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208 lines
7.5 KiB
208 lines
7.5 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 RandomAffine op in DE
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"""
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import numpy as np
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import mindspore.dataset as ds
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import mindspore.dataset.transforms.vision.py_transforms as py_vision
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from mindspore import log as logger
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from util import visualize, save_and_check_md5, \
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config_get_set_seed, config_get_set_num_parallel_workers
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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_random_affine_op(plot=False):
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"""
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Test RandomAffine in python transformations
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"""
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logger.info("test_random_affine_op")
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# define map operations
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transforms1 = [
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py_vision.Decode(),
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py_vision.RandomAffine(degrees=15, translate=(0.1, 0.1), scale=(0.9, 1.1)),
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py_vision.ToTensor()
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]
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transform1 = py_vision.ComposeOp(transforms1)
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transforms2 = [
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py_vision.Decode(),
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py_vision.ToTensor()
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]
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transform2 = py_vision.ComposeOp(transforms2)
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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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data1 = data1.map(input_columns=["image"], operations=transform1())
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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=transform2())
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image_affine = []
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image_original = []
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for item1, item2 in zip(data1.create_dict_iterator(), data2.create_dict_iterator()):
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image1 = (item1["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
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image2 = (item2["image"].transpose(1, 2, 0) * 255).astype(np.uint8)
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image_affine.append(image1)
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image_original.append(image2)
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if plot:
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visualize(image_original, image_affine)
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def test_random_affine_md5():
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"""
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Test RandomAffine with md5 comparison
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"""
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logger.info("test_random_affine_md5")
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original_seed = config_get_set_seed(55)
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original_num_parallel_workers = config_get_set_num_parallel_workers(1)
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# define map operations
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transforms = [
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py_vision.Decode(),
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py_vision.RandomAffine(degrees=(-5, 15), translate=(0.1, 0.3),
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scale=(0.9, 1.1), shear=(-10, 10, -5, 5)),
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py_vision.ToTensor()
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]
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transform = py_vision.ComposeOp(transforms)
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# Generate dataset
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data = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
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data = data.map(input_columns=["image"], operations=transform())
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# check results with md5 comparison
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filename = "random_affine_01_result.npz"
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save_and_check_md5(data, filename, generate_golden=GENERATE_GOLDEN)
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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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def test_random_affine_exception_negative_degrees():
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"""
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Test RandomAffine: input degrees in negative, expected to raise ValueError
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"""
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logger.info("test_random_affine_exception_negative_degrees")
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try:
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_ = py_vision.RandomAffine(degrees=-15)
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except ValueError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "If degrees is a single number, it cannot be negative."
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def test_random_affine_exception_translation_range():
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"""
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Test RandomAffine: translation value is not in [0, 1], expected to raise ValueError
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"""
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logger.info("test_random_affine_exception_translation_range")
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try:
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_ = py_vision.RandomAffine(degrees=15, translate=(0.1, 1.5))
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except ValueError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "translation values should be between 0 and 1"
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def test_random_affine_exception_scale_value():
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"""
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Test RandomAffine: scale is not positive, expected to raise ValueError
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"""
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logger.info("test_random_affine_exception_scale_value")
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try:
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_ = py_vision.RandomAffine(degrees=15, scale=(0.0, 1.1))
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except ValueError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "scale values should be positive"
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def test_random_affine_exception_shear_value():
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"""
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Test RandomAffine: shear is a number but is not positive, expected to raise ValueError
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"""
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logger.info("test_random_affine_exception_shear_value")
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try:
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_ = py_vision.RandomAffine(degrees=15, shear=-5)
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except ValueError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "If shear is a single number, it must be positive."
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def test_random_affine_exception_degrees_size():
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"""
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Test RandomAffine: degrees is a list or tuple and its length is not 2,
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expected to raise TypeError
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"""
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logger.info("test_random_affine_exception_degrees_size")
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try:
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_ = py_vision.RandomAffine(degrees=[15])
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except TypeError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "If degrees is a sequence, the length must be 2."
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def test_random_affine_exception_translate_size():
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"""
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Test RandomAffine: translate is not list or a tuple of length 2,
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expected to raise TypeError
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"""
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logger.info("test_random_affine_exception_translate_size")
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try:
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_ = py_vision.RandomAffine(degrees=15, translate=(0.1))
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except TypeError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "translate should be a list or tuple of length 2."
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def test_random_affine_exception_scale_size():
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"""
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Test RandomAffine: scale is not a list or tuple of length 2,
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expected to raise TypeError
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"""
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logger.info("test_random_affine_exception_scale_size")
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try:
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_ = py_vision.RandomAffine(degrees=15, scale=(0.5))
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except TypeError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "scale should be a list or tuple of length 2."
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def test_random_affine_exception_shear_size():
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"""
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Test RandomAffine: shear is not a list or tuple of length 2 or 4,
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expected to raise TypeError
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"""
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logger.info("test_random_affine_exception_shear_size")
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try:
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_ = py_vision.RandomAffine(degrees=15, shear=(-5, 5, 10))
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except TypeError as e:
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logger.info("Got an exception in DE: {}".format(str(e)))
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assert str(e) == "shear should be a list or tuple and it must be of length 2 or 4."
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if __name__ == "__main__":
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test_random_affine_op(plot=True)
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test_random_affine_md5()
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test_random_affine_exception_negative_degrees()
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test_random_affine_exception_translation_range()
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test_random_affine_exception_scale_value()
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test_random_affine_exception_shear_value()
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test_random_affine_exception_degrees_size()
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test_random_affine_exception_translate_size()
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test_random_affine_exception_scale_size()
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test_random_affine_exception_shear_size()
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