From: Tomas Musil Date: Wed, 28 Nov 2012 23:37:24 +0000 (+0100) Subject: better error plotter X-Git-Url: http://git.tomasm.cz/imago.git/commitdiff_plain/c98a7fb2507b7ba3ee5f539bb6a7e356000a7f9c?hp=f16fe1e775f2159741146264a6494e63b0e2d618 better error plotter --- diff --git a/gridf.py b/gridf.py index d39bdd5..dcffd92 100644 --- a/gridf.py +++ b/gridf.py @@ -1,6 +1,7 @@ """Imago grid-fitting module""" import multiprocessing +import itertools import Image, ImageDraw, ImageFilter @@ -22,104 +23,98 @@ class MyGaussianBlur(ImageFilter.Filter): 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)] + im_l, v1, v2, h1, h2, x, y, dv, dh, size = args + v1 = (v1[0] + x * dv, v1[1] + x) + v2 = (v2[0] + y * dv, v2[1] + y) + return (distance(im_l, + get_grid([v1, v2], [h1, h2], size), + size), x, y) 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)] + im_l, v1, v2, h1, h2, x, y, dv, dh, size = args + h1 = (h1[0] + x * dh, h1[1] + x) + h2 = (h2[0] + y * dh, h2[1] + y) + return (distance(im_l, + get_grid([v1, v2], [h1, h2], size), + size), x, y) 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, b, c, d = [V(*a) for a in bounds] a = projection(a, l1, v1) b = projection(b, l1, v1) c = projection(c, l2, v2) d = projection(d, l2, v2) + + v1, v2 = hough.lines_from_list([a, b]) + h1, h2 = hough.lines_from_list([c, d]) + + delta_v = ((l1[1][1] - l1[0][1]) * hough.dt) / l1[1][0] + delta_h = ((l2[1][1] - l2[0][1]) * hough.dt) / l2[1][0] 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)) + im_l = im_l.filter(MyGaussianBlur(radius=5)) #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) - - 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]) + k = 30 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) + tasks = [(im_l_s, v1, v2, h1, h2, x, y, delta_v, delta_h, size) for (x, y) in + itertools.product(xrange(-k, k), xrange(-k, k))] - #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)) + opt_v = pool.map(job_br1, tasks, 8) + opt_h = pool.map(job_br2, tasks, 8) + _, x_v, y_v = max(opt_v) + _, x_h, y_h = max(opt_h) - #do_something(im_t, "lines and grid") + v1 = (v1[0] + x_v * delta_v, v1[1] + x_v) + v2 = (v2[0] + y_v * delta_v, v2[1] + y_v) + h1 = (h1[0] + x_h * delta_h, h1[1] + x_h) + h2 = (h2[0] + y_h * delta_h, h2[1] + y_h) + grid = get_grid([v1, v2], [h1, h2], size) + grid_lines = [[l2ad(l, size) for l in grid[0]], + [l2ad(l, size) for l in grid[1]]] - ### + pool.terminate() + pool.join() + +### Show error surface +# +# from gridf_analyzer import error_surface +# error_surface(k, im_l_s, v1_i, v2_i, h1_i, h2_i, +# delta_v, delta_h, x_v, y_v, x_h, y_h, size) +### + +### Show grid over lines +# +# 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]) +def get_grid(l1, l2, size): 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]) @@ -141,8 +136,8 @@ def distance(im_l, grid, 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 +# 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) diff --git a/gridf_analyzer.py b/gridf_analyzer.py index feb1e25..9ae783f 100644 --- a/gridf_analyzer.py +++ b/gridf_analyzer.py @@ -1,50 +1,45 @@ import matplotlib.pyplot as plt from matplotlib import cm -import time import sys import pickle import multiprocessing import gridf -def job1(args): - X, Y, im_l, a, b, c, d, s, v1, k, hough, size = args - return [gridf.distance(im_l, - gridf.get_grid(a + X[y] * s * v1, - b + Y[y] * s * v1, - c, d, hough, size), - size) for y in range(2 * k)] -def job2(args): - X, Y, im_l, a, b, c, d, s, v1, v2, k, hough, size = args - return [gridf.distance(im_l, - gridf.get_grid(a, b, c+ X[y] * s * v2, - d + Y[y] * s * v2, - hough, size), - size) for y in range(2 * k)] - -def error_surface(im_l, a, b, c, d, hough, size, v1, v2): +def dist1(task): + d, _, _ = gridf.job_br1(task) + return d + +def dist2(task): + d, _, _ = gridf.job_br2(task) + return d + +def error_surface(k, im_l, v1, v2, h1, h2, dv, dh, x_v, y_v, x_h, y_h, size): X = [] Y = [] - Z = [] - s = 0.001 - 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, v2, k, hough, size) for x in xrange(0, 2 * k)] + Z1 = [] + Z2 = [] pool = multiprocessing.Pool(None) - start = time.time() - Z = pool.map(job2, 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.jet, interpolation='bicubic', - origin='upper', extent=(-k, k, -k, k), aspect='equal') - plt.colorbar() + for y in xrange(-k, k): + tasks = [(im_l, v1, v2, h1, h2, x, y, dv, dh, size) for x in xrange(-k, k)] + Z1.append(pool.map(dist1, tasks, 8)) + Z2.append(pool.map(dist2, tasks, 8)) + + fig = plt.figure() + s1 = fig.add_subplot(121) + s2 = fig.add_subplot(122) + + s1.imshow(Z1, cmap=cm.jet, interpolation='bicubic', + extent=(-k, k, -k, k), aspect='equal') + s1.plot([x_v], [-y_v], 'o') + s1.set_ylim(-k, k) + s1.set_xlim(-k, k) + s2.imshow(Z2, cmap=cm.jet, interpolation='bicubic', + extent=(-k, k, -k, k), aspect='equal') + s2.plot([x_h], [-y_h], 'o') + s2.set_ylim(-k, k) + s2.set_xlim(-k, k) plt.show()