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93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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This code is refer from:
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https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/iaa_augment.py
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import numpy as np
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import imgaug
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import imgaug.augmenters as iaa
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class AugmenterBuilder(object):
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def __init__(self):
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pass
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def build(self, args, root=True):
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if args is None or len(args) == 0:
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return None
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elif isinstance(args, list):
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if root:
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sequence = [self.build(value, root=False) for value in args]
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return iaa.Sequential(sequence)
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else:
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return getattr(iaa, args[0])(
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*[self.to_tuple_if_list(a) for a in args[1:]]
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)
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elif isinstance(args, dict):
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cls = getattr(iaa, args["type"])
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return cls(**{k: self.to_tuple_if_list(v) for k, v in args["args"].items()})
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else:
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raise RuntimeError("unknown augmenter arg: " + str(args))
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def to_tuple_if_list(self, obj):
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if isinstance(obj, list):
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return tuple(obj)
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return obj
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class IaaAugment:
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def __init__(self, augmenter_args=None, **kwargs):
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if augmenter_args is None:
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augmenter_args = [
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{"type": "Fliplr", "args": {"p": 0.5}},
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{"type": "Affine", "args": {"rotate": [-10, 10]}},
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{"type": "Resize", "args": {"size": [0.5, 3]}},
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]
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self.augmenter = AugmenterBuilder().build(augmenter_args)
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def __call__(self, data):
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image = data["image"]
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shape = image.shape
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if self.augmenter:
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aug = self.augmenter.to_deterministic()
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data["image"] = aug.augment_image(image)
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data = self.may_augment_annotation(aug, data, shape)
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return data
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def may_augment_annotation(self, aug, data, shape):
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if aug is None:
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return data
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line_polys = []
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for poly in data["polys"]:
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new_poly = self.may_augment_poly(aug, shape, poly)
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line_polys.append(new_poly)
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data["polys"] = np.array(line_polys)
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return data
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def may_augment_poly(self, aug, img_shape, poly):
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keypoints = [imgaug.Keypoint(p[0], p[1]) for p in poly]
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keypoints = aug.augment_keypoints(
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[imgaug.KeypointsOnImage(keypoints, shape=img_shape)]
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)[0].keypoints
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poly = [(p.x, p.y) for p in keypoints]
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return poly
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