X-Git-Url: http://git.tomasm.cz/imago.git/blobdiff_plain/6171054cca1b1120afad2d70a50b6efc0441a831..e6f073518dbb7ad540d5876f6326b326cdc6da13:/src/gridf3.py?ds=inline

diff --git a/src/gridf3.py b/src/gridf3.py
index 0697b92..8a1a216 100644
--- a/src/gridf3.py
+++ b/src/gridf3.py
@@ -12,6 +12,9 @@ from geometry import l2ad
 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)
@@ -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:
@@ -50,15 +57,25 @@ class Diagonal_model:
         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)
-            score += min(d, dist)
+                if p.l1 == l1 or p.l2 == l2:
+                    return float("inf"), []
+                else:
+                    l1, l2 = p.l1, p.l2
+            else: # TODO delete this or refactor
+                score += min(d, dist)
+
         return score, cons
 
 def intersection((a1, b1, c1), (a2, b2, c2)):
     delim = float(a1 * b2 - b1 * a2)
+    if delim == 0:
+        return None
     x = (b1 * c2 - c1 * b2) / delim
     y = (c1 * a2 - a1 * c2) / delim
     return x, y
@@ -125,7 +142,7 @@ def gen_corners(d1, d2):
             # TODO create an intersection?
         try:
             yield manual.lines(map(lambda p: p.to_tuple(), [c2, c1, c3, c4]))
-        except (TypeError, ZeroDivisionError):
+        except (TypeError):
             pass
             # the square was too small to fit 17 lines inside
             # TODO define SquareTooSmallError or something
@@ -157,16 +174,24 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
 
     points = [l.points for l in new_lines1]
 
-    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)
+    def dst_p(x, y):
+        x = x - size[0] / 2
+        y = y - size[1] / 2
+        return sqrt(x * x + y * y)
+
+    for n_tries in xrange(3):
+        model = Diagonal_model(points)
+        diag_lines = ransac.ransac_multi(6, points, 2, 800, model=model)
+        diag_lines = [l[0] for l in diag_lines]
+        centers = []
+        cen_lin = []
+        for i in xrange(len(diag_lines)):
+            line1 = diag_lines[i]
+            for line2 in diag_lines[i+1:]:
+                c = intersection(line1, line2)
+                if c and dst_p(*c) < min(size) / 2:
+                    cen_lin.append((line1, line2, c))
+                    centers.append(c)
 
         if show_all:
             import matplotlib.pyplot as pyplot
@@ -177,10 +202,11 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
                 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])
+            for l in diag_lines:
+                plot_line_g(l, size[0])
             pyplot.scatter(*zip(*sum(points, [])))
-            pyplot.scatter([center[0]], [center[1]], color='r')
+            if len(centers) >= 1:
+                pyplot.scatter([c[0] for c in centers], [c[1] for c in centers], color='r')
             pyplot.xlim(0, size[0])
             pyplot.ylim(0, size[1])
             pyplot.gca().invert_yaxis()
@@ -188,16 +214,29 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
             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")
+            do_something(image_p, "finding diagonals")
 
-
-        grids = list(gen_corners(diag1, diag2))
-        
-        try:
-            sc, grid = min(map(lambda g: (score(sum(g, []), data), g), grids))
+        data = sum(points, [])
+        # TODO what if lines are missing?
+        sc = float("inf")
+        grid = None
+        for (line1, line2, c) in cen_lin:
+            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))
+            
+            try:
+                new_sc, new_grid = min(map(lambda g: (score(sum(g, []), data), g), grids))
+                if new_sc < sc:
+                    sc, grid = new_sc, new_grid
+            except ValueError:
+                pass
+        if grid:
             break
-        except ValueError:
-            pass
     else:
         raise GridFittingFailedError