error surface -- multiprocessing

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index 83a9771..35bbc80 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -3,6 +3,7 @@ import Image, ImageDraw, ImageFilter
 from manual import lines as g_grid, l2ad, intersection, line as g_line
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist
 from manual import lines as g_grid, l2ad, intersection, line as g_line
 from intrsc import intersections_from_angl_dist
 from linef import line_from_angl_dist

+import pcf

 
 class GridFittingFailedError(Exception):
     pass
 
 class GridFittingFailedError(Exception):
     pass


@@ -15,7 +16,7 @@ class MyGaussianBlur(ImageFilter.Filter):
     def filter(self, image):
         return image.gaussian_blur(self.radius)
 
     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
     def __init__(self, x, y):
         self.x = x
         self.y = y


@@ -29,17 +30,74 @@ class V():
     def __rmul__(self, other):
         return V(other * self.x, other * self.y)
 
     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):
     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(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 = 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()
+    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.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]
 
 def find(lines, size, l1, l2, bounds, hough, do_something):
     a, b, c, d = [V(*a) for a in bounds]


@@ -51,16 +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) 
     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)
     grid = get_grid(a, b, c, d, hough, size)

-    dist = distance(lines, grid, size)
+    dist = distance(im_l, grid, size)

     print dist
     print dist

-    
+   

     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]
     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:
                       grid, t) for grid, t in grids]
         distances.sort(reverse=True)
         if distances[0][0] > dist:


@@ -80,7 +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]
         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:
                       grid, t) for grid, t in grids]
         distances.sort(reverse=True)
         if distances[0][0] > dist:


@@ -97,9 +166,10 @@ def find(lines, size, l1, l2, bounds, hough, do_something):
     return grid, grid_lines
 
 def get_grid(a, b, c, d, hough, size):
     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)
     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])
     if len(corners) < 4:
         print l1, l2, c
     corners = (c[0] + c[1])
     if len(corners) < 4:
         print l1, l2, c


@@ -107,26 +177,22 @@ def get_grid(a, b, c, d, hough, size):
     grid = g_grid(corners)
     return grid
 
     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))
     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))

-    im_d, distance = combine(im_l, im_g)
+    #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, im_g.tostring())

     return distance
 
 def combine(bg, fg):
     bg_l = bg.load()
     fg_l = fg.load()
     return distance
 
 def combine(bg, fg):
     bg_l = bg.load()
     fg_l = fg.load()

-    res = Image.new('L', fg.size)
-    res_l = res.load()
+    #res = Image.new('L', fg.size)
+    #res_l = res.load()

 
     score = 0
     area = 0
 
     score = 0
     area = 0


@@ -134,8 +200,9 @@ def combine(bg, fg):
     for x in xrange(fg.size[0]):
         for y in xrange(fg.size[1]):
             if fg_l[x, y]:
     for x in xrange(fg.size[0]):
         for y in xrange(fg.size[1]):
             if fg_l[x, y]:

-                res_l[x, y] = bg_l[x, y] * fg_l[x, y]
+                #res_l[x, y] = bg_l[x, y] * fg_l[x, y]

                 score +=  bg_l[x, y]
                 area += 1
 
                 score +=  bg_l[x, y]
                 area += 1
 

-    return res, float(score)/area
+    #return res, float(score)/area
+    return None, float(score)/area