import numpy from gbp import GBP # Setup a chain... print 'Whole chain...' solver = GBP(5) solver.unary(0, 0.0, 15.0) solver.unary(4, 10.0, 15.0) solver.pairwise(slice(None, -1), slice(1, None), 0.5, 1.0) iters = solver.solve_bp() print 'iters =', iters mean, prec = solver.result() print 'Mean: ' + ' '.join(['%.2f' % v for v in mean]) print 'Precison: ' + ' '.join(['%.2f' % v for v in prec]) print # Disable middle and resolve... print 'Middle gone...' solver.disable(2) iters = solver.solve_bp() print 'iters =', iters mean, prec = solver.result() print 'Mean: ' + ' '.join(['%.2f' % v for v in mean])
from gbp import GBP # Setup a chain... print 'Whole chain...' solver = GBP(5) solver.unary(0, 0.0, 15.0) solver.unary(4, 10.0, 15.0) solver.pairwise(slice(None,-1), slice(1, None), 0.5, 1.0) iters = solver.solve_bp() print 'iters =', iters mean, prec = solver.result() print 'Mean: ' + ' '.join(['%.2f'%v for v in mean]) print 'Precison: ' + ' '.join(['%.2f'%v for v in prec]) print # Disable middle and resolve... print 'Middle gone...' solver.disable(2) iters = solver.solve_bp() print 'iters =', iters mean, prec = solver.result()
print 'Single Pivot:' solver = GBP(25) #5x5 solver.unary(12, 5.0, 4.0) for row in xrange(5): solver.pairwise(slice(row*5,(row+1)*5-1), slice(row*5+1,(row+1)*5), 1.0, 1.0) for col in xrange(5): solver.pairwise(slice(col,col+20,5), slice(col+5,col+25,5), 1.0, 1.0) iters = solver.solve() print 'iters =', iters for row in xrange(5): mean, prec = solver.result(slice(row*5, (row+1)*5)) print ' '.join(['%.4f'%v for v in mean]) print ' '.join(['(%.2f)'%v for v in prec]) print # Grid 2... print 'Stretch:' solver = GBP(25) #5x5 solver.unary(0, 0.0, 5.0) solver.unary(4, 9.0, 5.0) solver.unary(20, 9.0, 5.0) solver.unary(24, 0.0, 5.0)
solver.unary(12, 5.0, 4.0)
for row in xrange(5):
solver.pairwise(slice(row * 5, (row + 1) * 5 - 1),
slice(row * 5 + 1, (row + 1) * 5), 1.0, 1.0)
for col in xrange(5):
solver.pairwise(slice(col, col + 20, 5), slice(col + 5, col + 25, 5), 1.0,
1.0)
iters = solver.solve()
print 'iters =', iters
for row in xrange(5):
mean, prec = solver.result(slice(row * 5, (row + 1) * 5))
print ' '.join(['%.4f' % v for v in mean])
print ' '.join(['(%.2f)' % v for v in prec])
print
# Grid 2...
print 'Stretch:'
solver = GBP(25) #5x5
solver.unary(0, 0.0, 5.0)
solver.unary(4, 9.0, 5.0)
solver.unary(20, 9.0, 5.0)
solver.unary(24, 0.0, 5.0)
for row in xrange(5):
iters = 0
start = time.clock()
while True:
it = solver.solve_trws(args.report, args.epsilon)
iters += it
print(' %i iters, delta = %f (target = %f)' %
(iters, solver.last_delta, args.epsilon))
if it != args.report:
break
end = time.clock()
print('...solved in %.1f seconds' % (end - start))
# Convert back to a normal field...
height, _ = solver.result()
height = height.reshape((image.shape[0], image.shape[1]))
grad_x = height.copy()
grad_x[:, 0] = height[:, 1] - height[:, 0]
grad_x[:, 1:-1] = 0.5 * (height[:, 2:] - height[:, :-2])
grad_x[:, -1] = height[:, -1] - height[:, -2]
grad_x *= -1.0
grad_y = height.copy()
grad_y[0, :] = height[1, :] - height[0, :]
grad_y[1:-1, :] = 0.5 * (height[2:, :] - height[:-2, :])
grad_y[-1, :] = height[-1, :] - height[-2, :]
norm = numpy.concatenate(
(grad_x[:, :, numpy.newaxis], grad_y[:, :, numpy.newaxis],
start = time.clock()
while True:
it = solver.solve_trws(args.report, args.epsilon)
iters += it
print(' %i iters, delta = %f (target = %f)' % (iters, solver.last_delta, args.epsilon))
if it!=args.report:
break
end = time.clock()
print('...solved in %.1f seconds' % (end - start))
# Convert back to a normal field...
height, _ = solver.result()
height = height.reshape((image.shape[0], image.shape[1]))
grad_x = height.copy()
grad_x[:,0] = height[:,1] - height[:,0]
grad_x[:,1:-1] = 0.5 * (height[:,2:] - height[:,:-2])
grad_x[:,-1] = height[:,-1] - height[:,-2]
grad_x *= -1.0
grad_y = height.copy()
grad_y[0,:] = height[1,:] - height[0,:]
grad_y[1:-1,:] = 0.5 * (height[2:,:] - height[:-2,:])
grad_y[-1,:] = height[-1,:] - height[-2,:]
norm = numpy.concatenate((grad_x[:,:,numpy.newaxis], grad_y[:,:,numpy.newaxis], numpy.ones((height.shape[0], height.shape[1], 1), dtype=numpy.float32)), axis=2)