color distribution plot

[imago.git] / gridf.py

diff --git a/gridf.py b/gridf.py
index c8f4b90..03e3014 100644 (file)
--- a/gridf.py
+++ b/gridf.py
@@ -1,8 +1,131 @@
-from manual import lines as g_grid, l2ad
+"""Imago grid-fitting module"""
+
+import multiprocessing
+from functools import partial
+
+import Image, ImageDraw, ImageFilter
+
+from geometry import V, projection, l2ad
+from manual import lines as g_grid

 from intrsc import intersections_from_angl_dist
 from intrsc import intersections_from_angl_dist

+from linef import line_from_angl_dist
+import pcf
+import cs as Optimizer
+
+class GridFittingFailedError(Exception):
+    pass
+
+class MyGaussianBlur(ImageFilter.Filter):
+    name = "GaussianBlur"
+
+    def __init__(self, radius=2):
+        self.radius = radius
+    def filter(self, image):
+        return image.gaussian_blur(self.radius)
+
+def job_4(x, y, w, z, im_l, v1, v2, h1, h2, dv, dh, size):
+    v1 = (v1[0] + x * dv, v1[1] + x)
+    v2 = (v2[0] + y * dv, v2[1] + y)
+    h1 = (h1[0] + w * dh, h1[1] + w)
+    h2 = (h2[0] + z * dh, h2[1] + z)
+    return (distance(im_l, get_grid([v1, v2], [h1, h2], size), size))
+
+def find(lines, size, l1, l2, bounds, hough, do_something, im_h):
+    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_l.filter(MyGaussianBlur(radius=3))
+    #GaussianBlur is undocumented class, may not work in future versions of PIL
+    im_l_s = im_l.tostring()

 
 

-def find(lines, size, l1, l2):
-    c = intersections_from_angl_dist(lines, size)
-    corners = [c[0][0], c[0][-1], c[-1][0], c[-1][-1]]
+    import time
+    start = time.time()
+
+    f_dist = partial(job_4, im_l=im_l_s, v1=v1, v2=v2, h1=h1, h2=h2,
+                     dv=delta_v, dh=delta_h, size=size)
+
+    x_v, y_v, x_h, y_h = Optimizer.optimize(4, 30, f_dist, 128, 256)
+
+    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]]]
+    
+    print time.time() - start
+    
+### 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(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])
+    if len(corners) < 4:
+        print l1, l2, c
+        raise GridFittingFailedError

     grid = g_grid(corners)
     return grid
     grid = g_grid(corners)
     return grid

+
+def line_out(line, size):
+    for p in line:
+        if p[0] < 0 or p[0] > size[0] or p[1] < 0 or p[1] > size[1]:
+            return True
+    else:
+        return False
+
+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)
+        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)
+    distance_d = pcf.combine(im_l, im_g.tostring())
+    return distance_d