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# 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 Resize op in DE |
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""" |
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import pytest |
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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.utils import Inter |
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from mindspore import log as logger |
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from util import visualize_list, save_and_check_md5, \ |
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config_get_set_seed, config_get_set_num_parallel_workers |
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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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GENERATE_GOLDEN = False |
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def test_resize_op(plot=False): |
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def test_resize_op_parameters(test_name, size, plot): |
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""" |
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Test resize_op |
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""" |
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logger.info("Test resize: {0}".format(test_name)) |
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data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False) |
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# define map operations |
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decode_op = vision.Decode() |
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resize_op = vision.Resize(size) |
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# apply map operations on images |
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data1 = data1.map(input_columns=["image"], operations=decode_op) |
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data2 = data1.map(input_columns=["image"], operations=resize_op) |
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image_original = [] |
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image_resized = [] |
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for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()): |
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image_1 = item1["image"] |
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image_2 = item2["image"] |
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image_original.append(image_1) |
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image_resized.append(image_2) |
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if plot: |
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visualize_list(image_original, image_resized) |
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test_resize_op_parameters("Test single int for size", 10, plot=False) |
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test_resize_op_parameters("Test tuple for size", (10, 15), plot=False) |
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def test_resize_md5(plot=False): |
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def test_resize_md5_parameters(test_name, size, filename, seed, plot): |
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""" |
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Test Resize with md5 check |
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""" |
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logger.info("Test Resize with md5 check: {0}".format(test_name)) |
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original_seed = config_get_set_seed(seed) |
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original_num_parallel_workers = config_get_set_num_parallel_workers(1) |
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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 = vision.Decode() |
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resize_op = vision.Resize(size) |
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data1 = data1.map(input_columns=["image"], operations=decode_op) |
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data2 = data1.map(input_columns=["image"], operations=resize_op) |
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image_original = [] |
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image_resized = [] |
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# Compare with expected md5 from images |
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save_and_check_md5(data1, filename, generate_golden=GENERATE_GOLDEN) |
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for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()): |
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image_1 = item1["image"] |
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image_2 = item2["image"] |
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image_original.append(image_1) |
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image_resized.append(image_2) |
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if plot: |
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visualize_list(image_original, image_resized) |
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# Restore configuration |
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ds.config.set_seed(original_seed) |
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ds.config.set_num_parallel_workers(original_num_parallel_workers) |
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test_resize_md5_parameters("Test single int for size", 5, "resize_01_result.npz", 5, plot) |
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test_resize_md5_parameters("Test tuple for size", (5, 7), "resize_02_result.npz", 7, plot) |
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def test_resize_op_invalid_input(): |
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def test_invalid_input(test_name, size, interpolation, error, error_msg): |
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logger.info("Test Resize with bad input: {0}".format(test_name)) |
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with pytest.raises(error) as error_info: |
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vision.Resize(size, interpolation) |
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assert error_msg in str(error_info.value) |
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test_invalid_input("invalid size parameter type as a single number", 4.5, Inter.LINEAR, TypeError, |
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"Size should be a single integer or a list/tuple (h, w) of length 2.") |
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test_invalid_input("invalid size parameter shape", (2, 3, 4), Inter.LINEAR, TypeError, |
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"Size should be a single integer or a list/tuple (h, w) of length 2.") |
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test_invalid_input("invalid size parameter type in a tuple", (2.3, 3), Inter.LINEAR, TypeError, |
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"incompatible constructor arguments.") |
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test_invalid_input("invalid Interpolation value", (2.3, 3), None, KeyError, "None") |
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if __name__ == "__main__": |
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test_resize_op(plot=True) |
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test_resize_md5(plot=True) |
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test_resize_op_invalid_input() |