class Hough:
"""Hough transform.
- This class stores the transformed image and metainformation.
+ This class stores the parameters of the transformation.
"""
- def __init__(self, size, dt, init_angle, image):
+ def __init__(self, size, dt, init_angle):
self.size = size # this is a tuple (width, height)
self.dt = dt # this is the angle step in hough transform
self.initial_angle = init_angle
- self.image = image
@classmethod
- def Transform(cls, image):
- """Create Hough transform of the *image* with default parameters."""
- # TODO rename to transform?
+ def default(cls, image):
+ """Default parameters for Hough transform of the *image*."""
size = image.size
dt = pi / size[1]
initial_angle = (pi / 4) + (dt / 2)
- image_s = pcf.hough(size, image.tostring(), initial_angle, dt)
- image_t = Image.fromstring('L', size, image_s)
- return cls(size, dt, initial_angle, image_t)
+ return cls(size, dt, initial_angle)
+
+ def transform(self, image):
+ image_s = pcf.hough(self.size, image.tostring(), self.initial_angle,
+ self.dt)
+ image_t = Image.fromstring('L', self.size, image_s)
+ return image_t
def apply_filter(self, filter_f):
return Hough(self.size, self.dt, self.initial_angle,
lines.append(self.angle_distance(p))
return lines
- def all_lines_h(self):
+ def all_lines_h(self, image):
# TODO what is this?
- im_l = self.image.load()
+ im_l = image.load()
lines1 = []
for x in xrange(self.size[0] / 2):
for y in xrange(self.size[1]):
im_h = prepare(image, show_all, do_something, verbose)
+
+ hough = Hough.default(im_h)
+
if verbose:
print >> sys.stderr, "hough transform"
- im_hough = Hough.Transform(im_h)
+ im_hough = hough.transform(im_h)
if show_all:
- do_something(im_hough.image, "hough transform")
+ do_something(im_hough, "hough transform")
# im_hough.image = filters.peaks(im_hough.image)
# if show_all:
# do_something(im_hough.image, "peak extraction")
- im_h2 = im_hough.apply_filter(partial(filters.high_pass, height=96))
+ im_h2 = filters.high_pass(im_hough, 96)
if show_all:
- do_something(im_h2.image, "second high pass filters")
+ do_something(im_h2, "second high pass filters")
- im_h2 = im_h2.apply_filter(filters.components2)
+ im_h2 = filters.components2(im_h2)
if show_all:
- do_something(im_h2.image, "components centers")
+ do_something(im_h2, "components centers")
if verbose:
print >> sys.stderr, "second hough transform"
# 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 = Hough.Transform(im_h2.image)
+ hough2 = Hough.default(im_h2)
+ im_hough2 = hough2.transform(im_h2)
if show_all:
- do_something(im_hough2.image, "second hough transform")
+ do_something(im_hough2, "second hough transform")
- im_h3 = im_hough2.apply_filter(partial(filters.high_pass, height=120))
+ im_h3 = filters.high_pass(im_hough2, 120)
if show_all:
- do_something(im_h3.image, "third high pass filter")
+ do_something(im_h3, "third high pass filter")
- im_h3 = im_h3.apply_filter(filters.components)
+ im_h3 = filters.components(im_h3)
if show_all:
- do_something(im_h3.image, "half centers")
+ do_something(im_h3, "half centers")
if verbose:
print >> sys.stderr, "finding the grid"
- lines_m = im_h3.all_lines_h()
+ lines_m = hough2.all_lines_h(im_h3)
lines = []
- im_c = im_h2.image.convert('RGB').convert('RGB', (1, 0.5, 0.5, 0))
+ im_c = im_h2.convert('RGB').convert('RGB', (1, 0.5, 0.5, 0))
draw_c = ImageDraw.Draw(im_c)
bounds = []
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.image, im_line):
+ 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(im_hough.lines_from_list(line_points))
+ lines.append(hough.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(image_g, "lines")
- return lines, lines_m[0][0], lines_m[1][0], bounds, im_hough
+ return lines, lines_m[0][0], lines_m[1][0], bounds, hough
def combine(image1, image2):
"""Return a list of points that are present in both images."""