forked from mindspore-Ecosystem/mindspore
94 lines
3.4 KiB
Python
94 lines
3.4 KiB
Python
# 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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import mindspore.dataset as ds
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import mindspore.dataset.transforms.vision.c_transforms as vision
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from mindspore.dataset.transforms.vision import Inter
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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testCelebAData/"
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def test_celeba_dataset_label():
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data = ds.CelebADataset(DATA_DIR, decode=True, shuffle=False)
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expect_labels = [
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[0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1,
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0, 0, 1],
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[0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
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0, 0, 1]]
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count = 0
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for item in data.create_dict_iterator():
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logger.info("----------image--------")
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logger.info(item["image"])
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logger.info("----------attr--------")
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logger.info(item["attr"])
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for index in range(len(expect_labels[count])):
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assert (item["attr"][index] == expect_labels[count][index])
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count = count + 1
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assert (count == 2)
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def test_celeba_dataset_op():
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data = ds.CelebADataset(DATA_DIR, decode=True, num_shards=1, shard_id=0)
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crop_size = (80, 80)
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resize_size = (24, 24)
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# define map operations
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data = data.repeat(2)
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center_crop = vision.CenterCrop(crop_size)
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resize_op = vision.Resize(resize_size, Inter.LINEAR) # Bilinear mode
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data = data.map(input_columns=["image"], operations=center_crop)
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data = data.map(input_columns=["image"], operations=resize_op)
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count = 0
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for item in data.create_dict_iterator():
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logger.info("----------image--------")
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logger.info(item["image"])
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count = count + 1
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assert (count == 4)
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def test_celeba_dataset_ext():
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ext = [".JPEG"]
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data = ds.CelebADataset(DATA_DIR, decode=True, extensions=ext)
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expect_labels = [0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1,
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0, 1, 0, 1, 0, 0, 1],
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count = 0
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for item in data.create_dict_iterator():
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logger.info("----------image--------")
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logger.info(item["image"])
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logger.info("----------attr--------")
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logger.info(item["attr"])
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for index in range(len(expect_labels[count])):
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assert (item["attr"][index] == expect_labels[count][index])
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count = count + 1
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assert (count == 1)
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def test_celeba_dataset_distribute():
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data = ds.CelebADataset(DATA_DIR, decode=True, num_shards=2, shard_id=0)
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count = 0
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for item in data.create_dict_iterator():
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logger.info("----------image--------")
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logger.info(item["image"])
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logger.info("----------attr--------")
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logger.info(item["attr"])
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count = count + 1
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assert (count == 1)
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if __name__ == '__main__':
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test_celeba_dataset_label()
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test_celeba_dataset_op()
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test_celeba_dataset_ext()
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test_celeba_dataset_distribute()
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