X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/04fed003945a46c6399db7eb94e81f2b215b87a8..601a48bd9846a6bbbb3b9931c88d1c46c1dff4b1:/gridf.py diff --git a/gridf.py b/gridf.py index 50beb81..35bbc80 100644 --- a/gridf.py +++ b/gridf.py @@ -16,7 +16,7 @@ class MyGaussianBlur(ImageFilter.Filter): def filter(self, image): return image.gaussian_blur(self.radius) -class V(): +class V(object): def __init__(self, x, y): self.x = x self.y = y @@ -30,50 +30,75 @@ class V(): def __rmul__(self, other): return V(other * self.x, other * self.y) - def t(self): - return (self.x, self.y) + def __len__(self): + return 2; + def __getitem__(self, key): + if key == 0: + return self.x + elif key == 1: + return self.y + elif type(key) != int: + raise TypeError("V indices must be integers") + else: + raise KeyError("V index ({}) out of range".format(key)) + + def __iter__(self): + yield self.x + yield self.y + + @property 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))) + return V(*intersection(g_line(point, point + vector.normal), g_line(*line))) + +def job(args): + X, Y, im_l, a, b, c, d, s, v1, 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) for y in range(0,2 * k)] -def error_surface(lines, a, b, c, d, hough, size, v1): +def error_surface(im_l, a, b, c, d, hough, size, v1): import matplotlib.pyplot as plt from matplotlib import cm + import multiprocessing import time + import sys import pickle + X = [] Y = [] Z = [] s = 0.001 - k = 200 + k = 250 for i in range(-k, k): X.append(range(-k, k)) Y.append(2*k*[i]) - + + tasks = [(X[x], Y[x], im_l, a, b, c, d, s, v1, k, hough, size) for x in xrange(0, 2 * k)] + #everything is passed by value here; can it somehow be passed by reference? + + pool = multiprocessing.Pool(None) + start = time.time() - for x in range(0, 2*k): - try: - Z.append([distance(lines, get_grid(a + X[x][y] * s * v1, b + Y[x][y] * s * v1, - c, d, hough, size), - size) for y in range(0, 2* k)]) - except Exception: - Z.append(Z[-1]) - o = ((time.time() - start) * (2 * k - (x + 1))) / (60 * (x + 1)) - print x + 1, "{0} h {1:2.2f} m".format(int(o) / 60, o % 60) + Z = pool.map(job, tasks, 1) + print time.time() - start + s_file = open('surface' + str(k), 'w') pickle.dump((X, Y, Z), s_file) s_file.close() - plt.imshow(Z, cmap=cm.gnuplot2, interpolation='bicubic', + plt.imshow(Z, cmap=cm.jet, interpolation='bicubic', origin='upper', extent=(-k, k, -k, k), aspect='equal') plt.colorbar() plt.show() + sys.exit() + 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) @@ -84,18 +109,27 @@ def find(lines, size, l1, l2, bounds, hough, do_something): 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_l.filter(MyGaussianBlur(radius=50)) + #GaussianBlur is undocumented class, may not work in future versions of PIL + im_l = im_l.tostring() + + #error_surface(im_l, a, b, c, d, hough, size, v1) + grid = get_grid(a, b, c, d, hough, size) - dist = distance(lines, grid, size) + dist = distance(im_l, grid, size) print dist - - #error_surface(lines, a, b, c, d, hough, size, v1) - + 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), + distances = [(distance(im_l, grid, size), grid, t) for grid, t in grids] distances.sort(reverse=True) if distances[0][0] > dist: @@ -115,7 +149,7 @@ def find(lines, size, l1, l2, bounds, hough, do_something): 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), + distances = [(distance(im_l, grid, size), grid, t) for grid, t in grids] distances.sort(reverse=True) if distances[0][0] > dist: @@ -132,8 +166,8 @@ def find(lines, size, l1, l2, bounds, hough, do_something): 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()]) + 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]) @@ -143,20 +177,15 @@ def get_grid(a, b, c, d, hough, size): 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 +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) #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 = pcf.combine(im_l.tostring(), im_g.tostring()) + distance = pcf.combine(im_l, im_g.tostring()) return distance def combine(bg, fg):