Spaces:
Running
Running
File size: 1,682 Bytes
0bc8459 af24524 0bc8459 af24524 0bc8459 af24524 0bc8459 af24524 0bc8459 af24524 0bc8459 af24524 0bc8459 af24524 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
import threading
from typing import Any, List, Optional
import insightface
import roop.globals
from roop.typing import Frame
FACE_ANALYSER = None
THREAD_LOCK = threading.Lock()
def get_face_analyser() -> Any:
"""
Initialize and return the face analyser.
This function ensures that the face analyser is initialized only once,
using a thread-safe mechanism.
Returns:
Any: An instance of the FaceAnalysis class from insightface.
"""
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, det_size=(640, 640))
return FACE_ANALYSER
def get_one_face(frame: Frame) -> Optional[Any]:
"""
Extract the face with the smallest bounding box from the given frame.
Args:
frame (Frame): The image or video frame to analyze.
Returns:
Optional[Any]: The face with the smallest bounding box or None if no face is found.
"""
faces = get_face_analyser().get(frame)
if not faces:
return None
return min(faces, key=lambda x: x.bbox[0])
def get_many_faces(frame: Frame) -> List[Any]:
"""
Extract all detected faces from the given frame.
Args:
frame (Frame): The image or video frame to analyze.
Returns:
List[Any]: A list of detected faces or an empty list if no faces are found.
"""
try:
return get_face_analyser().get(frame)
except Exception as e:
print(f"Error getting faces: {e}")
return []
|