from typing import Any, List import cv2 import insightface import threading import modules.globals import modules.processors.frame.core from modules.core import update_status from modules.face_analyser import get_one_face, get_many_faces, default_source_face from modules.typing import Face, Frame from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video from modules.cluster_analysis import find_closest_centroid FACE_SWAPPER = None THREAD_LOCK = threading.Lock() NAME = 'DLC.FACE-SWAPPER' def pre_check() -> bool: download_directory_path = resolve_relative_path('../models') conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx']) return True def pre_start() -> bool: if not modules.globals.map_faces and not is_image(modules.globals.source_path): update_status('Select an image for source path.', NAME) return False elif not modules.globals.map_faces and not get_one_face(cv2.imread(modules.globals.source_path)): update_status('No face in source path detected.', NAME) return False if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path): update_status('Select an image or video for target path.', NAME) return False return True def get_face_swapper() -> Any: global FACE_SWAPPER with THREAD_LOCK: if FACE_SWAPPER is None: model_path = resolve_relative_path('../models/inswapper_128_fp16.onnx') FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers) return FACE_SWAPPER 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, temp_frame: Frame) -> Frame: # Ensure the frame is in RGB format if color correction is enabled if modules.globals.color_correction: temp_frame = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB) if modules.globals.many_faces: 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) else: target_face = get_one_face(temp_frame) if target_face: temp_frame = swap_face(source_face, target_face, temp_frame) return temp_frame def process_frame_v2(temp_frame: Frame, temp_frame_path: str = "") -> Frame: if is_image(modules.globals.target_path): if modules.globals.many_faces: source_face = default_source_face() for map in modules.globals.souce_target_map: target_face = map['target']['face'] temp_frame = swap_face(source_face, target_face, temp_frame) elif not modules.globals.many_faces: for map in modules.globals.souce_target_map: if "source" in map: source_face = map['source']['face'] target_face = map['target']['face'] temp_frame = swap_face(source_face, target_face, temp_frame) elif is_video(modules.globals.target_path): if modules.globals.many_faces: source_face = default_source_face() for map in modules.globals.souce_target_map: target_frame = [f for f in map['target_faces_in_frame'] if f['location'] == temp_frame_path] for frame in target_frame: for target_face in frame['faces']: temp_frame = swap_face(source_face, target_face, temp_frame) elif not modules.globals.many_faces: for map in modules.globals.souce_target_map: if "source" in map: target_frame = [f for f in map['target_faces_in_frame'] if f['location'] == temp_frame_path] source_face = map['source']['face'] for frame in target_frame: for target_face in frame['faces']: temp_frame = swap_face(source_face, target_face, temp_frame) else: detected_faces = get_many_faces(temp_frame) if modules.globals.many_faces: if detected_faces: source_face = default_source_face() for target_face in detected_faces: temp_frame = swap_face(source_face, target_face, temp_frame) elif not modules.globals.many_faces: if detected_faces: if len(detected_faces) <= len(modules.globals.simple_map['target_embeddings']): for detected_face in detected_faces: closest_centroid_index, _ = find_closest_centroid(modules.globals.simple_map['target_embeddings'], detected_face.normed_embedding) temp_frame = swap_face(modules.globals.simple_map['source_faces'][closest_centroid_index], detected_face, temp_frame) else: detected_faces_centroids = [] for face in detected_faces: detected_faces_centroids.append(face.normed_embedding) i = 0 for target_embedding in modules.globals.simple_map['target_embeddings']: closest_centroid_index, _ = find_closest_centroid(detected_faces_centroids, target_embedding) temp_frame = swap_face(modules.globals.simple_map['source_faces'][i], detected_faces[closest_centroid_index], temp_frame) i += 1 return temp_frame def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None: if not modules.globals.map_faces: source_face = get_one_face(cv2.imread(source_path)) for temp_frame_path in temp_frame_paths: temp_frame = cv2.imread(temp_frame_path) try: result = process_frame(source_face, temp_frame) cv2.imwrite(temp_frame_path, result) except Exception as exception: print(exception) pass if progress: progress.update(1) else: for temp_frame_path in temp_frame_paths: temp_frame = cv2.imread(temp_frame_path) try: result = process_frame_v2(temp_frame, temp_frame_path) cv2.imwrite(temp_frame_path, result) except Exception as exception: print(exception) pass if progress: progress.update(1) def process_image(source_path: str, target_path: str, output_path: str) -> None: if not modules.globals.map_faces: source_face = get_one_face(cv2.imread(source_path)) target_frame = cv2.imread(target_path) result = process_frame(source_face, target_frame) cv2.imwrite(output_path, result) else: if modules.globals.many_faces: update_status('Many faces enabled. Using first source image. Progressing...', NAME) target_frame = cv2.imread(output_path) result = process_frame_v2(target_frame) cv2.imwrite(output_path, result) def process_video(source_path: str, temp_frame_paths: List[str]) -> None: if modules.globals.map_faces and modules.globals.many_faces: update_status('Many faces enabled. Using first source image. Progressing...', NAME) modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)