102 lines
3.2 KiB
Python
102 lines
3.2 KiB
Python
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# 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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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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elif isinstance(args, dict):
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cls = getattr(iaa, args['type'])
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return cls(**{
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k: self.to_tuple_if_list(v)
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for k, v in args['args'].items()
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})
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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',
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'args': {
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'p': 0.5
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}
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}, {
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'type': 'Affine',
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'args': {
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'rotate': [-10, 10]
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}
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}, {
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'type': 'Resize',
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'args': {
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'size': [0.5, 3]
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}
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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(
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keypoints, shape=img_shape)])[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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