107 lines
3.4 KiB
Python
107 lines
3.4 KiB
Python
import threading
|
|
from typing import Any, Optional, List
|
|
import insightface
|
|
import numpy
|
|
|
|
import facefusion.globals
|
|
from facefusion.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 = facefusion.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 facefusion.globals.face_analyser_direction:
|
|
faces = sort_by_direction(faces, facefusion.globals.face_analyser_direction)
|
|
if facefusion.globals.face_analyser_age:
|
|
faces = filter_by_age(faces, facefusion.globals.face_analyser_age)
|
|
if facefusion.globals.face_analyser_gender:
|
|
faces = filter_by_gender(faces, facefusion.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))
|