change ImagefolderDV2 name change ds.transforms.vision to ds.vision change batch api to match map api more closely compose op changes test_pylint remove compose op from vision, move to transform module, refactor map and batch to use column_orderpull/5384/head
nhussain
5 years ago
parent
75045e3e2a
commit
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# Copyright 2020 Huawei Technologies Co., Ltd
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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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"""
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General py_transforms_utils functions.
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"""
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import numpy as np
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def is_numpy(img):
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"""
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Check if the input image is Numpy format.
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Args:
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img: Image to be checked.
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Returns:
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Bool, True if input is Numpy image.
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"""
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return isinstance(img, np.ndarray)
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# Copyright 2020 Huawei Technologies Co., Ltd
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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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"""
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Built-in py_transforms_utils functions.
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"""
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import numpy as np
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from ..core.py_util_helpers import is_numpy
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def compose(img, transforms):
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"""
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Compose a list of transforms and apply on the image.
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Args:
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img (numpy.ndarray): An image in Numpy ndarray.
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transforms (list): A list of transform Class objects to be composed.
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Returns:
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img (numpy.ndarray), An augmented image in Numpy ndarray.
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"""
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if is_numpy(img):
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for transform in transforms:
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img = transform(img)
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if is_numpy(img):
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return img
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raise TypeError('img should be Numpy ndarray. Got {}. Append ToTensor() to transforms'.format(type(img)))
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raise TypeError('img should be Numpy ndarray. Got {}.'.format(type(img)))
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def one_hot_encoding(label, num_classes, epsilon):
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"""
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Apply label smoothing transformation to the input label, and make label be more smoothing and continuous.
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Args:
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label (numpy.ndarray): label to be applied label smoothing.
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num_classes (int): Num class of object in dataset, value should over 0.
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epsilon (float): The adjustable Hyper parameter. Default is 0.0.
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Returns:
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img (numpy.ndarray), label after being one hot encoded and done label smoothed.
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"""
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if label > num_classes:
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raise ValueError('the num_classes is smaller than the category number.')
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num_elements = label.size
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one_hot_label = np.zeros((num_elements, num_classes), dtype=int)
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if isinstance(label, list) is False:
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label = [label]
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for index in range(num_elements):
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one_hot_label[index, label[index]] = 1
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return (1 - epsilon) * one_hot_label + epsilon / num_classes
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