-"""Imago intersections module"""
+"""Imago intersections module."""
from math import cos, tan, pi
from operator import itemgetter
import ImageDraw
+import filters
import k_means
+import output
def dst(line):
"""Return normalized line."""
def board(image, lines, show_all, do_something):
"""Compute intersections, find stone colors and return board situation."""
+ # TODO refactor show_all, do_something
lines = [dst_sort(l) for l in lines]
intersections = intersections_from_angl_dist(lines, image.size)
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")
+
board_raw = []
for line in intersections:
- board_raw.append([stone_color_raw(image, intersection) for intersection in
+ board_raw.append([stone_color_raw(image_c, intersection) for intersection in
line])
board_raw = sum(board_raw, [])
if show_all:
import matplotlib.pyplot as pyplot
+ import Image
+ fig = pyplot.figure(figsize=(8, 6))
pyplot.scatter(luma, saturation,
- color=[(s[2][0]/255., s[2][1]/255., s[2][2]/255., 1.)
- for s in board_raw])
- pyplot.show()
+ color=[(s[2][0]/255.,
+ s[2][1]/255.,
+ s[2][2]/255., 1.)
+ for s in board_raw])
+ pyplot.xlim(0,1)
+ pyplot.ylim(0,1)
+ fig.canvas.draw()
+ size = fig.canvas.get_width_height()
+ buff = fig.canvas.tostring_rgb()
+ 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.], [0.5, 0.5], [1., 1.]])
+ [[0., 0.5], [0.5, 0.5], [1., 0.5]])
#clusters.sort(key=mean_luma)
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]],
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()
+ pyplot.xlim(0,1)
+ pyplot.ylim(0,1)
+ fig.canvas.draw()
+ size = fig.canvas.get_width_height()
+ buff = fig.canvas.tostring_rgb()
+ image_p = Image.fromstring('RGB', size, buff, 'raw')
+ do_something(image_p, "color clustering")
clusters[0] = [(p[1], 'B') for p in clusters[0]]
clusters[1] = [(p[1], '.') for p in clusters[1]]
board_r = []
+ #TODO 19 should be a size parameter
try:
for i in xrange(19):
- board_r.append([])
for _ in xrange(19):
- board_r[i].append(board_rg.next())
+ board_r.append(board_rg.next())
except StopIteration:
pass
+
- return board_r
+ return output.Board(19, board_r)
def mean_luma(cluster):
+ """Return mean luma of the *cluster* of points."""
return sum(c[0][0] for c in cluster) / float(len(cluster))
def intersections_from_angl_dist(lines, size, get_all=True):
intersections.append(line)
return intersections
+def RGBtoSat(c):
+ """Using the HSI color model."""
+ max_diff = max(c) - min(c)
+ if max_diff == 0:
+ return 0
+ else:
+ return 1. - ((3. * min(c)) / sum(c))
+
def stone_color_raw(image, (x, y)):
"""Given image and coordinates, return stone color."""
+ size = 3
suma = []
- for i in range(-2, 3):
- for j in range(-2, 3):
+ t = 0
+ for i in range(-size, size + 1):
+ for j in range(-size, size + 1):
try:
suma.append(image.getpixel((x + i, y + j)))
+ t += 1
except IndexError:
pass
- luma = sum([0.30 * sum(s[0] for s in suma) / 25., 0.59 * sum(s[1] for s in suma) / 25.,
- 0.11 * sum(s[2] for s in suma) / 25.]) / 255.
- saturation = sum(max(s) - min(s) / float(255. - abs(max(s) + min(s) - 255))
- for s in suma) / (25. * 255.)
- color = [sum(s[0] for s in suma) / 25., sum(s[1] for s in suma) / 25.,
- sum(s[2] for s in suma) / 25.]
+ luma = sum([0.30 * sum(s[0] for s in suma) / t, 0.59 * sum(s[1] for s in suma) / t,
+ 0.11 * sum(s[2] for s in suma) / t]) / 255.
+ saturation = sum(RGBtoSat(s) for s in suma) / t
+ color = [sum(s[0] for s in suma) / t, sum(s[1] for s in suma) / t,
+ sum(s[2] for s in suma) / t]
return luma, saturation, color
projekty / imago.git / blobdiff