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71 lines
2.2 KiB
71 lines
2.2 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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"""
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Testing RandomCropAndResize op in DE
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"""
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import matplotlib.pyplot as plt
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import mindspore.dataset.transforms.vision.c_transforms as vision
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from mindspore import log as logger
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import mindspore.dataset as ds
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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 visualize(a, mse, original):
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"""
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visualizes the image using DE op and Numpy op
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"""
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plt.subplot(141)
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plt.imshow(original)
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plt.title("Original image")
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plt.subplot(142)
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plt.imshow(a)
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plt.title("DE random_crop image")
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plt.subplot(143)
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plt.imshow(a - original)
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plt.title("Difference image, mse : {}".format(mse))
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plt.show()
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def test_random_crop_op():
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"""
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Test RandomCrop Op
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"""
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logger.info("test_random_crop_op")
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# First dataset
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data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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random_crop_op = vision.RandomCrop([512, 512], [200, 200, 200, 200])
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decode_op = vision.Decode()
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data1 = data1.map(input_columns=["image"], operations=decode_op)
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data1 = data1.map(input_columns=["image"], operations=random_crop_op)
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# Second dataset
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data2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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data2 = data2.map(input_columns=["image"], operations=decode_op)
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for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
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image1 = item1["image"]
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image2 = item2["image"]
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if __name__ == "__main__":
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test_random_crop_op()
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