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use ransac in linef
[imago.git] / imago_pack / linef.py
diff --git a/imago_pack/linef.py b/imago_pack/linef.py
index 4e35781..2e40fca 100644 (file)
--- a/imago_pack/linef.py
+++ b/imago_pack/linef.py
@@ -1,5 +1,6 @@
-"""Go image recognition lines-finding module"""
+"""Lines finding module."""
 
 
+from functools import partial
 import sys
 from math import sin, cos, pi
 
 import sys
 from math import sin, cos, pi
 
@@ -11,107 +12,98 @@ except ImportError, msg:
 
 import filters
 from hough import Hough
 
 import filters
 from hough import Hough
+import ransac
 
 
-def find_lines(image, show_all, do_something, verbose):
-
-    if verbose:
-        print >> sys.stderr, "preprocessing"
-
-    if show_all:
-        do_something(image, "original image")
-
+def prepare(image, show_image, logger):
+    # TODO comment
     im_l = image.convert('L')
     im_l = image.convert('L')
-    if show_all:
-        do_something(im_l, "ITU-R 601-2 luma transform")
-
-    if verbose:
-        print >> sys.stderr, "edge detection"
+    show_image(im_l, "ITU-R 601-2 luma transform")
 
 
+    logger("edge detection")
     im_edges = filters.edge_detection(im_l)
     im_edges = filters.edge_detection(im_l)
-    if show_all:    
-        do_something(im_edges, "edge detection")
+    show_image(im_edges, "edge detection")
 
     im_h = filters.high_pass(im_edges, 100)
 
     im_h = filters.high_pass(im_edges, 100)
-    if show_all:
-        do_something(im_h, "high pass filters")
-    
-    if verbose:
-        print >> sys.stderr, "hough transform"
+    show_image(im_h, "high pass filters")
 
 
-    hough1 = Hough(im_h.size)
-    im_hough = hough1.transform(im_h)
-    if show_all:
-        do_something(im_hough, "hough transform")
+    return im_h
+ 
+def transform(image, hough, show_image):
+    # TODO comment
+    im_hough = hough.transform(image)
+    show_image(im_hough, "hough transform")
 
 
-   # im_hough = filters.peaks(im_hough)
-   # if show_all:
-   #     do_something(im_hough, "peak extraction")
+   # im_hough.image = filters.peaks(im_hough.image)
+   # show_image(im_hough.image, "peak extraction")
                
     im_h2 = filters.high_pass(im_hough, 96)
                
     im_h2 = filters.high_pass(im_hough, 96)
-    if show_all:
-        do_something(im_h2, "second high pass filters")
-
-    im_h2 = filters.components2(im_h2)
-    if show_all:
-        do_something(im_h2, "components centers")
-
-    if verbose:
-        print >> sys.stderr, "second hough transform"
-
-    hough2 = Hough(im_h2.size) 
-    # im_hough might be used instead im_h2, but at the moment it brings a lot of
-    # noise to the second transform, which later confuses the center-finding
-    # mechanism (which is not very robust yet)
-    im_hough2 = hough2.transform(im_h2)
-    if show_all:
-        do_something(im_hough2, "second hough transform")
-
-    im_h3 = filters.high_pass(im_hough2, 120)
-    if show_all:
-        do_something(im_h3, "third high pass filter")
-     
-    im_h3 = filters.components(im_h3)
-    if show_all:
-        do_something(im_h3, "half centers")
-
-    if verbose:
-        print >> sys.stderr, "finding the grid"
-
-    lines_m = hough2.all_lines_h(im_h3)
-    lines = []
-    im_c = im_h2.convert('RGB').convert('RGB', (1, 0.5, 0.5, 0))
-    draw_c = ImageDraw.Draw(im_c)
-    bounds = []
-
-    for line_l in lines_m:
-        im_line = Image.new('L', im_h2.size)
-        draw = ImageDraw.Draw(im_line)
-        line_points = set()
-        for line in line_l:
-            draw.line(line_from_angl_dist(line, im_h2.size), fill=255, width=7)
-            draw_c.line(line_from_angl_dist(line, im_c.size), fill=(70, 70, 70), width=7)
-            for p in combine(im_h2, im_line):
-                line_points.add(p)
-        for point in line_points:
-            draw_c.point(point, fill=(120, 255, 120))
-        lines.append(hough1.lines_from_list(line_points))
-        line_points = list(line_points)
-        line_points.sort()
-        bounds += [line_points[0], line_points[-1]]
-
-    if show_all:
-        do_something(im_c, "hough x lines")
+    show_image(im_h2, "second high pass filters")
+
+    im_h2 = filters.components(im_h2, 2)
+    show_image(im_h2, "components centers")
+
+    return im_h2
+
+def run_ransac(image):
+    # TODO comment
+    # TODO vizualize this
+    image_l = image.load()
+    width, height = image.size
+
+    data = []
+
+    for y in xrange(0, height):
+        for x in xrange(0, width):
+            if image_l[x, y] > 128:
+                data.append((x, y))
+
+    dist = 3 
+    (line, points), (line2, points2) = ransac.ransac_duo(data, dist, 75, 15)
+    line_to_points = lambda (a, b, c), x: (x, (a*x + c) / (- b))
+    # TODO width should not be here vvv
+    # TODO refactor gridf to use standard equations instead of points
+    line = [line_to_points(line, 0), line_to_points(line, width - 1)]
+    line2 = [line_to_points(line2, 0), line_to_points(line2, width - 1)]
+    return [sorted(points), sorted(points2)], line, line2
+
 
