (x, y)):
"""Given image and coordinates, return stone color."""
suma = []
--- /dev/null
+"""K-means module"""
+
+import random
+
+def cluster(k, d, data, i_centers=None):
+ borders = [(min(p[0][i] for p in data), max(p[0][i] for p in data))
+ for i in range(d) ]
+ if i_centers:
+ old_centers = i_centers
+ else:
+ old_centers = [[(h - l) * random.random() + l for (l, h) in borders]
+ for _ in range(k)]
+ clusters, centers = next_step(old_centers, data)
+ while delta(old_centers, centers) > 0:
+ old_centers = centers
+ clusters, centers = next_step(old_centers, data)
+
+ return clusters
+
+def next_step(centers, data):
+ clusters = [[] for _ in centers]
+ for point in data:
+ clusters[nearest(centers, point)].append(point)
+ centers = [centroid(c) for c in clusters]
+ return clusters, centers
+
+def nearest(centers, point):
+ d, i = min(((sum((p - c) ** 2 for (p, c) in zip(point[0], center)) ** 0.5 ,
+ index) if center else (float('inf'), len(centers)))
+ for (index, center) in enumerate(centers))
+ return i
+
+def centroid(cluster):
+ l = float(len(cluster))
+ try:
+ d = len(cluster[0][0]) #TODO empty cluster error
+ except IndexError:
+ return None
+ return [sum(c[0][i] for c in cluster) / l for i in range(d)]
+
+def delta(c1, c2):
+ return sum( (sum(abs(cc1 - cc2) for (cc1, cc2) in zip (ccc1, ccc2)) if ccc2
+ else 0.) for (ccc1, ccc2) in zip(c1, c2))
projekty / imago.git / commitdiff