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# 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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"""Example for natural robustness methods.""" |
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import pytest |
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import numpy as np |
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from mindspore import context |
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from mindarmour.natural_robustness.image import Translate, Curve, Perspective, Scale, Shear, Rotate, SaltAndPepperNoise, \ |
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NaturalNoise, GaussianNoise, UniformNoise, MotionBlur, GaussianBlur, GradientBlur, Contrast, GradientLuminance |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_perspective(): |
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""" |
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Feature: Test image perspective. |
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Description: Image will be transform for given perspective projection. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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ori_pos = [[0, 0], [0, 800], [800, 0], [800, 800]] |
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dst_pos = [[50, 0], [0, 800], [780, 0], [800, 800]] |
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trans = Perspective(ori_pos, dst_pos) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_uniform_noise(): |
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""" |
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Feature: Test image uniform noise. |
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Description: Add uniform image in image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = UniformNoise(factor=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gaussian_noise(): |
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""" |
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Feature: Test image gaussian noise. |
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Description: Add gaussian image in image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = GaussianNoise(factor=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_contrast(): |
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""" |
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Feature: Test image contrast. |
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Description: Adjust image contrast. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Contrast(alpha=0.3, beta=0) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gaussian_blur(): |
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""" |
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Feature: Test image gaussian blur. |
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Description: Add gaussian blur to image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = GaussianBlur(ksize=5) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_salt_and_pepper_noise(): |
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""" |
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Feature: Test image salt and pepper noise. |
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Description: Add salt and pepper to image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = SaltAndPepperNoise(factor=0.01) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_translate(): |
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""" |
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Feature: Test image translate. |
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Description: Translate an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Translate(x_bias=0.1, y_bias=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_scale(): |
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""" |
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Feature: Test image scale. |
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Description: Scale an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Scale(factor_x=0.7, factor_y=0.7) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_shear(): |
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""" |
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Feature: Test image shear. |
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Description: Shear an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Shear(factor=0.2) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_rotate(): |
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""" |
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Feature: Test image rotate. |
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Description: Rotate an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Rotate(angle=20) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_curve(): |
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""" |
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Feature: Test image curve. |
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Description: Transform an image with curve. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = Curve(curves=1.5, depth=1.5, mode='horizontal') |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_natural_noise(): |
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""" |
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Feature: Test natural noise. |
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Description: Add natural noise to an. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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trans = NaturalNoise(ratio=0.0001, k_x_range=(1, 30), k_y_range=(1, 10), auto_param=True) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gradient_luminance(): |
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""" |
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Feature: Test gradient luminance. |
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Description: Adjust image luminance. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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height, width = image.shape[:2] |
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point = (height // 4, width // 2) |
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start = (255, 255, 255) |
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end = (0, 0, 0) |
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scope = 0.3 |
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bright_rate = 0.4 |
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trans = GradientLuminance(start, end, start_point=point, scope=scope, pattern='dark', bright_rate=bright_rate, |
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mode='horizontal') |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_motion_blur(): |
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""" |
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Feature: Test motion blur. |
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Description: Add motion blur to an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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angle = -10.5 |
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i = 3 |
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trans = MotionBlur(degree=i, angle=angle) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_x86_cpu |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gradient_blur(): |
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""" |
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Feature: Test gradient blur. |
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Description: Add gradient blur to an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU") |
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image = np.random.random((32, 32, 3)) |
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number = 10 |
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h, w = image.shape[:2] |
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point = (int(h / 5), int(w / 5)) |
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center = False |
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trans = GradientBlur(point, number, center) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_perspective_ascend(): |
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""" |
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Feature: Test image perspective. |
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Description: Image will be transform for given perspective projection. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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ori_pos = [[0, 0], [0, 800], [800, 0], [800, 800]] |
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dst_pos = [[50, 0], [0, 800], [780, 0], [800, 800]] |
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trans = Perspective(ori_pos, dst_pos) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_uniform_noise_ascend(): |
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""" |
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Feature: Test image uniform noise. |
