X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/7a92cb7d12234e559c0ec6f5e3e393f8350ef727..b92613882c83f64e0c513af1facc262fb4915e54:/src/gridf3.py diff --git a/src/gridf3.py b/src/gridf3.py index 34e2315..693b8ee 100644 --- a/src/gridf3.py +++ b/src/gridf3.py @@ -9,13 +9,16 @@ from geometry import l2ad # TODO comments, refactoring, move methods to appropriate modules -def plot_line(line, c): - points = linef.line_from_angl_dist(line, (520, 390)) +class GridFittingFailedError(Exception): + pass + +class BadGenError(Exception): + pass + +def plot_line(line, c, size): + points = linef.line_from_angl_dist(line, size) pyplot.plot(*zip(*points), color=c) -def plot_line_g((a, b, c), max_x): - find_y = lambda x: - (c + a * x) / b - pyplot.plot([0, max_x], [find_y(0), find_y(max_x)], color='b') class Diagonal_model: def __init__(self, data): @@ -32,12 +35,16 @@ class Diagonal_model: if l1[i] and l2[j]: yield (l1[i], l2[j]) + def remove(self, data): + self.data = list(set(self.data) - set(data)) + def initial(self): try: - return self.gen.next() + nxt = self.gen.next() except StopIteration: self.gen = self.initial_g() - return self.gen.next() + nxt = self.gen.next() + return nxt def get(self, sample): if len(sample) == 2: @@ -45,6 +52,25 @@ class Diagonal_model: else: return ransac.least_squares(sample) + def score(self, est, dist): + cons = [] + score = 0 + a, b, c = est + dst = lambda (x, y): abs(a * x + b * y + c) / sqrt(a*a+b*b) + l1 = None + l2 = None + for p in self.data: + d = dst(p) + if d <= dist: + cons.append(p) + if p.l1 == l1 or p.l2 == l2: + return float("inf"), [] + else: + l1, l2 = p.l1, p.l2 + score += min(d, dist) + + return score, cons + def intersection((a1, b1, c1), (a2, b2, c2)): delim = float(a1 * b2 - b1 * a2) x = (b1 * c2 - c1 * b2) / delim @@ -103,12 +129,17 @@ def gen_corners(d1, d2): if c1 in d2.points: continue pass - c2 = [p for p in d2.points if p in c1.l1.points][0] - c3 = [p for p in d1.points if p in c2.l2.points][0] - c4 = [p for p in d2.points if p in c3.l1.points][0] + try: + c2 = [p for p in d2.points if p in c1.l1.points][0] + c3 = [p for p in d1.points if p in c2.l2.points][0] + c4 = [p for p in d2.points if p in c3.l1.points][0] + except IndexError: + continue + # there is not a corresponding intersection + # TODO create an intersection? try: yield manual.lines(map(lambda p: p.to_tuple(), [c2, c1, c3, c4])) - except TypeError: + except (TypeError, ZeroDivisionError): pass # the square was too small to fit 17 lines inside # TODO define SquareTooSmallError or something @@ -140,20 +171,50 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger): points = [l.points for l in new_lines1] - line1, cons = ransac.estimate(points, 2, 800, Diagonal_model) - points2 = map(lambda l: [(p if not p in cons else None) for p in l], points) - line2, cons2 = ransac.estimate(points2, 2, 800, Diagonal_model) - 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) - - grids = list(gen_corners(diag1, diag2)) - - sc, grid = min(map(lambda g: (score(sum(g, []), data), g), grids)) - + for trial in xrange(3): + line1, cons = ransac.estimate(points, 2, 800, Diagonal_model) + points2 = map(lambda l: [(p if not p in cons else None) for p in l], points) + line2, cons2 = ransac.estimate(points2, 2, 800, Diagonal_model) + 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) + + if show_all: + import matplotlib.pyplot as pyplot + import Image + + def plot_line_g((a, b, c), max_x): + find_y = lambda x: - (c + a * x) / b + 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]) + pyplot.scatter(*zip(*sum(points, []))) + pyplot.scatter([center[0]], [center[1]], color='r') + pyplot.xlim(0, size[0]) + pyplot.ylim(0, size[1]) + pyplot.gca().invert_yaxis() + fig.canvas.draw() + 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") + + + grids = list(gen_corners(diag1, diag2)) + + try: + sc, grid = min(map(lambda g: (score(sum(g, []), data), g), grids)) + break + except ValueError: + pass + else: + raise GridFittingFailedError + grid_lines = [[l2ad(l, size) for l in grid[0]], [l2ad(l, size) for l in grid[1]]] grid_lines[0].sort(key=lambda l: l[1]) @@ -163,52 +224,3 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger): return grid, grid_lines -def test(): - import pickle - import matplotlib.pyplot as pyplot - - lines = pickle.load(open('lines.pickle')) - - size = (520, 390) - new_lines1 = map(lambda l: Line.from_ad(l, size), lines[0]) - new_lines2 = map(lambda l: Line.from_ad(l, size), lines[1]) - for l1 in new_lines1: - for l2 in new_lines2: - p = Point(intersection(l1, l2)) - p.l1 = l1 - p.l2 = l2 - l1.points.append(p) - l2.points.append(p) - - points = [l.points for l in new_lines1] - - line1, cons = ransac.estimate(points, 2, 800, Diagonal_model) - points2 = map(lambda l: [(p if not p in cons else None) for p in l], points) - line2, cons2 = ransac.estimate(points2, 2, 800, Diagonal_model) - 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) - - plot_line_g(diag1, 520) - plot_line_g(diag2, 520) - pyplot.scatter(*zip(*sum(points, []))) - pyplot.scatter([center[0]], [center[1]], color='r') - pyplot.xlim(0, 520) - pyplot.ylim(0, 390) - pyplot.show() - - grids = map(manual.lines, list(gen_corners(diag1, diag2))) - plot_grid = lambda g: map(lambda l: pyplot.plot(*zip(*l), color='g'), sum(g, [])) - map(plot_grid, grids) - pyplot.show() - - sc, grid = min(map(lambda g: (score(sum(g, []), data), g), grids)) - - map(lambda l: pyplot.plot(*zip(*l), color='g'), sum(grid, [])) - pyplot.scatter(*zip(*sum(points, []))) - pyplot.xlim(0, 520) - pyplot.ylim(0, 390) - pyplot.show()