81 lines
2.7 KiB
Python
81 lines
2.7 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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# ==============================================================================
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"""
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Testing ToPIL op in DE
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"""
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import mindspore.dataset as ds
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import mindspore.dataset.transforms.py_transforms
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import mindspore.dataset.vision.c_transforms as c_vision
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import mindspore.dataset.vision.py_transforms as py_vision
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from mindspore import log as logger
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from util import save_and_check_md5
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GENERATE_GOLDEN = False
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DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
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SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
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def test_to_pil_01():
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"""
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Test ToPIL Op with md5 comparison: input is already PIL image
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Expected to pass
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"""
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logger.info("test_to_pil_01")
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# Generate dataset
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data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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transforms = [
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py_vision.Decode(),
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# If input is already PIL image.
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py_vision.ToPIL(),
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py_vision.CenterCrop(375),
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py_vision.ToTensor()
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]
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transform = mindspore.dataset.transforms.py_transforms.Compose(transforms)
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data1 = data1.map(input_columns=["image"], operations=transform)
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# Compare with expected md5 from images
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filename = "to_pil_01_result.npz"
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save_and_check_md5(data1, filename, generate_golden=GENERATE_GOLDEN)
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def test_to_pil_02():
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"""
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Test ToPIL Op with md5 comparison: input is not PIL image
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Expected to pass
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"""
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logger.info("test_to_pil_02")
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# Generate dataset
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data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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decode_op = c_vision.Decode()
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transforms = [
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# If input type is not PIL.
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py_vision.ToPIL(),
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py_vision.CenterCrop(375),
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py_vision.ToTensor()
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]
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transform = mindspore.dataset.transforms.py_transforms.Compose(transforms)
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data1 = data1.map(input_columns=["image"], operations=decode_op)
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data1 = data1.map(input_columns=["image"], operations=transform)
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# Compare with expected md5 from images
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filename = "to_pil_02_result.npz"
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save_and_check_md5(data1, filename, generate_golden=GENERATE_GOLDEN)
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if __name__ == "__main__":
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test_to_pil_01()
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test_to_pil_02()
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