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Description: Add uniform image in image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = UniformNoise(factor=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gaussian_noise_ascend(): |
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""" |
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Feature: Test image gaussian noise. |
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Description: Add gaussian image in image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = GaussianNoise(factor=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_contrast_ascend(): |
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""" |
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Feature: Test image contrast. |
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Description: Adjust image contrast. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Contrast(alpha=0.3, beta=0) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_gaussian_blur_ascend(): |
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""" |
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Feature: Test image gaussian blur. |
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Description: Add gaussian blur to image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = GaussianBlur(ksize=5) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_salt_and_pepper_noise_ascend(): |
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""" |
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Feature: Test image salt and pepper noise. |
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Description: Add salt and pepper to image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = SaltAndPepperNoise(factor=0.01) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_translate_ascend(): |
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""" |
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Feature: Test image translate. |
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Description: Translate an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Translate(x_bias=0.1, y_bias=0.1) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_ascend_mindarmour |
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def test_scale_ascend(): |
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""" |
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Feature: Test image scale. |
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Description: Scale an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Scale(factor_x=0.7, factor_y=0.7) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_shear_ascend(): |
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""" |
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Feature: Test image shear. |
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Description: Shear an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Shear(factor=0.2) |
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dst = trans(image) |
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print(dst) |
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@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_rotate_ascend(): |
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""" |
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Feature: Test image rotate. |
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Description: Rotate an image. |
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Expectation: success. |
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""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Rotate(angle=20) |
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dst = trans(image) |
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print(dst) |
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|
@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_curve_ascend(): |
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""" |
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|
Feature: Test image curve. |
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|
Description: Transform an image with curve. |
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Expectation: success. |
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|
""" |
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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image = np.random.random((32, 32, 3)) |
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trans = Curve(curves=1.5, depth=1.5, mode='horizontal') |
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dst = trans(image) |
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|
print(dst) |
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|
@pytest.mark.level0 |
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@pytest.mark.platform_arm_ascend_training |
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@pytest.mark.platform_x86_ascend_training |
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@pytest.mark.env_card |
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@pytest.mark.component_mindarmour |
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def test_natural_noise_ascend(): |
|
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""" |
|
|
|
Feature: Test natural noise. |
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|
|
Description: Add natural noise to an. |
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|
Expectation: success. |
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|
""" |
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|
|
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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|
image = np.random.random((32, 32, 3)) |
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|
trans = NaturalNoise(ratio=0.0001, k_x_range=(1, 30), k_y_range=(1, 10), auto_param=True) |
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|
dst = trans(image) |
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|
print(dst) |
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|
@pytest.mark.level0 |
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|
@pytest.mark.platform_arm_ascend_training |
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|
@pytest.mark.platform_x86_ascend_training |
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|
@pytest.mark.env_card |
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|
@pytest.mark.component_mindarmour |
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def test_gradient_luminance_ascend(): |
|
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|
""" |
|
|
|
Feature: Test gradient luminance. |
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|
|
Description: Adjust image luminance. |
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|
|
Expectation: success. |
|
|
|
""" |
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
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|
image = np.random.random((32, 32, 3)) |
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|
|
height, width = image.shape[:2] |
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|
point = (height // 4, width // 2) |
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|
start = (255, 255, 255) |
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|
end = (0, 0, 0) |
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|
scope = 0.3 |
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|
bright_rate = 0.4 |
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|
|
trans = GradientLuminance(start, end, start_point=point, scope=scope, pattern='dark', bright_rate=bright_rate, |
|
|
|
mode='horizontal') |
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|
|
dst = trans(image) |
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|
|
print(dst) |
|
|
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|
|
|
@pytest.mark.level0 |
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|
@pytest.mark.platform_arm_ascend_training |
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|
@pytest.mark.platform_x86_ascend_training |
|
|
|
@pytest.mark.env_card |
|
|
|
@pytest.mark.component_mindarmour |
|
|
|
def test_motion_blur_ascend(): |
|
|
|
""" |
|
|
|
Feature: Test motion blur. |
|
|
|
Description: Add motion blur to an image. |
|
|
|
Expectation: success. |
|
|
|
""" |
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
|
|
|
image = np.random.random((32, 32, 3)) |
|
|
|
angle = -10.5 |
|
|
|
i = 3 |
|
|
|
trans = MotionBlur(degree=i, angle=angle) |
|
|
|
dst = trans(image) |
|
|
|
print(dst) |
|
|
|
|
|
|
|
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|
|
|
@pytest.mark.level0 |
|
|
|
@pytest.mark.platform_arm_ascend_training |
|
|
|
@pytest.mark.platform_x86_ascend_training |
|
|
|
@pytest.mark.env_card |
|
|
|
@pytest.mark.component_mindarmour |
|
|
|
def test_gradient_blur_ascend(): |
|
|
|
""" |
|
|
|
Feature: Test gradient blur. |
|
|
|
Description: Add gradient blur to an image. |
|
|
|
Expectation: success. |
|
|
|
""" |
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target="Ascend") |
|
|
|
image = np.random.random((32, 32, 3)) |
|
|
|
number = 10 |
|
|
|
h, w = image.shape[:2] |
|
|
|
point = (int(h / 5), int(w / 5)) |
|
|
|
center = False |
|
|
|
trans = GradientBlur(point, number, center) |
|
|
|
dst = trans(image) |
|
|
|
print(dst) |