 
+
+def find_lines(image, show_image, logger):
+    """Find lines in the *image*."""
+    # TODO refactor into smaller functions
+    
+    logger("preprocessing")
+    show_image(image, "original image")
+
+    im_h = prepare(image, show_image, logger)
+
+    hough = Hough.default(im_h)
+
+    logger("hough transform")
+    
+    im_h2 = transform(im_h, hough, show_image)
+
+    logger("finding the lines")
+
+    r_lines, l1, l2 = run_ransac(im_h2) 
+
+    lines = map(hough.lines_from_list, r_lines)
+
+    # TODO refactor gridf to get rid of this:
+    bounds = sum(map(lambda l: [l[0], l[-1]], r_lines), []) 
+    # sum(list, []) = flatten list
+
+    # TODO do this only if show_all is true:
     image_g = image.copy()
     draw = ImageDraw.Draw(image_g)
     for line in [l for s in lines for l in s]:
         draw.line(line_from_angl_dist(line, image.size), fill=(120, 255, 120))
     image_g = image.copy()
     draw = ImageDraw.Draw(image_g)
     for line in [l for s in lines for l in s]:
         draw.line(line_from_angl_dist(line, image.size), fill=(120, 255, 120))
-    if show_all:
-        do_something(image_g, "lines")
-   
-    return lines, lines_m[0][0], lines_m[1][0], bounds, hough1, im_h
+    show_image(image_g, "lines")
+
+    return lines, l1, l2, bounds, hough # TODO
 
 def combine(image1, image2):
 
 def combine(image1, image2):
+    """Return a list of points that are present in both images."""
     im_l1 = image1.load()
     im_l2 = image2.load()
 
     im_l1 = image1.load()
     im_l2 = image2.load()
 
@@ -124,6 +116,8 @@ def combine(image1, image2):
     return on_both
 
 def line_from_angl_dist((angle, distance), size):
     return on_both
 
 def line_from_angl_dist((angle, distance), size):
+    """Take *angle* and *distance* (from the center of the image) of a line and
+    size of the image. Return the line represented by two points."""
     if pi / 4 < angle < 3 * pi / 4:
         y1 = - size[1] / 2
         x1 = int(round((y1 * cos(angle) + distance) / sin(angle))) + size[0] / 2
     if pi / 4 < angle < 3 * pi / 4:
         y1 = - size[1] / 2
         x1 = int(round((y1 * cos(angle) + distance) / sin(angle))) + size[0] / 2
Go image recognition