Added files for Face Stylizer Unit Tests

This commit is contained in:
Kinar 2023-09-19 03:08:01 -07:00
parent 0ed199186b
commit 1c40ecf8a5
3 changed files with 200 additions and 0 deletions

View File

@ -211,3 +211,20 @@ py_test(
"//mediapipe/tasks/python/vision/core:image_processing_options", "//mediapipe/tasks/python/vision/core:image_processing_options",
], ],
) )
py_test(
name = "face_stylizer_test",
srcs = ["face_stylizer_test.py"],
data = [
"//mediapipe/tasks/testdata/vision:test_images",
"//mediapipe/tasks/testdata/vision:test_models",
],
deps = [
"//mediapipe/python:_framework_bindings",
"//mediapipe/tasks/python/components/containers:rect",
"//mediapipe/tasks/python/core:base_options",
"//mediapipe/tasks/python/test:test_utils",
"//mediapipe/tasks/python/vision:face_stylizer",
"//mediapipe/tasks/python/vision/core:image_processing_options",
],
)

View File

@ -0,0 +1,182 @@
# Copyright 2023 The MediaPipe Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for face stylizer."""
import enum
import os
from absl.testing import absltest
from absl.testing import parameterized
from mediapipe.python._framework_bindings import image as image_module
from mediapipe.tasks.python.core import base_options as base_options_module
from mediapipe.tasks.python.components.containers import rect
from mediapipe.tasks.python.test import test_utils
from mediapipe.tasks.python.vision import face_stylizer
from mediapipe.tasks.python.vision.core import image_processing_options as image_processing_options_module
_BaseOptions = base_options_module.BaseOptions
_Rect = rect.Rect
_Image = image_module.Image
_FaceStylizer = face_stylizer.FaceStylizer
_FaceStylizerOptions = face_stylizer.FaceStylizerOptions
_ImageProcessingOptions = image_processing_options_module.ImageProcessingOptions
_MODEL = 'face_stylizer_color_ink.task'
_LARGE_FACE_IMAGE = "portrait.jpg"
_MODEL_IMAGE_SIZE = 256
_TEST_DATA_DIR = 'mediapipe/tasks/testdata/vision'
class ModelFileType(enum.Enum):
FILE_CONTENT = 1
FILE_NAME = 2
class FaceStylizerTest(parameterized.TestCase):
def setUp(self):
super().setUp()
self.test_image = _Image.create_from_file(
test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)))
self.model_path = test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, _MODEL))
def test_create_from_file_succeeds_with_valid_model_path(self):
# Creates with default option and valid model file successfully.
with _FaceStylizer.create_from_model_path(self.model_path) as stylizer:
self.assertIsInstance(stylizer, _FaceStylizer)
def test_create_from_options_succeeds_with_valid_model_path(self):
# Creates with options containing model file successfully.
base_options = _BaseOptions(model_asset_path=self.model_path)
options = _FaceStylizerOptions(base_options=base_options)
with _FaceStylizer.create_from_options(options) as stylizer:
self.assertIsInstance(stylizer, _FaceStylizer)
def test_create_from_options_fails_with_invalid_model_path(self):
with self.assertRaisesRegex(
RuntimeError, 'Unable to open file at /path/to/invalid/model.tflite'):
base_options = _BaseOptions(
model_asset_path='/path/to/invalid/model.tflite')
options = _FaceStylizerOptions(base_options=base_options)
_FaceStylizer.create_from_options(options)
def test_create_from_options_succeeds_with_valid_model_content(self):
# Creates with options containing model content successfully.
with open(self.model_path, 'rb') as f:
base_options = _BaseOptions(model_asset_buffer=f.read())
options = _FaceStylizerOptions(base_options=base_options)
stylizer = _FaceStylizer.create_from_options(options)
self.assertIsInstance(stylizer, _FaceStylizer)
@parameterized.parameters(
(ModelFileType.FILE_NAME, _LARGE_FACE_IMAGE),
(ModelFileType.FILE_CONTENT, _LARGE_FACE_IMAGE)
)
def test_stylize(self, model_file_type, image_file_name):
# Load the test image.
self.test_image = _Image.create_from_file(
