Added files for Face Stylizer Unit Tests
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@ -211,3 +211,20 @@ py_test(
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"//mediapipe/tasks/python/vision/core:image_processing_options",
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"//mediapipe/tasks/python/vision/core:image_processing_options",
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],
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],
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)
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)
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py_test(
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name = "face_stylizer_test",
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srcs = ["face_stylizer_test.py"],
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data = [
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"//mediapipe/tasks/testdata/vision:test_images",
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"//mediapipe/tasks/testdata/vision:test_models",
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],
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deps = [
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"//mediapipe/python:_framework_bindings",
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"//mediapipe/tasks/python/components/containers:rect",
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"//mediapipe/tasks/python/core:base_options",
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"//mediapipe/tasks/python/test:test_utils",
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"//mediapipe/tasks/python/vision:face_stylizer",
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"//mediapipe/tasks/python/vision/core:image_processing_options",
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],
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)
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182
mediapipe/tasks/python/test/vision/face_stylizer_test.py
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182
mediapipe/tasks/python/test/vision/face_stylizer_test.py
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@ -0,0 +1,182 @@
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# Copyright 2023 The MediaPipe Authors. All Rights Reserved.
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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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"""Tests for face stylizer."""
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import enum
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import os
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from absl.testing import absltest
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from absl.testing import parameterized
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from mediapipe.python._framework_bindings import image as image_module
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from mediapipe.tasks.python.core import base_options as base_options_module
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from mediapipe.tasks.python.components.containers import rect
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from mediapipe.tasks.python.test import test_utils
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from mediapipe.tasks.python.vision import face_stylizer
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from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module
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_BaseOptions = base_options_module.BaseOptions
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_Rect = rect.Rect
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_Image = image_module.Image
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_FaceStylizer = face_stylizer.FaceStylizer
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_FaceStylizerOptions = face_stylizer.FaceStylizerOptions
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_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions
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_MODEL = 'face_stylizer_color_ink.task'
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_LARGE_FACE_IMAGE = "portrait.jpg"
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_MODEL_IMAGE_SIZE = 256
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_TEST_DATA_DIR = 'mediapipe/tasks/testdata/vision'
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class ModelFileType(enum.Enum):
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FILE_CONTENT = 1
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FILE_NAME = 2
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class FaceStylizerTest(parameterized.TestCase):
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def setUp(self):
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super().setUp()
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self.test_image = _Image.create_from_file(
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test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)))
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self.model_path = test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, _MODEL))
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def test_create_from_file_succeeds_with_valid_model_path(self):
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# Creates with default option and valid model file successfully.
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with _FaceStylizer.create_from_model_path(self.model_path) as stylizer:
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self.assertIsInstance(stylizer, _FaceStylizer)
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def test_create_from_options_succeeds_with_valid_model_path(self):
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# Creates with options containing model file successfully.
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base_options = _BaseOptions(model_asset_path=self.model_path)
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options = _FaceStylizerOptions(base_options=base_options)
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with _FaceStylizer.create_from_options(options) as stylizer:
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self.assertIsInstance(stylizer, _FaceStylizer)
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def test_create_from_options_fails_with_invalid_model_path(self):
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with self.assertRaisesRegex(
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RuntimeError, 'Unable to open file at /path/to/invalid/model.tflite'):
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base_options = _BaseOptions(
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model_asset_path='/path/to/invalid/model.tflite')
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options = _FaceStylizerOptions(base_options=base_options)
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_FaceStylizer.create_from_options(options)
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def test_create_from_options_succeeds_with_valid_model_content(self):
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# Creates with options containing model content successfully.
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with open(self.model_path, 'rb') as f:
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base_options = _BaseOptions(model_asset_buffer=f.read())
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options = _FaceStylizerOptions(base_options=base_options)
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stylizer = _FaceStylizer.create_from_options(options)
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self.assertIsInstance(stylizer, _FaceStylizer)
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@parameterized.parameters(
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(ModelFileType.FILE_NAME, _LARGE_FACE_IMAGE),
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(ModelFileType.FILE_CONTENT, _LARGE_FACE_IMAGE)
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)
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def test_stylize(self, model_file_type, image_file_name):
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# Load the test image.
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self.test_image = _Image.create_from_file(
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test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, image_file_name)))
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# Creates stylizer.
