def apply_preprocessing_sim(batch):
X, Y, xyzs = batch
pp.add_norm(X)
np.random.seed(0)
pp.add_noise(X, c=0.05)
# Add background gradient
c = 0.3
angle = -np.pi / 2
x, y = np.meshgrid(np.arange(0, X[0].shape[1]),
np.arange(0, X[0].shape[2]),
indexing='ij')
n = [np.cos(angle), np.sin(angle), 1]
z = -(n[0] * x + n[1] * y)
z -= z.mean()
z /= np.ptp(z)
for x in X:
x += z[None, :, :, None] * c * np.ptp(x)
X = list(reversed(X))
Y = [Y[-1][..., i] for i in range(2)]
return X, Y, xyzs
def apply_preprocessing(batch):
X, Y, xyzs = batch
pp.add_norm(X)
np.random.seed(0)
pp.add_noise(X, c=0.05)
Y = [Y[-1][..., i] for i in range(2)]
return X, Y, xyzs
def apply_preprocessing_sim(batch):
X, Y, xyzs = batch
pp.add_norm(X)
np.random.seed(0)
pp.add_noise(X, c=0.05)
X = list(reversed(X))
# Pick slices
X[0] = X[0][..., 10:20] # CO
X[1] = X[1][..., 8:18] # Xe
Y = [Y[-1][...,i] for i in range(2)]
return X, Y, xyzs
def apply_preprocessing(self, batch):
Xs, Ys, xyz = batch
pp.add_norm(Xs, per_layer=True)
pp.add_gradient(Xs, c=0.3)
pp.add_noise(Xs, c=0.1, randomize_amplitude=False)
pp.rand_shift_xy(Xs, c=0.02)
pp.add_cutout(Xs, n_holes=5)
Ys = Ys[0]
Ys = [Ys[:,:,:,i] for i in range(Ys.shape[-1])]
Xs, Ys = pp.add_rotation_reflection(Xs, Ys, rotations=True, reflections=True,
multiple=2, crop=(128, 128))
Xs = list(reversed(Xs)) # Only for CO-Xe tip combination
return Xs, Ys