mirror of
https://github.com/facefusion/facefusion.git
synced 2026-06-02 02:41:38 +02:00
Henry Ruhs
0f5f75ba51
* clean testing suite * clean testing suite part2 * clean testing suite part3 * add todos * extend testing suite and kill some mutants * fix hashes * fix lint * fix test * fix test
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
import subprocess
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import pytest
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from facefusion import face_classifier, face_detector, face_landmarker, face_recognizer, state_manager
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from facefusion.download import conditional_download
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from facefusion.face_analyser import get_many_faces
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from facefusion.vision import read_static_image
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from .assert_helper import get_test_example_file, get_test_examples_directory
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@pytest.fixture(scope = 'module', autouse = True)
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def before_all() -> None:
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state_manager.init_item('execution_device_ids', [ 0 ])
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state_manager.init_item('execution_providers', [ 'cpu' ])
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state_manager.init_item('download_providers', [ 'github' ])
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state_manager.init_item('face_detector_angles', [ 0 ])
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state_manager.init_item('face_detector_model', 'many')
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state_manager.init_item('face_detector_score', 0.5)
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state_manager.init_item('face_landmarker_model', 'many')
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state_manager.init_item('face_landmarker_score', 0.5)
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face_classifier.pre_check()
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face_landmarker.pre_check()
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face_recognizer.pre_check()
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conditional_download(get_test_examples_directory(),
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[
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'https://github.com/facefusion/facefusion-assets/releases/download/examples-3.0.0/source.jpg'
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])
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subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.8:ih*0.8', get_test_example_file('source-80crop.jpg') ])
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subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.7:ih*0.7', get_test_example_file('source-70crop.jpg') ])
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subprocess.run([ 'ffmpeg', '-i', get_test_example_file('source.jpg'), '-vf', 'crop=iw*0.6:ih*0.6', get_test_example_file('source-60crop.jpg') ])
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@pytest.fixture(autouse = True)
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def before_each() -> None:
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face_classifier.clear_inference_pool()
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face_detector.clear_inference_pool()
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face_landmarker.clear_inference_pool()
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face_recognizer.clear_inference_pool()
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@pytest.mark.parametrize('face_detector_model, face_detector_size',
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[
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('retinaface', '320x320'),
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('scrfd', '320x320'),
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('yolo_face', '640x640'),
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('yunet', '640x640')
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])
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def test_get_one_face(face_detector_model : str, face_detector_size : str) -> None:
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state_manager.init_item('face_detector_model', face_detector_model)
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state_manager.init_item('face_detector_size', face_detector_size)
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state_manager.init_item('face_detector_margin', (0, 0, 0, 0))
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face_detector.pre_check()
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source_paths =\
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[
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get_test_example_file('source.jpg'),
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get_test_example_file('source-80crop.jpg'),
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get_test_example_file('source-70crop.jpg'),
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get_test_example_file('source-60crop.jpg')
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]
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for source_path in source_paths:
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source_frame = read_static_image(source_path)
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many_faces = get_many_faces([ source_frame ])
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assert len(many_faces) == 1
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def test_get_many_faces() -> None:
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source_path = get_test_example_file('source.jpg')
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source_frame = read_static_image(source_path)
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many_faces = get_many_faces([ source_frame, source_frame, source_frame ])
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assert len(many_faces) == 3
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