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face_swapper.py
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face_swapper.py
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from typing import Any, List, Callable
import cv2
import insightface
import threading
import roop.globals
import roop.processors.frame.core as frame_processors
from roop.core import update_status
from roop.face_analyser import get_one_face, get_many_faces, find_similar_faces
from roop.face_reference import get_face_reference, set_face_reference, clear_face_reference
from roop.typing import Face, Frame
from roop.utilities import conditional_download, resolve_relative_path, is_image, is_video
FRAME_PROCESSOR = None
THREAD_LOCK = threading.Lock()
NAME = 'ROOP.FRAME_PROCESSOR.FACE_SWAPPER'
def get_frame_processor() -> Any:
global FRAME_PROCESSOR
with THREAD_LOCK:
if FRAME_PROCESSOR is None:
model_path = resolve_relative_path('../models/inswapper_128.onnx')
FRAME_PROCESSOR = insightface.model_zoo.get_model(model_path, providers=roop.globals.execution_providers)
return FRAME_PROCESSOR
def clear_frame_processor() -> None:
global FRAME_PROCESSOR
FRAME_PROCESSOR = None
def pre_check() -> bool:
download_directory_path = resolve_relative_path('../models')
conditional_download(download_directory_path, ['https://huggingface.co/henryruhs/roop/resolve/main/inswapper_128.onnx'])
return True
def pre_start() -> bool:
if not is_image(roop.globals.source_path):
update_status('Select an image for source path.', NAME)
return False
elif not get_one_face(cv2.imread(roop.globals.source_path)):
update_status('No face in source path detected.', NAME)
return False
if not is_image(roop.globals.target_path) and not is_video(roop.globals.target_path):
update_status('Select an image or video for target path.', NAME)
return False
return True
def post_process() -> None:
clear_frame_processor()
clear_face_reference()
def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
return get_frame_processor().get(temp_frame, target_face, source_face, paste_back=True)
def process_frame(source_face: Face, reference_face: Face, temp_frame: Frame) -> Frame:
if 'reference' in roop.globals.face_recognition:
similar_faces = find_similar_faces(temp_frame, reference_face, roop.globals.reference_face_distance)
if similar_faces:
for similar_face in similar_faces:
temp_frame = swap_face(source_face, similar_face, temp_frame)
if 'many' in roop.globals.face_recognition:
many_faces = get_many_faces(temp_frame)
if many_faces:
for target_face in many_faces:
temp_frame = swap_face(source_face, target_face, temp_frame)
return temp_frame
def process_frames(source_path: str, temp_frame_paths: List[str], update: Callable[[], None]) -> None:
source_face = get_one_face(cv2.imread(source_path))
reference_face = get_face_reference() if 'reference' in roop.globals.face_recognition else None
for temp_frame_path in temp_frame_paths:
temp_frame = cv2.imread(temp_frame_path)
result_frame = process_frame(source_face, reference_face, temp_frame)
cv2.imwrite(temp_frame_path, result_frame)
if update:
update()
def process_image(source_path: str, target_path: str, output_path: str) -> None:
source_face = get_one_face(cv2.imread(source_path))
target_frame = cv2.imread(target_path)
reference_face = get_one_face(target_frame, roop.globals.reference_face_position) if 'reference' in roop.globals.face_recognition else None
result_frame = process_frame(source_face, reference_face, target_frame)
cv2.imwrite(output_path, result_frame)
def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
conditional_set_face_reference(temp_frame_paths)
frame_processors.process_video(source_path, temp_frame_paths, process_frames)
def conditional_set_face_reference(temp_frame_paths: List[str]) -> None:
if 'reference' in roop.globals.face_recognition and not get_face_reference():
reference_frame = cv2.imread(temp_frame_paths[roop.globals.reference_frame_number])
reference_face = get_one_face(reference_frame, roop.globals.reference_face_position)
set_face_reference(reference_face)