from supreme.io import imread
A = imread(sys.argv[1], flatten=True).astype(np.uint8)
Ac = imread(sys.argv[1], flatten=False).astype(np.uint8)
B = imread(sys.argv[2], flatten=True).astype(np.uint8)
Bc = imread(sys.argv[2], flatten=False).astype(np.uint8)
else:
A = chelsea(grey=True).astype(np.uint8)
Ac = A
t = 20/180. * np.pi
x = 3
y = 6
B = homography(A, [[np.cos(t), -np.sin(t), x],
[np.sin(t), np.cos(t), y],
[0, 0, 1]])
Bc = B
M, S = register.dense_MI(A, B, levels=3, std=5, win_size=9)
print "Mutual information: ", S
if S < 1.5:
print "Warning: registration probably failed."
print "Transformation matrix:"
print np.array2string(M, separator=', ')
X = register.stack.with_transform([Ac, Bc], [np.eye(3), M], save_tiff=True)
if len(sys.argv) != 3:
import matplotlib.pyplot as plt
plt.imshow(X)
plt.show()
if len(sys.argv) == 3:
from supreme.io import imread
A = imread(sys.argv[1], flatten=True).astype(np.uint8)
Ac = imread(sys.argv[1], flatten=False).astype(np.uint8)
B = imread(sys.argv[2], flatten=True).astype(np.uint8)
Bc = imread(sys.argv[2], flatten=False).astype(np.uint8)
else:
A = chelsea(grey=True).astype(np.uint8)
Ac = A
t = 20 / 180. * np.pi
x = 3
y = 6
B = homography(
A, [[np.cos(t), -np.sin(t), x], [np.sin(t), np.cos(t), y], [0, 0, 1]])
Bc = B
M, S = register.dense_MI(A, B, levels=3, std=5, win_size=9)
print "Mutual information: ", S
if S < 1.5:
print "Warning: registration probably failed."
print "Transformation matrix:"
print np.array2string(M, separator=', ')
X = register.stack.with_transform([Ac, Bc], [np.eye(3), M], save_tiff=True)
if len(sys.argv) != 3:
import matplotlib.pyplot as plt
plt.imshow(X)
plt.show()
img_dir = img_dir[0]
images = [imread(i, flatten=True).astype(np.uint8) for i in
glob(os.path.join(os.path.join(vgg, img_dir), '*.' + img_dir))]
H_dir = os.path.join(vgg, 'H')
if not os.path.isdir(H_dir):
os.mkdir(H_dir)
A = images[0]
M_0A = np.eye(3)
for i, img in enumerate(images[1:]):
print "Registering %d -> %d" % (i, i + 1)
B = images[i + 1]
M_0B, S = register.dense_MI(B, A, levels=options.levels + 1,
std=3, win_size=9,
translation_only=options.translation,
fixed_scale=options.fixed_scale)
print "Mutual information: ", S
if S > 1.5:
print "Warning: registration (%d -> %d) probably failed." % (i, i + 1)
H = '%03d.%03d.H' % (i, i + 1)
imsave(os.path.join(H_dir, H + '.png'),
register.stack.with_transform([A, B],
[np.eye(3), np.linalg.inv(M_0B)],
oshape=A.shape),
)
M_A0 = np.linalg.inv(M_0A)
M_0A = M_0B
# Transformation relative to previous frame
for i in glob(os.path.join(os.path.join(vgg, img_dir), '*.' + img_dir))
]
H_dir = os.path.join(vgg, 'H')
if not os.path.isdir(H_dir):
os.mkdir(H_dir)
A = images[0]
M_0A = np.eye(3)
for i, img in enumerate(images[1:]):
print "Registering %d -> %d" % (i, i + 1)
B = images[i + 1]
M_0B, S = register.dense_MI(B,
A,
levels=options.levels + 1,
std=3,
win_size=9,
translation_only=options.translation,
fixed_scale=options.fixed_scale)
print "Mutual information: ", S
if S > 1.5:
print "Warning: registration (%d -> %d) probably failed." % (i, i + 1)
H = '%03d.%03d.H' % (i, i + 1)
imsave(
os.path.join(H_dir, H + '.png'),
register.stack.with_transform(
[A, B], [np.eye(3), np.linalg.inv(M_0B)], oshape=A.shape),
)
M_A0 = np.linalg.inv(M_0A)
