Transfer learning on TensorFlow-Slim image classification model library
# 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.# =============================================================================="""A factory-pattern class which returns classification image/label pairs."""from __future__ import absolute_importfrom __future__ import divisionfrom __future__ import print_function#from datasets import cifar10#from datasets import flowers#from datasets import imagenet#from datasets import mnist#from datasets import visualwakewords#from datasets import facesfrom datasets import naturaldatasets_map = { 'natural': natural,}def get_dataset(name, split_name, dataset_dir, file_pattern=None, reader=None): """Given a dataset name and a split_name returns a Dataset. Args: name: String, the name of the dataset. split_name: A train/test split name. dataset_dir: The directory where the dataset files are stored. file_pattern: The file pattern to use for matching the dataset source files. reader: The subclass of tf.ReaderBase. If left as `None`, then the default reader defined by each dataset is used. Returns: A `Dataset` class. Raises: ValueError: If the dataset `name` is unknown. """ if name not in datasets_map: raise ValueError('Name of dataset unknown %s' % name) return datasets_map[name].get_split( split_name, dataset_dir, file_pattern, reader)