def animate():
while True:
line = random_middle_line()
d = DividingLine(synthetic_image(line=line))
d.traverse(line, True)
#d.traverse_np(line, True)
pylab.clf()
pylab.imshow(d.debug)
pylab.waitforbuttonpress(0.01)
def test_dividingline(self):
line = [1,1,-300]
image = synthetic_image((640,480), line)
d = DividingLine(image)
result = d.traverse(line)
assert result['p0'] + result['n0'] == image.shape[0] * image.shape[1]
assert result['p1'] + result['n1'] == image.sum()
assert result['p2'] + result['n2'] == (image.astype('i8')**2).sum()
d2 = DividingLine(image)
d2.traverse(line)
assert np.all(d2.debug == d.debug)
within_eps = lambda a, b: np.all(np.abs(a - b) < 1e-5)
assert within_eps(float(result['p1'])/result['p0'], 255)
assert within_eps(float(result['n1'])/result['n0'], 0)
def optimize(rgb, debug=False):
im = rgb.mean(2).astype('u1')
size = im.shape[::-1]
mask = table_calibration.make_mask(config.bg['boundpts'])
d = DividingLine(im, mask)
def error(x):
theta, dist = x
line = middle_offset(theta, dist, size)
s = 1./(d.score(line, debug) + 1e-5)
if debug:
clf()
imshow(d.debug * d.image)
pylab.waitforbuttonpress(0.01)
return s
for iteration in xrange(5):
initial = (np.random.rand()*2*pi, (2*np.random.rand()-1)*100)
r, score, _, _, _ = scipy.optimize.fmin(error, initial,
full_output=True, disp=False)
# This threshold is based on empirical observations. Might change.
if score < 0.02: break
else:
print 'Failed %d times' % iteration
raise ValueError
line = middle_offset(r[0], r[1], size)
line = np.array(line) / line[2]
res = d.traverse(line)
# Scale the line so that a positive dot product indicates the point is
# on the 'bright' side of the line
if res['p1'] / res['p0'] < res['n1'] / res['n0']:
line *= -1
return line
import dividingline; reload(dividingline)
from dividingline import dividingline
reload(dividingline)
from dividingline import DividingLine, synthetic_image, random_middle_line
import pylab
import scipy.optimize
line = [1,1,-300]
#im = synthetic_image((640,480), line)
im = imread('tableshot.png').mean(2)[100:,:]*255
d = DividingLine(im)
res = d.traverse(line, True)
d2 = DividingLine(im)
res2 = d2.traverse_np(line, True)
def animate():
while True:
line = random_middle_line()
d = DividingLine(synthetic_image(line=line))
d.traverse(line, True)
#d.traverse_np(line, True)
pylab.clf()
pylab.imshow(d.debug)
pylab.waitforbuttonpress(0.01)
middle_offset = dividingline.middle_offset
def optimize():
