forked from mindspore-Ecosystem/mindspore
127 lines
5.6 KiB
Python
127 lines
5.6 KiB
Python
# Copyright 2022 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 Erase op in DE
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"""
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import cv2
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import numpy as np
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import pytest
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import mindspore.dataset as ds
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import mindspore.dataset.vision as vision
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from mindspore import log as logger
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from util import visualize_image, diff_mse
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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_erase_op(plot=False):
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"""
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Feature: Erase op
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Description: Test Erase pipeline
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Expectation: Pass without error
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"""
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logger.info("test_erase_pipeline")
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# First dataset
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dataset1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, shuffle=False)
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decode_op = vision.Decode()
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erase_op = vision.Erase(1, 1, 2, 4)
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dataset1 = dataset1.map(operations=decode_op, input_columns=["image"])
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dataset1 = dataset1.map(operations=erase_op, input_columns=["image"])
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# Second dataset
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dataset2 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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dataset2 = dataset2.map(operations=decode_op, input_columns=["image"])
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num_iter = 0
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for item1, item2 in zip(dataset1.create_dict_iterator(num_epochs=1, output_numpy=True),
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dataset2.create_dict_iterator(num_epochs=1, output_numpy=True)):
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num_iter += 1
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erase_ms = item1["image"]
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original = item2["image"]
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erase_cv = cv2.rectangle(original, (1, 1), (4, 2), 0, -1)
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mse = diff_mse(erase_ms, erase_cv)
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logger.info("mse is {}".format(mse))
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assert mse < 0.01
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if plot:
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visualize_image(erase_ms, erase_cv, mse)
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def test_func_erase_eager():
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"""
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Feature: Erase op
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Description: Test Erase in eager mode
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Expectation: Output is the same as expected output
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"""
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image1 = np.random.randint(0, 255, (30, 30, 3), dtype=np.int32)
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out1 = vision.Erase(1, 1, 2, 4, 30)(image1)
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out2 = cv2.rectangle(image1, (1, 1), (4, 2), 30, -1)
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mse = diff_mse(out1, out2)
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logger.info("mse is {}".format(mse))
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assert mse < 0.01
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def test_erase_invalid_input():
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"""
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Feature: Erase op
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Description: Test operation with invalid input
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Expectation: Throw exception as expected
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"""
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def test_invalid_input(test_name, top, left, height, width, value, inplace, error, error_msg):
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logger.info("Test Erase with bad input: {0}".format(test_name))
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with pytest.raises(error) as error_info:
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vision.Erase(top, left, height, width, value, inplace)
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print(error_info)
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assert error_msg in str(error_info.value)
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test_invalid_input("invalid top parameter Value", 999999999999, 10, 10, 10, 0,
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False, ValueError, "Input top is not within the required interval of [0, 2147483647].")
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test_invalid_input("invalid top parameter type", 10.5, 10, 10, 10, 0, False, TypeError,
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"Argument top with value 10.5 is not of type [<class 'int'>], but got <class 'float'>.")
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test_invalid_input("invalid left parameter Value", 10, 999999999999, 10, 10, 0,
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False, ValueError, "Input left is not within the required interval of [0, 2147483647].")
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test_invalid_input("invalid left parameter type", 10, 10.5, 10, 10, 0, False, TypeError,
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"Argument left with value 10.5 is not of type [<class 'int'>], but got <class 'float'>.")
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test_invalid_input("invalid height parameter Value", 10, 10, 999999999999, 10, 0,
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False, ValueError, "Input height is not within the required interval of [1, 2147483647].")
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test_invalid_input("invalid height parameter type", 10, 10, 10.5, 10, 0, False, TypeError,
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"Argument height with value 10.5 is not of type [<class 'int'>], but got <class 'float'>.")
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test_invalid_input("invalid width parameter Value", 10, 10, 10, 999999999999, 0,
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False, ValueError, "Input width is not within the required interval of [1, 2147483647].")
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test_invalid_input("invalid width parameter type", 10, 10, 10, 10.5, 0, False, TypeError,
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"Argument width with value 10.5 is not of type [<class 'int'>], but got <class 'float'>.")
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test_invalid_input("invalid value parameter Value", 10, 10, 10, 10, 999999999999,
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False, ValueError, "Input fill_value is not within the required interval of [0, 255].")
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test_invalid_input("invalid value parameter type as a single number", 10, 10, 10, 10, 3.5, False, TypeError,
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"fill_value should be a single integer or a 3-tuple.")
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test_invalid_input("invalid value parameter shape", 10, 10, 10, 10, (2, 3), False, TypeError,
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"fill_value should be a single integer or a 3-tuple.")
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test_invalid_input("invalid inplace parameter type as a single number", 10, 10, 10, 10, 0, 0, TypeError,
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"Argument inplace with value 0 is not of type [<class 'bool'>], but got <class 'int'>.")
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if __name__ == "__main__":
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test_erase_op(plot=True)
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test_func_erase_eager()
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test_erase_invalid_input()
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