X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/f6002686fef1bd826f3a1777998416b93d909d56..f16fe1e775f2159741146264a6494e63b0e2d618:/gridf.py?ds=inline diff --git a/gridf.py b/gridf.py index c8f4b90..d39bdd5 100644 --- a/gridf.py +++ b/gridf.py @@ -1,8 +1,150 @@ +"""Imago grid-fitting module""" + +import multiprocessing + +import Image, ImageDraw, ImageFilter + +from geometry import V, projection from manual import lines as g_grid, l2ad from intrsc import intersections_from_angl_dist +from linef import line_from_angl_dist +import pcf + +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) + +def job_br1(args): + X, Y, im_l, a, b, c, d, s, v1, v2, k, hough, size = args + return [(distance(im_l, + get_grid(a + X[y] * s * v1, + b + Y[y] * s * v1, + c, d, hough, size), + size), a + X[y] * s * v1, b + Y[y] * s * v1) for y in range(2 *k)] + +def job_br2(args): + X, Y, im_l, a, b, c, d, s, v1, v2, k, hough, size = args + return [(distance(im_l, + get_grid(a, b, c + X[y] * s * v2, + d + Y[y] * s * v2, + hough, size), + size), c + X[y] * s * v2, d + Y[y] * s * v2) for y in range(2 *k)] + +def find(lines, size, l1, l2, bounds, hough, do_something, im_h): + 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) + + 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_h #hocus pocus + im_l = im_l.filter(MyGaussianBlur(radius=2)) + #GaussianBlur is undocumented class, may not work in future versions of PIL + im_l_s = im_l.tostring() + + #from gridf_analyzer import error_surface + #error_surface(im_l, a, b, c, d, hough, size, v1 ,v2) -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]] + grid = get_grid(a, b, c, d, hough, size) + + #let's try the bruteforce aproach: + s = 0.001 + k = 50 + X, Y = [], [] + for i in range(-k, k): + X.append(range(-k, k)) + Y.append(2*k*[i]) + + pool = multiprocessing.Pool(None) + + tasks = [(X[x], Y[x], im_l_s, a, b, c, d, s, + v1, v2, k, hough, size) for x in xrange(0, 2 * k)] + + import time + start = time.time() + opt_ab = pool.map(job_br1, tasks, 1) + opt_cd = pool.map(job_br2, tasks, 1) + d1 = 0 + for lst in opt_ab: + for tpl in lst: + if tpl[0] > d1: + d1 = tpl[0] + a, b = tpl[1], tpl[2] + d1 = 0 + for lst in opt_cd: + for tpl in lst: + if tpl[0] > d1: + d1 = tpl[0] + c, d = tpl[1], tpl[2] + print time.time() - start + grid = get_grid(a, b, c, d, hough, size) + grid_lines = [[l2ad(l, size) for l in grid[0]], + [l2ad(l, size) for l in grid[1]]] + + ### + + 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 + +def get_grid(a, b, c, d, hough, size): + l1 = hough.lines_from_list([a, b]) + l2 = hough.lines_from_list([c, d]) + c = intersections_from_angl_dist([l1, l2], size, get_all=True) + #TODO do something when a corner is outside the image + corners = (c[0] + c[1]) + if len(corners) < 4: + print l1, l2, c + raise GridFittingFailedError grid = g_grid(corners) return grid + +def line_out(line, size): + for p in line: + if p[0] < 0 or p[0] > size[0] or p[1] < 0 or p[1] > size[1]: + return True + else: + return False + +def distance(im_l, grid, size): + 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) + if line_out(line, size): + return 0 + #im_g = im_g.filter(MyGaussianBlur(radius=3)) + #GaussianBlur is undocumented class, may not work in future versions of PIL + #im_d, distance = combine(im_l, im_g) + distance_d = pcf.combine(im_l, im_g.tostring()) + return distance_d