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126 lines
5.0 KiB
126 lines
5.0 KiB
# 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 soft dvpp SoftDvppDecodeResizeJpeg and SoftDvppDecodeRandomCropResizeJpeg in DE
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"""
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import mindspore.dataset as ds
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import mindspore.dataset.vision.c_transforms as vision
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from mindspore import log as logger
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from util import diff_mse, visualize_image
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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_soft_dvpp_decode_resize_jpeg(plot=False):
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"""
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Test SoftDvppDecodeResizeJpeg op
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"""
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logger.info("test_random_decode_resize_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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decode_op = vision.Decode()
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resize_op = vision.Resize((256, 512))
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data1 = data1.map(operations=[decode_op, resize_op], input_columns=["image"])
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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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soft_dvpp_decode_resize_op = vision.SoftDvppDecodeResizeJpeg((256, 512))
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data2 = data2.map(operations=soft_dvpp_decode_resize_op, input_columns=["image"])
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
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data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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if num_iter > 0:
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break
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image1 = item1["image"]
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image2 = item2["image"]
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mse = diff_mse(image1, image2)
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assert mse <= 0.02
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logger.info("random_crop_decode_resize_op_{}, mse: {}".format(num_iter + 1, mse))
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if plot:
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visualize_image(image1, image2, mse)
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num_iter += 1
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def test_soft_dvpp_decode_random_crop_resize_jpeg(plot=False):
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"""
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Test SoftDvppDecodeRandomCropResizeJpeg op
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"""
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logger.info("test_random_decode_resize_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_decode_resize_op = vision.RandomCropDecodeResize((256, 512), (1, 1), (0.5, 0.5))
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data1 = data1.map(operations=random_crop_decode_resize_op, input_columns=["image"])
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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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soft_dvpp_random_crop_decode_resize_op = vision.SoftDvppDecodeRandomCropResizeJpeg((256, 512), (1, 1), (0.5, 0.5))
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data2 = data2.map(operations=soft_dvpp_random_crop_decode_resize_op, input_columns=["image"])
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
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data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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if num_iter > 0:
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break
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image1 = item1["image"]
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image2 = item2["image"]
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mse = diff_mse(image1, image2)
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assert mse <= 0.06
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logger.info("random_crop_decode_resize_op_{}, mse: {}".format(num_iter + 1, mse))
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if plot:
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visualize_image(image1, image2, mse)
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num_iter += 1
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def test_soft_dvpp_decode_resize_jpeg_supplement(plot=False):
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"""
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Test SoftDvppDecodeResizeJpeg op
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"""
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logger.info("test_random_decode_resize_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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decode_op = vision.Decode()
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resize_op = vision.Resize(1134)
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data1 = data1.map(operations=[decode_op, resize_op], input_columns=["image"])
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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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soft_dvpp_decode_resize_op = vision.SoftDvppDecodeResizeJpeg(1134)
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data2 = data2.map(operations=soft_dvpp_decode_resize_op, input_columns=["image"])
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num_iter = 0
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for item1, item2 in zip(data1.create_dict_iterator(num_epochs=1, output_numpy=True),
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data2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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if num_iter > 0:
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break
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image1 = item1["image"]
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image2 = item2["image"]
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mse = diff_mse(image1, image2)
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assert mse <= 0.02
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logger.info("random_crop_decode_resize_op_{}, mse: {}".format(num_iter + 1, mse))
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if plot:
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visualize_image(image1, image2, mse)
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num_iter += 1
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if __name__ == "__main__":
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test_soft_dvpp_decode_resize_jpeg(plot=True)
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test_soft_dvpp_decode_random_crop_resize_jpeg(plot=True)
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test_soft_dvpp_decode_resize_jpeg_supplement(plot=True)
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