def apply_transform(
input_path,
transform_name,
output_path,
kwargs,
seed,
):
"""Apply transform to an image.
\b
Example:
$ torchio-transform -k "degrees=(-5,15) num_transforms=3" input.nrrd RandomMotion output.nii
"""
# Imports are placed here so that the tool loads faster if not being run
import torchio.transforms as transforms
from torchio.transforms.augmentation import RandomTransform
from torchio.utils import apply_transform_to_file
try:
transform_class = getattr(transforms, transform_name)
except AttributeError as error:
message = f'Transform "{transform_name}" not found in torchio'
raise ValueError(message) from error
params_dict = get_params_dict_from_kwargs(kwargs)
if issubclass(transform_class, RandomTransform):
params_dict['seed'] = seed
transform = transform_class(**params_dict)
apply_transform_to_file(
input_path,
transform,
output_path,
)
return 0
def apply_transform(input_path, transform_name, output_path, kwargs, seed,
verbose):
"""Apply transform to an image.
\b
Example:
$ torchio-transform input.nrrd RandomMotion output.nii --kwargs "proportion_to_augment=1 num_transforms=3"
"""
import torchio.transforms as transforms
from torchio.transforms.augmentation import RandomTransform
from torchio.utils import apply_transform_to_file, guess_type
try:
transform_class = getattr(transforms, transform_name)
except AttributeError:
raise AttributeError(f'"{transform_name}" class not found in torchio')
params_dict = {}
if kwargs is not None:
for substring in kwargs.split():
key, value_string = substring.split('=')
value = guess_type(value_string)
params_dict[key] = value
debug_kwargs = dict(verbose=verbose)
if isinstance(transform_class, RandomTransform):
debug_kwargs['seed'] = seed
params_dict.update(debug_kwargs)
transform = transform_class(**params_dict)
apply_transform_to_file(
input_path,
transform,
output_path,
)
return 0
def test_apply_transform_to_file(self):
transform = RandomFlip()
apply_transform_to_file(
self.get_image_path('input'),
transform,
self.get_image_path('output'),
verbose=True,
)
def apply_transform(
input_path,
transform_name,
output_path,
kwargs,
seed,
):
"""Apply transform to an image.
\b
Example:
$ torchio-transform -k "degrees=(-5,15) num_transforms=3" input.nrrd RandomMotion output.nii
"""
import torchio.transforms as transforms
from torchio.transforms.augmentation import RandomTransform
from torchio.utils import apply_transform_to_file, guess_type
try:
transform_class = getattr(transforms, transform_name)
except AttributeError as error:
message = f'Transform "{transform_name}" not found in torchio'
raise ValueError(message) from error
params_dict = {}
if kwargs is not None:
for substring in kwargs.split():
try:
key, value_string = substring.split('=')
except ValueError as error:
message = f'Arguments string "{kwargs}" not valid'
raise ValueError(message) from error
value = guess_type(value_string)
params_dict[key] = value
if issubclass(transform_class, RandomTransform):
params_dict['seed'] = seed
transform = transform_class(**params_dict)
apply_transform_to_file(
input_path,
transform,
output_path,
)
return 0
def main(
input_path,
transform_name,
output_path,
kwargs,
imclass,
seed,
verbose,
):
"""Apply transform to an image.
\b
Example:
$ torchio-transform -k "degrees=(-5,15) num_transforms=3" input.nrrd RandomMotion output.nii
""" # noqa: E501
# Imports are placed here so that the tool loads faster if not being run
import torch
import torchio.transforms as transforms
from torchio.utils import apply_transform_to_file
try:
transform_class = getattr(transforms, transform_name)
except AttributeError as error:
message = f'Transform "{transform_name}" not found in torchio'
raise ValueError(message) from error
params_dict = get_params_dict_from_kwargs(kwargs)
transform = transform_class(**params_dict)
if seed is not None:
torch.manual_seed(seed)
apply_transform_to_file(
input_path,
transform,
output_path,
verbose=verbose,
class_=imclass,
)
return 0
