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import subprocess |
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import pytest |
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import facefusion.globals |
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from facefusion.download import conditional_download |
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from facefusion.face_analyser import pre_check, clear_face_analyser, get_one_face |
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from facefusion.my_typing import Face |
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from facefusion.vision import read_static_image |
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@pytest.fixture(scope = 'module', autouse = True) |
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def before_all() -> None: |
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conditional_download('.assets/examples', |
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[ |
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'https://github.com/facefusion/facefusion-assets/releases/download/examples/source.jpg' |
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]) |
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subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.8:ih*0.8', '.assets/examples/source-80crop.jpg' ]) |
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subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.7:ih*0.7', '.assets/examples/source-70crop.jpg' ]) |
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subprocess.run([ 'ffmpeg', '-i', '.assets/examples/source.jpg', '-vf', 'crop=iw*0.6:ih*0.6', '.assets/examples/source-60crop.jpg' ]) |
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@pytest.fixture(autouse = True) |
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def before_each() -> None: |
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facefusion.globals.face_detector_score = 0.5 |
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facefusion.globals.face_landmarker_score = 0.5 |
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facefusion.globals.face_recognizer_model = 'arcface_inswapper' |
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clear_face_analyser() |
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def test_get_one_face_with_retinaface() -> None: |
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facefusion.globals.face_detector_model = 'retinaface' |
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facefusion.globals.face_detector_size = '320x320' |
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pre_check() |
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source_paths =\ |
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[ |
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'.assets/examples/source.jpg', |
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'.assets/examples/source-80crop.jpg', |
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'.assets/examples/source-70crop.jpg', |
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'.assets/examples/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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face = get_one_face(source_frame) |
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assert isinstance(face, Face) |
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def test_get_one_face_with_scrfd() -> None: |
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facefusion.globals.face_detector_model = 'scrfd' |
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facefusion.globals.face_detector_size = '640x640' |
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pre_check() |
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source_paths =\ |
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[ |
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'.assets/examples/source.jpg', |
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'.assets/examples/source-80crop.jpg', |
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'.assets/examples/source-70crop.jpg', |
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'.assets/examples/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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face = get_one_face(source_frame) |
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assert isinstance(face, Face) |
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def test_get_one_face_with_yoloface() -> None: |
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facefusion.globals.face_detector_model = 'yoloface' |
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facefusion.globals.face_detector_size = '640x640' |
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pre_check() |
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source_paths =\ |
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[ |
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'.assets/examples/source.jpg', |
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'.assets/examples/source-80crop.jpg', |
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'.assets/examples/source-70crop.jpg', |
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'.assets/examples/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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face = get_one_face(source_frame) |
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assert isinstance(face, Face) |
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def test_get_one_face_with_yunet() -> None: |
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facefusion.globals.face_detector_model = 'yunet' |
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facefusion.globals.face_detector_size = '640x640' |
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pre_check() |
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source_paths =\ |
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[ |
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'.assets/examples/source.jpg', |
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'.assets/examples/source-80crop.jpg', |
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'.assets/examples/source-70crop.jpg', |
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'.assets/examples/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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face = get_one_face(source_frame) |
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assert isinstance(face, Face) |
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