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Update roop/face_analyser.py
Browse files- roop/face_analyser.py +41 -10
roop/face_analyser.py
CHANGED
@@ -1,5 +1,5 @@
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import threading
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from typing import Any
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import insightface
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import roop.globals
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@@ -10,25 +10,56 @@ THREAD_LOCK = threading.Lock()
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def get_face_analyser() -> Any:
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global FACE_ANALYSER
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with THREAD_LOCK:
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if FACE_ANALYSER is None:
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FACE_ANALYSER = insightface.app.FaceAnalysis(
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FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
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return FACE_ANALYSER
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def get_one_face(frame: Frame) -> Any:
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return None
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try:
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return get_face_analyser().get(frame)
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except
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import threading
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from typing import Any, List, Optional
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import insightface
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import roop.globals
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def get_face_analyser() -> Any:
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"""
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Initialize and return the face analyser.
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This function ensures that the face analyser is initialized only once,
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using a thread-safe mechanism.
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Returns:
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Any: An instance of the FaceAnalysis class from insightface.
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"""
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global FACE_ANALYSER
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with THREAD_LOCK:
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if FACE_ANALYSER is None:
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FACE_ANALYSER = insightface.app.FaceAnalysis(
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name='buffalo_l',
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providers=roop.globals.execution_providers
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)
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FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
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return FACE_ANALYSER
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def get_one_face(frame: Frame) -> Optional[Any]:
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"""
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Extract the face with the smallest bounding box from the given frame.
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Args:
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frame (Frame): The image or video frame to analyze.
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Returns:
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Optional[Any]: The face with the smallest bounding box or None if no face is found.
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"""
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faces = get_face_analyser().get(frame)
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if not faces:
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return None
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return min(faces, key=lambda x: x.bbox[0])
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def get_many_faces(frame: Frame) -> List[Any]:
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"""
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Extract all detected faces from the given frame.
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Args:
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frame (Frame): The image or video frame to analyze.
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Returns:
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List[Any]: A list of detected faces or an empty list if no faces are found.
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"""
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try:
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return get_face_analyser().get(frame)
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except Exception as e:
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print(f"Error getting faces: {e}")
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return []
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