-from manual import lines as g_grid, l2ad
+import Image, ImageDraw, ImageFilter
+
+from manual import lines as g_grid, l2ad, intersection, line as g_line
from intrsc import intersections_from_angl_dist
+from linef import line_from_angl_dist
+
+class GridFittingFailedError(Exception):
+ pass
+
+class MyGaussianBlur(ImageFilter.Filter):
+ name = "GaussianBlur"
+
+ def __init__(self, radius=2):
+ self.radius = radius
+ def filter(self, image):
+ return image.gaussian_blur(self.radius)
+
+class V():
+ def __init__(self, x, y):
+ self.x = x
+ self.y = y
+
+ def __add__(self, other):
+ return V(self.x + other.x, self.y + other.y)
+
+ def __sub__(self, other):
+ return V(self.x - other.x, self.y - other.y)
+
+ def __rmul__(self, other):
+ return V(other * self.x, other * self.y)
+
+ def t(self):
+ return (self.x, self.y)
+
+ def normal(self):
+ return V(-self.y, self.x)
+
+def projection(point, line, vector):
+ n = vector.normal()
+ l2 = g_line(point.t(), (point + n).t())
+ return V(*intersection(l2, g_line(*line)))
+
-def find(lines, size, l1, l2):
- c = intersections_from_angl_dist(lines, size)
- corners = [c[0][0], c[0][-1], c[-1][0], c[-1][-1]]
+def find(lines, size, l1, l2, bounds, hough, do_something):
+ a, b, c, d = [V(*a) for a in bounds]
+ l1 = line_from_angl_dist(l1, size)
+ l2 = line_from_angl_dist(l2, size)
+ v1 = V(*l1[0]) - V(*l1[1])
+ v2 = V(*l2[0]) - V(*l2[1])
+ a = projection(a, l1, v1)
+ b = projection(b, l1, v1)
+ c = projection(c, l2, v2)
+ d = projection(d, l2, v2)
+ grid = get_grid(a, b, c, d, hough, size)
+ dist = distance(lines, grid, size)
+ print dist
+
+ s = 0.02
+ while True:
+ ts1 = [(s, 0), (-s, 0), (s, s), (-s, -s), (-s, s), (s, -s), (0, s), (0, -s)]
+ grids = [(get_grid(a + t[0] * v1, b + t[1] * v1,
+ c, d, hough, size), t) for t in ts1]
+ distances = [(distance(lines, grid, size),
+ grid, t) for grid, t in grids]
+ distances.sort(reverse=True)
+ if distances[0][0] > dist:
+ dist = distances[0][0]
+ grid = distances[0][1]
+ t = distances[0][2]
+ a, b = a + t[0] * v1, b + t[1] * v1
+ print dist
+ s *= 0.75
+ else:
+ break
+
+ print "---"
+
+ s = 0.02
+ while True:
+ ts1 = [(s, 0), (-s, 0), (s, s), (-s, -s), (-s, s), (s, -s), (0, s), (0, -s)]
+ grids = [(get_grid(a, b,
+ c + t[0] * v2, d + t[1] * v2, hough, size), t) for t in ts1]
+ distances = [(distance(lines, grid, size),
+ grid, t) for grid, t in grids]
+ distances.sort(reverse=True)
+ if distances[0][0] > dist:
+ dist = distances[0][0]
+ grid = distances[0][1]
+ t = distances[0][2]
+ c, d = c + t[0] * v2, d + t[1] * v2
+ print dist
+ s *= 0.75
+ else:
+ break
+
+ grid_lines = [[l2ad(l, size) for l in grid[0]], [l2ad(l, size) for l in grid[1]]]
+ return grid, grid_lines
+
+def get_grid(a, b, c, d, hough, size):
+ l1 = hough.lines_from_list([a.t(), b.t()])
+ l2 = hough.lines_from_list([c.t(), d.t()])
+ c = intersections_from_angl_dist([l1, l2], size, get_all=True)
+ corners = (c[0] + c[1])
+ if len(corners) < 4:
+ print l1, l2, c
+ raise GridFittingFailedError
grid = g_grid(corners)
return grid
+
+def distance(lines, grid, size):
+ im_l = Image.new('L', size)
+ dr_l = ImageDraw.Draw(im_l)
+ for line in sum(lines, []):
+ dr_l.line(line_from_angl_dist(line, size), width=1, fill=255)
+ im_l = im_l.filter(MyGaussianBlur(radius=3))
+ # GaussianBlur is undocumented class, may not work in future versions of PIL
+ im_g = Image.new('L', size)
+ dr_g = ImageDraw.Draw(im_g)
+ for line in grid[0] + grid[1]:
+ dr_g.line(line, width=1, fill=255)
+ #im_g = im_g.filter(MyGaussianBlur(radius=3))
+ im_d, distance = combine(im_l, im_g)
+ return distance
+
+def combine(bg, fg):
+ bg_l = bg.load()
+ fg_l = fg.load()
+ res = Image.new('L', fg.size)
+ res_l = res.load()
+
+ score = 0
+ area = 0
+
+ for x in xrange(fg.size[0]):
+ for y in xrange(fg.size[1]):
+ if fg_l[x, y]:
+ res_l[x, y] = bg_l[x, y] * fg_l[x, y]
+ score += bg_l[x, y]
+ area += 1
+
+ return res, float(score)/area
projekty / imago.git / blobdiff