forked from mindspore-Ecosystem/mindspore
135 lines
4.3 KiB
Python
135 lines
4.3 KiB
Python
# Copyright 2020-2022 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 ToPIL op in DE
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"""
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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.transforms
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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 save_and_check_md5_pil
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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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Feature: ToPIL op
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Description: Test ToPIL op with md5 comparison where input is already PIL image
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Expectation: Passes the md5 check test
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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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vision.Decode(True),
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# If input is already PIL image.
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vision.ToPIL(),
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vision.CenterCrop(375),
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vision.ToTensor()
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]
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transform = mindspore.dataset.transforms.Compose(transforms)
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data1 = data1.map(operations=transform, input_columns=["image"])
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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_pil(data1, filename, generate_golden=GENERATE_GOLDEN)
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def test_to_pil_02():
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"""
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Feature: ToPIL op
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Description: Test ToPIL op with md5 comparison where input is not a PIL image
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Expectation: Passes the md5 check test
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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 = vision.Decode()
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transforms = [
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# If input type is not PIL.
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vision.ToPIL(),
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vision.CenterCrop(375),
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vision.ToTensor()
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]
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transform = mindspore.dataset.transforms.Compose(transforms)
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data1 = data1.map(operations=decode_op, input_columns=["image"])
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data1 = data1.map(operations=transform, input_columns=["image"])
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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_pil(data1, filename, generate_golden=GENERATE_GOLDEN)
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def test_to_pil_invalid_type():
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"""
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Feature: ToPIL
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Description: Test ToPIL with invalid image type
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Expectation: Error is raised as expected
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"""
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image = list(np.random.randint(0, 255, (32, 32, 3)))
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to_pil = vision.ToPIL()
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with pytest.raises(TypeError) as error_info:
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to_pil(image)
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assert "should be of type numpy.ndarray or PIL.Image.Image" in str(error_info.value)
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def test_to_pil_invalid_shape():
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"""
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Feature: ToPIL
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Description: Test ToPIL with invalid image shape
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Expectation: Error is raised as expected
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"""
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image = np.random.randint(0, 255, (32, 32, 4, 3)).astype(np.uint8)
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to_pil = vision.ToPIL()
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with pytest.raises(ValueError) as error_info:
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to_pil(image)
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assert "dimension of input image should be 2 or 3" in str(error_info.value)
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image = np.random.randint(0, 255, (32, 32, 5)).astype(np.uint8)
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to_pil = vision.ToPIL()
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with pytest.raises(ValueError) as error_info:
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to_pil(image)
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assert "channel of input image should not exceed 4" in str(error_info.value)
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def test_to_pil_invalid_dtype():
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"""
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Feature: ToPIL
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Description: Test ToPIL with invalid image dtype
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Expectation: Error is raised as expected
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"""
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image = np.random.randint(0, 255, (32, 32, 3)).astype(np.int16)
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to_pil = vision.ToPIL()
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with pytest.raises(TypeError) as error_info:
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to_pil(image)
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assert "image type int16 is not supported" in str(error_info.value)
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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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test_to_pil_invalid_type()
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test_to_pil_invalid_shape()
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test_to_pil_invalid_dtype()
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