Initial commit

facefusion/face_analyser.py

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+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))