| import threading |
| from typing import Any, Optional, List |
| import insightface |
| import numpy |
|
|
| import DeepFakeAI.globals |
| from DeepFakeAI.typing import Frame, Face, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender |
|
|
| 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 = DeepFakeAI.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) -> List[Face]: |
| try: |
| faces = get_face_analyser().get(frame) |
| if DeepFakeAI.globals.face_analyser_direction: |
| faces = sort_by_direction(faces, DeepFakeAI.globals.face_analyser_direction) |
| if DeepFakeAI.globals.face_analyser_age: |
| faces = filter_by_age(faces, DeepFakeAI.globals.face_analyser_age) |
| if DeepFakeAI.globals.face_analyser_gender: |
| faces = filter_by_gender(faces, DeepFakeAI.globals.face_analyser_gender) |
| return faces |
| except (AttributeError, ValueError): |
| return [] |
|
|
|
|
| def find_similar_faces(frame : Frame, reference_face : Face, face_distance : float) -> List[Face]: |
| many_faces = get_many_faces(frame) |
| similar_faces = [] |
| if many_faces: |
| for face in many_faces: |
| if hasattr(face, 'normed_embedding') and hasattr(reference_face, 'normed_embedding'): |
| current_face_distance = numpy.sum(numpy.square(face.normed_embedding - reference_face.normed_embedding)) |
| if current_face_distance < face_distance: |
| similar_faces.append(face) |
| return similar_faces |
|
|
|
|
| def sort_by_direction(faces : List[Face], direction : FaceAnalyserDirection) -> List[Face]: |
| if direction == 'left-right': |
| return sorted(faces, key = lambda face: face['bbox'][0]) |
| if direction == 'right-left': |
| return sorted(faces, key = lambda face: face['bbox'][0], reverse = True) |
| if direction == 'top-bottom': |
| return sorted(faces, key = lambda face: face['bbox'][1]) |
| if direction == 'bottom-top': |
| return sorted(faces, key = lambda face: face['bbox'][1], reverse = True) |
| if direction == 'small-large': |
| return sorted(faces, key = lambda face: (face['bbox'][2] - face['bbox'][0]) * (face['bbox'][3] - face['bbox'][1])) |
| if direction == 'large-small': |
| return sorted(faces, key = lambda face: (face['bbox'][2] - face['bbox'][0]) * (face['bbox'][3] - face['bbox'][1]), reverse = True) |
| return faces |
|
|
|
|
| def filter_by_age(faces : List[Face], age : FaceAnalyserAge) -> List[Face]: |
| filter_faces = [] |
| for face in faces: |
| if face['age'] < 13 and age == 'child': |
| filter_faces.append(face) |
| elif face['age'] < 19 and age == 'teen': |
| filter_faces.append(face) |
| elif face['age'] < 60 and age == 'adult': |
| filter_faces.append(face) |
| elif face['age'] > 59 and age == 'senior': |
| filter_faces.append(face) |
| return filter_faces |
|
|
|
|
| def filter_by_gender(faces : List[Face], gender : FaceAnalyserGender) -> List[Face]: |
| filter_faces = [] |
| for face in faces: |
| if face['gender'] == 1 and gender == 'male': |
| filter_faces.append(face) |
| if face['gender'] == 0 and gender == 'female': |
| filter_faces.append(face) |
| return filter_faces |
|
|
|
|
| def get_faces_total(frame : Frame) -> int: |
| return len(get_many_faces(frame)) |
|
|
