def random_transform(self, x, y):
translation,rotation,scale,transform_matrix_raw= dv.generate_random_transform(
self.augmentation_params, x.shape[:-1]
)
transform_matrix = dv.transform_full_matrix_offset_center(
transform_matrix_raw, x.shape[:-1]
)
x = dv.apply_affine_transform_channelwise(
x,
transform_matrix[:-1, :],
channel_index=self.augmentation_params.img_channel_index,
fill_mode=self.augmentation_params.fill_mode,
cval=self.augmentation_params.cval,
)
# For y, mask data, fill mode constant, cval = 0
y = dv.apply_affine_transform_channelwise(
y,
transform_matrix[:-1, :],
channel_index=self.augmentation_params.img_channel_index,
fill_mode=self.augmentation_params.fill_mode,
cval=self.augmentation_params.cval,
)
return x, y,translation,rotation,scale,transform_matrix
def test_random_transform_3d():
a = np.sin(np.linspace(0, np.pi * 5, 256))
b = np.cos(np.linspace(0, np.pi * 5, 256))
img = np.outer(a, b)[..., np.newaxis] * a
x = dv.AugmentationParameters(
image_dimension=3,
translation_range=0.15,
rotation_range=45,
scale_range=0.15,
flip=False,
fill_mode="constant",
cval=0.0,
)
txf = dv.generate_random_transform(x, img.shape)
txf = dv.transform_full_matrix_offset_center(txf, img.shape)
nb.viewers.OrthoSlicer3D(dv.apply_affine_transform(img,
txf[:-1, :])).show()
def test_random_transform_2d():
img = face()
x = dv.AugmentationParameters(
image_dimension=2,
translation_range=0.1,
rotation_range=15,
scale_range=0.1,
flip=False,
fill_mode="constant",
cval=0.0,
)
txf = dv.generate_random_transform(x, img.shape)
txf = dv.transform_full_matrix_offset_center(txf, img.shape[:-1])
plt.imshow(
dv.apply_affine_transform_channelwise(img,
txf[:-1, :],
channel_index=2))
plt.show()