| 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 |
|
|