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