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53 lines
1.9 KiB
53 lines
1.9 KiB
# Copyright 2019 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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import mindspore.dataset.transforms.vision.c_transforms as vision
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import mindspore.dataset as ds
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from mindspore import log as logger
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DATA_DIR = "../data/dataset/testVOC2012"
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def test_voc_normal():
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data1 = ds.VOCDataset(DATA_DIR, decode=True)
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num = 0
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for item in data1.create_dict_iterator():
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logger.info("item[image] is {}".format(item["image"]))
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logger.info("item[image].shape is {}".format(item["image"].shape))
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logger.info("item[target] is {}".format(item["target"]))
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logger.info("item[target].shape is {}".format(item["target"].shape))
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num += 1
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logger.info("num is {}".format(str(num)))
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def test_case_0():
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data1 = ds.VOCDataset(DATA_DIR, decode=True)
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resize_op = vision.Resize((224, 224))
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data1 = data1.map(input_columns=["image"], operations=resize_op)
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data1 = data1.map(input_columns=["target"], operations=resize_op)
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repeat_num = 4
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data1 = data1.repeat(repeat_num)
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batch_size = 2
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data1 = data1.batch(batch_size, drop_remainder=True)
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num = 0
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for item in data1.create_dict_iterator():
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logger.info("item[image].shape is {}".format(item["image"].shape))
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logger.info("item[target].shape is {}".format(item["target"].shape))
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num += 1
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logger.info("num is {}".format(str(num)))
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