43 lines
1.5 KiB
Python
43 lines
1.5 KiB
Python
# Copyright 2023 The MediaPipe Authors.
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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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import numpy as np
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import tensorflow as tf
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from mediapipe.model_maker.python.vision.core import image_utils
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from mediapipe.model_maker.python.vision.face_stylizer import dataset
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from mediapipe.tasks.python.test import test_utils
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class DatasetTest(tf.test.TestCase):
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def setUp(self):
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super().setUp()
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def test_from_image(self):
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test_image_file = 'input/style/cartoon/cartoon.jpg'
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input_data_dir = test_utils.get_test_data_path(test_image_file)
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data = dataset.Dataset.from_image(filename=input_data_dir)
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self.assertEqual(data.num_classes, 1)
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self.assertEqual(data.label_names, ['cartoon'])
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self.assertLen(data, 1)
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def test_from_image_raise_value_error_for_invalid_path(self):
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with self.assertRaisesRegex(ValueError, 'Unsupported image formats: .zip'):
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dataset.Dataset.from_image(filename='input/style/cartoon/cartoon.zip')
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if __name__ == '__main__':
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tf.test.main()
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