offset = round(offset*img.shape[0]) # convert to pixels
dims = (img.shape[0]+offset, img.shape[1], img.shape[2])
g = m.makeCarrier(dims, T)
print 'computing gratings...'
L = 0.04 # learning rate
niter = 501 # of iterations
for i in range(niter):
if i % 25 == 0:
print "iteration [%4d/%4d]" % (i, niter)
# update grating
err = (1-img)/2 - (g[0:-offset,:,:] - g[offset:,:,:])
g[0:-offset,:,:] += L*err
g[offset:,:,:] -= L*err
g = m.smoothenPhase(g, 1e-4/T)
print 'saving image...'
g = m.makeGrating(g)
# visualize gratings
m.show(g, 312, 'grating')
# visualize superpositions
e = m.ones((offset, img.shape[1], img.shape[2]))
s = m.vstack((e, g))*m.vstack((g, e))
m.show(s, 313, 'superposition')
fig.savefig('./results/moire3.png', dpi=300)
Simple moire with a single color image
"""
import moirelib as m
T = 1./40 # grating period
print 'pre-processing images...'
img = m.prepImage('audrey', mag=2, sigma=(0,T/4., 0))
fig = m.figure(figsize=(8,10))
m.show(img, 311, 'original')
print 'generating gratings...'
carrier = m.makeCarrier(img.shape, T)
g1 = carrier-(1-img)/4
g2 = carrier+(1-img)/4
print 'smoothing phase...'
g1 = m.smoothenPhase(g1, 1e-3/T, 50)
g2 = m.smoothenPhase(g2, 1e-3/T, 50)
print 'saving images...'
g1 = m.makeGrating(g1)
g2 = m.makeGrating(g2)
m.show(g1,323, 'grating 1')
m.show(g2,324, 'grating 2')
m.show(g1*g2, 313, 'superposition')
fig.savefig('./results/moire1.png', dpi=300)
niter = 501 # of iterations
for i in range(niter):
if i % 25 == 0:
print "iteration [%4d/%4d]" % (i, niter)
# update gratings
err1 = (1 - img[0]) / 2 - (g1[:-offset, :, :] - g2[offset:, :, :])
err2 = (1 - img[1]) / 2 - (g2[:-offset, :, :] - g1[offset:, :, :])
g1[:-offset, :, :] += L * err1
g2[offset:, :, :] -= L * err1
g2[:-offset, :, :] += L * err2
g1[offset:, :, :] -= L * err2
# enforce grating smoothness by clipping the laplacian
g1 = m.smoothenPhase(g1, 1e-4 / T)
print "saving image..."
g1 = m.makeGrating(g1)
g2 = m.makeGrating(g2)
# visualize gratings
m.show(g1, 323, "grating 1")
m.show(g2, 324, "grating 2")
# visualize superpositions
e = m.ones((offset, dims[1], dims[2]))
s1 = m.vstack((e, g1)) * m.vstack((g2, e))
s2 = m.vstack((e, g2)) * m.vstack((g1, e))
m.show(s1, 325, "superposition 1")
m.show(s2, 326, "superposition 2")
"""
Simple moire with a single color image
"""
import moirelib as m
T = 1. / 40 # grating period
print 'pre-processing images...'
img = m.prepImage('audrey', mag=2, sigma=(0, T / 4., 0))
fig = m.figure(figsize=(8, 10))
m.show(img, 311, 'original')
print 'generating gratings...'
carrier = m.makeCarrier(img.shape, T)
g1 = carrier - (1 - img) / 4
g2 = carrier + (1 - img) / 4
print 'smoothing phase...'
g1 = m.smoothenPhase(g1, 1e-3 / T, 50)
g2 = m.smoothenPhase(g2, 1e-3 / T, 50)
print 'saving images...'
g1 = m.makeGrating(g1)
g2 = m.makeGrating(g2)
m.show(g1, 323, 'grating 1')
m.show(g2, 324, 'grating 2')
m.show(g1 * g2, 313, 'superposition')
fig.savefig('./results/moire1.png', dpi=300)
offset = round(offset * img.shape[0]) # convert to pixels
dims = (img.shape[0] + offset, img.shape[1], img.shape[2])
g = m.makeCarrier(dims, T)
print 'computing gratings...'
L = 0.04 # learning rate
niter = 501 # of iterations
for i in range(niter):
if i % 25 == 0:
print "iteration [%4d/%4d]" % (i, niter)
# update grating
err = (1 - img) / 2 - (g[0:-offset, :, :] - g[offset:, :, :])
g[0:-offset, :, :] += L * err
g[offset:, :, :] -= L * err
g = m.smoothenPhase(g, 1e-4 / T)
print 'saving image...'
g = m.makeGrating(g)
# visualize gratings
m.show(g, 312, 'grating')
# visualize superpositions
e = m.ones((offset, img.shape[1], img.shape[2]))
s = m.vstack((e, g)) * m.vstack((g, e))
m.show(s, 313, 'superposition')
fig.savefig('./results/moire3.png', dpi=300)
niter = 1000 # of iterations
for i in range(niter):
if i % 25 == 0:
print "iteration [%4d/%4d]" % (i, niter)
# update gratings
err1 = (1 - img[0]) / 2 - (g1[:-offset, :, :] - g2[offset:, :, :])
err2 = (1 - img[1]) / 2 - (g2[:-offset, :, :] - g1[offset:, :, :])
g1[:-offset, :, :] += L * err1
g2[offset:, :, :] -= L * err1
g2[:-offset, :, :] += L * err2
g1[offset:, :, :] -= L * err2
# enforce grating smoothness by clipping the laplacian
g1 = m.smoothenPhase(g1, 1e-4 / T)
g2 = m.smoothenPhase(g2, 1e-4 / T)
print 'saving image...'
g1 = m.makeGrating(g1)
g2 = m.makeGrating(g2)
# visualize gratings
m.saveImage(g1, combinedFilename + '-grating1', dpi)
m.saveImage(g2, combinedFilename + '-grating2', dpi)
m.show(g1, 323, 'grating 1')
m.show(g2, 324, 'grating 2')
# visualize superpositions
e = m.ones((offset, dims[1], dims[2]))
s1 = m.vstack((e, g1)) * m.vstack((g2, e))