test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, image_file_name)))
# Creates stylizer.
if model_file_type is ModelFileType.FILE_NAME:
base_options = _BaseOptions(model_asset_path=self.model_path)
elif model_file_type is ModelFileType.FILE_CONTENT:
with open(self.model_path, 'rb') as f:
model_content = f.read()
base_options = _BaseOptions(model_asset_buffer=model_content)
else:
# Should never happen
raise ValueError('model_file_type is invalid.')
options = _FaceStylizerOptions(base_options=base_options)
stylizer = _FaceStylizer.create_from_options(options)
# Performs face stylization on the input.
stylized_image = stylizer.stylize(self.test_image)
self.assertIsInstance(stylized_image, _Image)
# Closes the stylizer explicitly when the stylizer is not used in
# a context.
stylizer.close()
@parameterized.parameters(
(ModelFileType.FILE_NAME, _LARGE_FACE_IMAGE),
(ModelFileType.FILE_CONTENT, _LARGE_FACE_IMAGE)
)
def test_stylize_in_context(self, model_file_type, image_file_name):
# Load the test image.
self.test_image = _Image.create_from_file(
test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, image_file_name)))
# Creates stylizer.
if model_file_type is ModelFileType.FILE_NAME:
base_options = _BaseOptions(model_asset_path=self.model_path)
elif model_file_type is ModelFileType.FILE_CONTENT:
with open(self.model_path, 'rb') as f:
model_content = f.read()
base_options = _BaseOptions(model_asset_buffer=model_content)
else:
# Should never happen
raise ValueError('model_file_type is invalid.')
options = _FaceStylizerOptions(base_options=base_options)
with _FaceStylizer.create_from_options(options) as stylizer:
# Performs face stylization on the input.
stylized_image = stylizer.stylize(self.test_image)
self.assertIsInstance(stylized_image, _Image)
self.assertEqual(stylized_image.width, _MODEL_IMAGE_SIZE)
self.assertEqual(stylized_image.height, _MODEL_IMAGE_SIZE)
def test_stylize_succeeds_with_region_of_interest(self):
base_options = _BaseOptions(model_asset_path=self.model_path)
options = _FaceStylizerOptions(base_options=base_options)
with _FaceStylizer.create_from_options(options) as stylizer:
# Load the test image.
test_image = _Image.create_from_file(
test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)
)
)
# Region-of-interest around the face.
roi = _Rect(left=0.32, top=0.02, right=0.67, bottom=0.32)
image_processing_options = _ImageProcessingOptions(roi)
# Performs face stylization on the input.
stylized_image = stylizer.stylize(test_image, image_processing_options)
self.assertIsInstance(stylized_image, _Image)
self.assertEqual(stylized_image.width, _MODEL_IMAGE_SIZE)
self.assertEqual(stylized_image.height, _MODEL_IMAGE_SIZE)
def test_stylize_succeeds_with_no_face_detected(self):
base_options = _BaseOptions(model_asset_path=self.model_path)
options = _FaceStylizerOptions(base_options=base_options)
with _FaceStylizer.create_from_options(options) as stylizer:
# Load the test image.
test_image = _Image.create_from_file(
test_utils.get_test_data_path(
os.path.join(_TEST_DATA_DIR, _LARGE_FACE_IMAGE)
)
)
# Region-of-interest that doesn't contain a human face.
roi = _Rect(left=0.1, top=0.1, right=0.2, bottom=0.2)
image_processing_options = _ImageProcessingOptions(roi)
# Performs face stylization on the input.
stylized_image = stylizer.stylize(test_image, image_processing_options)
self.assertIsNone(stylized_image)
if __name__ == '__main__':
absltest.main()

View File

@ -186,6 +186,7 @@ filegroup(
"face_detection_short_range.tflite", "face_detection_short_range.tflite",
"face_landmarker.task", "face_landmarker.task",
"face_landmarker_v2.task", "face_landmarker_v2.task",
"face_stylizer_color_ink.task",
"hair_segmentation.tflite", "hair_segmentation.tflite",
"hand_landmark_full.tflite", "hand_landmark_full.tflite",
"hand_landmark_lite.tflite", "hand_landmark_lite.tflite",