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research/cognitive_planning/preprocessing/lenet_preprocessing.py
44 строки
2 KB
Arsalan Mousavian
adding implementation of https://arxiv.org/abs/1805.06066 (#5265)
11 сен 2018, 21:03
11 сен 2018, 21:03
e6ce8cd
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# Copyright 2016 The TensorFlow 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. # ============================================================================== """Provides utilities for preprocessing.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import tensorflow as tf slim = tf.contrib.slim def preprocess_image(image, output_height, output_width, is_training): """Preprocesses the given image. Args: image: A `Tensor` representing an image of arbitrary size. output_height: The height of the image after preprocessing. output_width: The width of the image after preprocessing. is_training: `True` if we're preprocessing the image for training and `False` otherwise. Returns: A preprocessed image. """ image = tf.to_float(image) image = tf.image.resize_image_with_crop_or_pad( image, output_width, output_height) image = tf.subtract(image, 128.0) image = tf.div(image, 128.0) return image