forked from mindspore-Ecosystem/mindspore
197 lines
8.0 KiB
Python
197 lines
8.0 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 Affine op in DE
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"""
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import numpy as np
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from mindspore import log as logger
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import mindspore.dataset as ds
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import mindspore.dataset.transforms as transforms
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import mindspore.dataset.vision as vision
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from util import visualize_list, diff_mse
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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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MNIST_DATA_DIR = "../data/dataset/testMnistData"
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def test_affine_exception_degrees_type():
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"""
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Feature: Test Affine degrees type
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Description: Input the type of degrees is list
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Expectation: Got an exception to raise TyoeError
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"""
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logger.info("test_affine_exception_degrees_type")
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try:
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_ = vision.Affine(degrees=[15.0], translate=[-1, 1], scale=1.0, shear=[1, 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) == "Argument degrees with value [15.0] is not of type [<class 'int'>, <class 'float'>], " \
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"but got <class 'list'>."
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def test_affine_exception_scale_value():
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"""
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Feature: Test Affine(scale is not valid)
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Description: Input scale is not valid
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Expectation: Got an exception to raise ValueError
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"""
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logger.info("test_affine_exception_scale_value")
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try:
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_ = vision.Affine(degrees=15, translate=[1, 1], scale=0.0, shear=10)
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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) == "Input scale must be greater than 0."
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try:
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_ = vision.Affine(degrees=15, translate=[1, 1], scale=-0.2, shear=10)
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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) == "Input scale must be greater than 0."
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def test_affine_exception_shear_size():
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"""
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Feature: Test Affine(shear is not list or a tuple of length 2)
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Description: Input shear is not list or a tuple of length 2
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Expectation: Got an exception to raise TypeError
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"""
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logger.info("test_affine_shear_size")
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try:
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_ = vision.Affine(degrees=15, translate=[1, 1], scale=1.5, shear=[1.5, 3.5, 3.5])
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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) == "The length of shear should be 2."
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def test_affine_exception_translate_size():
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"""
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Feature: Test Affine(translate is not list or a tuple of length 2)
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Description: Input translate is not list or a tuple of length 2
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Expectation: Got an exception to raise TypeError
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"""
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logger.info("test_affine_exception_translate_size")
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try:
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_ = vision.Affine(degrees=15, translate=[1, 1, 1], scale=1.9, shear=[10.1])
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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) == "The length of translate should be 2."
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def test_affine_exception_translate_value():
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"""
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Feature: Test Affine(translate value)
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Description: Input translate is not a sequence
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Expectation: Got an exception to raise TypeError
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"""
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logger.info("test_affine_exception_translate_value")
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try:
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_ = vision.Affine(degrees=15, translate=(0.1,), scale=2.1, shear=[1.5, 1.5], resample=vision.Inter.BILINEAR)
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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) == "The length of translate should be 2."
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def test_affine_pipeline(plot=False):
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"""
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Feature: Affine
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Description: Test Affine in pipeline mode
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Expectation: The dataset is processed as expected
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"""
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# First dataset
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transforms_list = transforms.Compose([vision.Decode(),
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vision.Resize([64, 64])])
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dataset = ds.TFRecordDataset(DATA_DIR,
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SCHEMA_DIR,
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columns_list=["image"],
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shuffle=False)
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dataset = dataset.map(operations=transforms_list, input_columns=["image"])
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# Second dataset
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affine_transforms_list = transforms.Compose([vision.Decode(),
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vision.Resize([64, 64]),
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vision.Affine(degrees=15, translate=[0.2, 0.2],
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scale=1.1, shear=[10.0, 10.0])])
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affine_dataset = ds.TFRecordDataset(DATA_DIR,
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SCHEMA_DIR,
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columns_list=["image"],
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shuffle=False)
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affine_dataset = affine_dataset.map(operations=affine_transforms_list, input_columns=["image"])
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num_image = 0
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image_list = []
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affine_image_list = []
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for image, affine_image in zip(dataset.create_dict_iterator(num_epochs=1, output_numpy=True),
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affine_dataset.create_dict_iterator(num_epochs=1, output_numpy=True)):
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num_image += 1
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image_list.append(image["image"])
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affine_image_list.append(affine_image["image"])
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assert num_image == 3
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if plot:
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visualize_list(image_list, affine_image_list)
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def test_affine_eager():
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"""
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Feature: Affine op
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Description: Test eager support for Affine Cpp implementation
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Expectation: The output data is the same as the result of cv2.warpAffine
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"""
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img_in = np.array([[[211, 192, 16], [146, 176, 190], [103, 86, 18], [23, 194, 246]],
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[[17, 86, 38], [180, 162, 43], [197, 198, 224], [109, 3, 195]],
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[[172, 197, 74], [33, 52, 136], [120, 185, 76], [105, 23, 221]],
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[[197, 50, 36], [82, 187, 119], [124, 193, 164], [181, 8, 11]]], dtype=np.uint8)
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affine_op1 = vision.Affine(degrees=30, translate=[0.5, 0.5], scale=1.0, shear=[0, 0])
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img_out1 = affine_op1(img_in)
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exp1 = np.array([[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0], [211, 192, 16]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0], [211, 192, 16]],
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[[0, 0, 0], [0, 0, 0], [172, 197, 74], [180, 162, 43]]], dtype=np.uint8)
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affine_op2 = vision.Affine(degrees=30, translate=[0.5, 0.5], scale=1.0, shear=[10, 10])
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img_out2 = affine_op2(img_in)
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exp2 = np.array([[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0], [211, 192, 16]],
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[[0, 0, 0], [0, 0, 0], [172, 197, 74], [180, 162, 43]]], dtype=np.uint8)
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affine_op3 = vision.Affine(degrees=30, translate=[0.5, 0.5], scale=1.2, shear=5)
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img_out3 = affine_op3(img_in)
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exp3 = np.array([[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]],
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[[0, 0, 0], [0, 0, 0], [0, 0, 0], [211, 192, 16]],
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[[0, 0, 0], [0, 0, 0], [17, 86, 38], [17, 86, 38]],
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[[0, 0, 0], [172, 197, 74], [172, 197, 74], [180, 162, 43]]], dtype=np.uint8)
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mse1 = diff_mse(img_out1, exp1)
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mse2 = diff_mse(img_out2, exp2)
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mse3 = diff_mse(img_out3, exp3)
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assert mse1 < 0.001 and mse2 < 0.001 and mse3 < 0.001
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if __name__ == "__main__":
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test_affine_exception_degrees_type()
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test_affine_exception_scale_value()
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test_affine_exception_shear_size()
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test_affine_exception_translate_size()
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test_affine_exception_translate_value()
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test_affine_pipeline(plot=False)
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test_affine_eager()
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