Spaces:
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import threading | |
from typing import Any, Optional, List | |
import insightface | |
import numpy | |
import roop.globals | |
from roop.typing import Frame, Face | |
FACE_ANALYSER = None | |
THREAD_LOCK = threading.Lock() | |
def get_face_analyser() -> Any: | |
global FACE_ANALYSER | |
with THREAD_LOCK: | |
if FACE_ANALYSER is None: | |
FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=roop.globals.execution_providers) | |
FACE_ANALYSER.prepare(ctx_id=0) | |
return FACE_ANALYSER | |
def clear_face_analyser() -> Any: | |
global FACE_ANALYSER | |
FACE_ANALYSER = None | |
def get_one_face(frame: Frame, position: int = 0) -> Optional[Face]: | |
many_faces = get_many_faces(frame) | |
if many_faces: | |
try: | |
return many_faces[position] | |
except IndexError: | |
return many_faces[-1] | |
return None | |
def get_many_faces(frame: Frame) -> Optional[List[Face]]: | |
try: | |
return get_face_analyser().get(frame) | |
except ValueError: | |
return None | |
def find_similar_face(frame: Frame, reference_face: Face) -> Optional[Face]: | |
many_faces = get_many_faces(frame) | |
if many_faces: | |
for face in many_faces: | |
if hasattr(face, 'normed_embedding') and hasattr(reference_face, 'normed_embedding'): | |
distance = numpy.sum(numpy.square(face.normed_embedding - reference_face.normed_embedding)) | |
if distance < roop.globals.similar_face_distance: | |
return face | |
return None | |