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import threading | |
from typing import Any | |
import insightface | |
import roop.globals | |
from roop.typing import Frame | |
import cv2 | |
from PIL import Image | |
from roop.capturer import get_video_frame | |
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=roop.globals.execution_providers) | |
FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640)) | |
return FACE_ANALYSER | |
def get_first_face(frame: Frame) -> Any: | |
faces = get_face_analyser().get(frame) | |
try: | |
return min(faces, key=lambda x: x.bbox[0]) | |
# return sorted(faces, reverse=True, key=lambda x: (x.bbox[2] - x.bbox[0]) * (x.bbox[3] - x.bbox[1]))[0] | |
except ValueError: | |
return None | |
def get_all_faces(frame: Frame) -> Any: | |
try: | |
faces = get_face_analyser().get(frame) | |
return sorted(faces, key = lambda x : x.bbox[0]) | |
except IndexError: | |
return None | |
def extract_face_images(source_filename, video_info): | |
face_data = [] | |
source_image = None | |
if video_info[0]: | |
frame = get_video_frame(source_filename, video_info[1]) | |
if frame is not None: | |
source_image = frame | |
else: | |
return face_data | |
else: | |
source_image = cv2.imread(source_filename) | |
faces = get_all_faces(source_image) | |
i = 0 | |
for face in faces: | |
(startX, startY, endX, endY) = face['bbox'].astype("int") | |
face_temp = source_image[startY:endY, startX:endX] | |
if face_temp.size < 1: | |
continue | |
i += 1 | |
face_data.append([face, face_temp]) | |
return face_data |