try again in gridf3

diff --git a/src/gridf2.py b/src/gridf2.py
index 0d9246f..0988508 100644 (file)
--- a/src/gridf2.py
+++ b/src/gridf2.py
@@ -51,7 +51,7 @@ def score(grid, lines, limit):
     ds = map(dsg, grid)
     d = max(map(abs, ds))
     if d > limit:
     ds = map(dsg, grid)
     d = max(map(abs, ds))
     if d > limit:

-        return 999999
+        return float("inf")

     score = 0
     for line in lines:
         s = min(map(lambda g: abs(line[1] - g), ds))
     score = 0
     for line in lines:
         s = min(map(lambda g: abs(line[1] - g), ds))


@@ -109,9 +109,9 @@ def test():
 
     while True:
         t0 = time.time()
 
     while True:
         t0 = time.time()

-        sc1, gridv = 999999, None
-        sc2, gridh = 999999, None
-        sc1_n, sc2_n = 999999, 999999
+        sc1, gridv = float("inf"), None
+        sc2, gridh = float("inf"), None
+        sc1_n, sc2_n = float("inf"), float("inf")

         gridv_n, gridh_n = None, None
         for k in range(50):
             for i in range(5):
         gridv_n, gridh_n = None, None
         for k in range(50):
             for i in range(5):


@@ -181,7 +181,7 @@ def test():
 def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
     logger("finding the grid")
     l1, l2 = lines
 def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
     logger("finding the grid")
     l1, l2 = lines

-    sc1, gridv = 999999, None
+    sc1, gridv = float("inf"), None

     for i in range(250):
         l1s = random.sample(l1, 2)
         l1s.sort(key=lambda l: l[1])
     for i in range(250):
         l1s = random.sample(l1, 2)
         l1s.sort(key=lambda l: l[1])


@@ -194,7 +194,7 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
         if sc1_n < sc1:
             sc1, gridv = sc1_n, gridv_n
 
         if sc1_n < sc1:
             sc1, gridv = sc1_n, gridv_n
 

-    sc2, gridh = 999999, None
+    sc2, gridh = float("inf"), None

     for i in range(250):
         l2s = random.sample(l2, 2)
         l2s.sort(key=lambda l: l[1])
     for i in range(250):
         l2s = random.sample(l2, 2)
         l2s.sort(key=lambda l: l[1])

diff --git a/src/gridf3.py b/src/gridf3.py
index 0ea26d9..ac7fa2a 100644 (file)
--- a/src/gridf3.py
+++ b/src/gridf3.py
@@ -9,6 +9,9 @@ from geometry import l2ad
 
 # TODO comments, refactoring, move methods to appropriate modules
 
 
 # TODO comments, refactoring, move methods to appropriate modules
 

+class GridFittingFailedError(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(line, c, size):
     points = linef.line_from_angl_dist(line, size)
     pyplot.plot(*zip(*points), color=c)


@@ -154,43 +157,50 @@ def find(lines, size, l1, l2, bounds, hough, show_all, do_something, logger):
 
     points = [l.points for l in new_lines1]
 
 
     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)
-
-    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))
-
-    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])
     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])