def intersection((a1, b1, c1), (a2, b2, c2)):
delim = float(a1 * b2 - b1 * a2)
+ if delim == 0:
+ return None
x = (b1 * c2 - c1 * b2) / delim
y = (c1 * a2 - a1 * c2) / delim
return x, y
# TODO create an intersection?
try:
yield manual.lines(map(lambda p: p.to_tuple(), [c2, c1, c3, c4]))
- except (TypeError, ZeroDivisionError):
+ except (TypeError):
pass
# the square was too small to fit 17 lines inside
# TODO define SquareTooSmallError or something
points = [l.points for l in new_lines1]
- for trial in xrange(3):
+ def dst_p(x, y):
+ x = x - size[0] / 2
+ y = y - size[1] / 2
+ return sqrt(x * x + y * y)
+
+ for n_tries in xrange(3):
model = Diagonal_model(points)
- diag_lines = ransac.ransac_multi(2, points, 2, 800, model=model)
- [(line1, cons), (line2, cons2)] = diag_lines
- center = intersection(line1, line2)
- data = sum(points, [])
- diag1 = Line(line1)
- diag1.points = ransac.filter_near(data, diag1, 2)
- diag2 = Line(line2)
- diag2.points = ransac.filter_near(data, diag2, 2)
+ diag_lines = ransac.ransac_multi(6, points, 2, 800, model=model)
+ diag_lines = [l[0] for l in diag_lines]
+ centers = []
+ cen_lin = []
+ for i in xrange(len(diag_lines)):
+ line1 = diag_lines[i]
+ for line2 in diag_lines[i+1:]:
+ c = intersection(line1, line2)
+ if c and dst_p(*c) < min(size) / 2:
+ cen_lin.append((line1, line2, c))
+ centers.append(c)
if show_all:
import matplotlib.pyplot as pyplot
pyplot.plot([0, max_x], [find_y(0), find_y(max_x)], color='b')
fig = pyplot.figure(figsize=(8, 6))
- plot_line_g(diag1, size[0])
- plot_line_g(diag2, size[0])
+ for l in diag_lines:
+ plot_line_g(l, size[0])
pyplot.scatter(*zip(*sum(points, [])))
- pyplot.scatter([center[0]], [center[1]], color='r')
+ if len(centers) >= 1:
+ pyplot.scatter([c[0] for c in centers], [c[1] for c in centers], color='r')
pyplot.xlim(0, size[0])
pyplot.ylim(0, size[1])
pyplot.gca().invert_yaxis()
size_f = fig.canvas.get_width_height()
buff = fig.canvas.tostring_rgb()
image_p = Image.fromstring('RGB', size_f, buff, 'raw')
- do_something(image_p, "finding diagonal")
+ do_something(image_p, "finding diagonals")
-
- grids = list(gen_corners(diag1, diag2))
-
- try:
- sc, grid = min(map(lambda g: (score(sum(g, []), data), g), grids))
+ data = sum(points, [])
+ # TODO what if lines are missing?
+ sc = float("inf")
+ grid = None
+ for (line1, line2, c) in cen_lin:
+ diag1 = Line(line1)
+ diag1.points = ransac.filter_near(data, diag1, 2)
+ diag2 = Line(line2)
+ diag2.points = ransac.filter_near(data, diag2, 2)
+
+
+ grids = list(gen_corners(diag1, diag2))
+
+ try:
+ new_sc, new_grid = min(map(lambda g: (score(sum(g, []), data), g), grids))
+ if new_sc < sc:
+ sc, grid = new_sc, new_grid
+ except ValueError:
+ pass
+ if grid:
break
- except ValueError:
- pass
else:
raise GridFittingFailedError