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from typing import Any, List, Callable
import cv2
import insightface
import threading
import roop.globals
import roop.processors.frame.core
from roop.face_util import get_first_face, get_all_faces
from roop.typing import Face, Frame
from roop.utilities import conditional_download, resolve_relative_path, is_image, is_video, compute_cosine_distance, get_destfilename_from_path
FACE_SWAPPER = None
THREAD_LOCK = threading.Lock()
NAME = 'ROOP.FACE-SWAPPER'
DIST_THRESHOLD = 0.65
def get_face_swapper() -> Any:
global FACE_SWAPPER
with THREAD_LOCK:
if FACE_SWAPPER is None:
model_path = resolve_relative_path('../models/inswapper_128.onnx')
FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=roop.globals.execution_providers)
return FACE_SWAPPER
def pre_check() -> bool:
download_directory_path = resolve_relative_path('../models')
conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/inswapper_128.onnx'])
return True
def pre_start() -> bool:
return True
def post_process() -> None:
global FACE_SWAPPER
FACE_SWAPPER = None
def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)
def process_frame(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
global DIST_THRESHOLD
if roop.globals.many_faces:
many_faces = get_all_faces(temp_frame)
if many_faces is not None:
for target_face in many_faces:
if target_face['det_score'] > 0.65:
temp_frame = swap_face(source_face, target_face, temp_frame)
else:
if target_face:
target_embedding = target_face.embedding
many_faces = get_all_faces(temp_frame)
target_face = None
for dest_face in many_faces:
dest_embedding = dest_face.embedding
if compute_cosine_distance(target_embedding, dest_embedding) <= DIST_THRESHOLD:
target_face = dest_face
break
if target_face:
temp_frame = swap_face(source_face, target_face, temp_frame)
return temp_frame
target_face = get_first_face(temp_frame)
if target_face is not None:
temp_frame = swap_face(source_face, target_face, temp_frame)
return temp_frame
def process_frames(is_batch: bool, source_face: Face, target_face: Face, temp_frame_paths: List[str], update: Callable[[], None]) -> None:
for temp_frame_path in temp_frame_paths:
temp_frame = cv2.imread(temp_frame_path)
if temp_frame is not None:
result = process_frame(source_face, target_face, temp_frame)
if result is not None:
if is_batch:
tf = get_destfilename_from_path(temp_frame_path, roop.globals.output_path, '_fake.png')
cv2.imwrite(tf, result)
else:
cv2.imwrite(temp_frame_path, result)
if update:
update()
def process_image(source_face: Any, target_face: Any, target_path: str, output_path: str) -> None:
global DIST_THRESHOLD
target_frame = cv2.imread(target_path)
if target_frame is not None:
result = process_frame(source_face, target_face, target_frame)
if result is not None:
cv2.imwrite(output_path, result)
def process_video(source_face: Any, target_face: Any, temp_frame_paths: List[str]) -> None:
global DIST_THRESHOLD
roop.processors.frame.core.process_video(source_face, target_face, temp_frame_paths, process_frames)
def process_batch_images(source_face: Any, target_face: Any, temp_frame_paths: List[str]) -> None:
global DIST_THRESHOLD
roop.processors.frame.core.process_batch(source_face, target_face, temp_frame_paths, process_frames)
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