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random_shadow.py
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random_shadow.py
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# Copyright 2019 The FastEstimator Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
from typing import Iterable, Sequence, Tuple, Union
from albumentations.augmentations.transforms import RandomShadow as RandomShadowAlb
from fastestimator.op.numpyop.univariate.univariate import ImageOnlyAlbumentation
from fastestimator.util.base_util import warn
from fastestimator.util.traceability_util import traceable
@traceable()
class RandomShadow(ImageOnlyAlbumentation):
"""Add shadows to an image
Args:
inputs: Key(s) of images to be modified.
outputs: Key(s) into which to write the modified images.
mode: What mode(s) to execute this Op in. For example, "train", "eval", "test", or "infer". To execute
regardless of mode, pass None. To execute in all modes except for a particular one, you can pass an argument
like "!infer" or "!train".
ds_id: What dataset id(s) to execute this Op in. To execute regardless of ds_id, pass None. To execute in all
ds_ids except for a particular one, you can pass an argument like "!ds1".
shadow_roi: Region of the image where shadows will appear (x_min, y_min, x_max, y_max).
All values should be in range [0, 1].
num_shadows_lower: Lower limit for the possible number of shadows. Should be in range [0, `num_shadows_upper`].
num_shadows_upper: Lower limit for the possible number of shadows.
Should be in range [`num_shadows_lower`, inf].
shadow_dimension: Number of edges in the shadow polygons.
Image types:
uint8, float32
"""
def __init__(self,
inputs: Union[str, Sequence[str]],
outputs: Union[str, Sequence[str]],
mode: Union[None, str, Iterable[str]] = None,
ds_id: Union[None, str, Iterable[str]] = None,
shadow_roi: Tuple[float, float, float, float] = (0.0, 0.5, 1.0, 1.0),
num_shadows_lower: int = 1,
num_shadows_upper: int = 2,
shadow_dimension: int = 5):
warn("RandomShadow does not work with multi-threaded Pipelines. Either do not use this Op or else " +
"set your Pipeline num_process=0")
# TODO - Have pipeline look for bad ops and auto-magically set num_process correctly
super().__init__(
RandomShadowAlb(shadow_roi=shadow_roi,
num_shadows_lower=num_shadows_lower,
num_shadows_upper=num_shadows_upper,
shadow_dimension=shadow_dimension,
always_apply=True),
inputs=inputs,
outputs=outputs,
mode=mode,
ds_id=ds_id)