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if model_file_type is ModelFileType.FILE_NAME:
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base_options = _BaseOptions(model_asset_path=self.model_path)
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elif model_file_type is ModelFileType.FILE_CONTENT:
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with open(self.model_path, 'rb') as f:
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model_content = f.read()
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base_options = _BaseOptions(model_asset_buffer=model_content)
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else:
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# Should never happen
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raise ValueError('model_file_type is invalid.')
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options = _FaceStylizerOptions(base_options=base_options)
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stylizer = _FaceStylizer.create_from_options(options)
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# Performs face stylization on the input.
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stylized_image = stylizer.stylize(self.test_image)
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self.assertIsInstance(stylized_image, _Image)
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# Closes the stylizer explicitly when the stylizer is not used in
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# a context.
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stylizer.close()
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@parameterized.parameters(
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(ModelFileType.FILE_NAME, _LARGE_FACE_IMAGE),
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(ModelFileType.FILE_CONTENT, _LARGE_FACE_IMAGE)
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)
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def test_stylize_in_context(self, model_file_type, image_file_name):
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# Load the test image.
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self.test_image = _Image.create_from_file(
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test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, image_file_name)))
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# Creates stylizer.
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if model_file_type is ModelFileType.FILE_NAME:
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base_options = _BaseOptions(model_asset_path=self.model_path)
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elif model_file_type is ModelFileType.FILE_CONTENT:
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with open(self.model_path, 'rb') as f:
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model_content = f.read()
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base_options = _BaseOptions(model_asset_buffer=model_content)
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else:
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# Should never happen
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raise ValueError('model_file_type is invalid.')
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options = _FaceStylizerOptions(base_options=base_options)
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with _FaceStylizer.create_from_options(options) as stylizer:
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# Performs face stylization on the input.
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stylized_image = stylizer.stylize(self.test_image)
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self.assertIsInstance(stylized_image, _Image)
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self.assertEqual(stylized_image.width, _MODEL_IMAGE_SIZE)
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self.assertEqual(stylized_image.height, _MODEL_IMAGE_SIZE)
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def test_stylize_succeeds_with_region_of_interest(self):
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base_options = _BaseOptions(model_asset_path=self.model_path)
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options = _FaceStylizerOptions(base_options=base_options)
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with _FaceStylizer.create_from_options(options) as stylizer:
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# Load the test image.
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test_image = _Image.create_from_file(
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test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)
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)
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)
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# Region-of-interest around the face.
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roi = _Rect(left=0.32, top=0.02, right=0.67, bottom=0.32)
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image_processing_options = _ImageProcessingOptions(roi)
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# Performs face stylization on the input.
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stylized_image = stylizer.stylize(test_image, image_processing_options)
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self.assertIsInstance(stylized_image, _Image)
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self.assertEqual(stylized_image.width, _MODEL_IMAGE_SIZE)
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self.assertEqual(stylized_image.height, _MODEL_IMAGE_SIZE)
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def test_stylize_succeeds_with_no_face_detected(self):
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base_options = _BaseOptions(model_asset_path=self.model_path)
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options = _FaceStylizerOptions(base_options=base_options)
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with _FaceStylizer.create_from_options(options) as stylizer:
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# Load the test image.
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test_image = _Image.create_from_file(
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test_utils.get_test_data_path(
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os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)
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)
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)
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# Region-of-interest that doesn't contain a human face.
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roi = _Rect(left=0.1, top=0.1, right=0.2, bottom=0.2)
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image_processing_options = _ImageProcessingOptions(roi)
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# Performs face stylization on the input.
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stylized_image = stylizer.stylize(test_image, image_processing_options)
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self.assertIsNone(stylized_image)
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if __name__ == '__main__':
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absltest.main()
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1
mediapipe/tasks/testdata/vision/BUILD
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1
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@ -186,6 +186,7 @@ filegroup(
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"face_detection_short_range.tflite",
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"face_detection_short_range.tflite",
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"face_landmarker.task",
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"face_landmarker.task",
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"face_landmarker_v2.task",
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"face_landmarker_v2.task",
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"face_stylizer_color_ink.task",
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"hair_segmentation.tflite",
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"hair_segmentation.tflite",
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"hand_landmark_full.tflite",
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"hand_landmark_full.tflite",
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"hand_landmark_lite.tflite",
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"hand_landmark_lite.tflite",
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