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from typing import Any, List, Callable |
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import cv2 |
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import insightface |
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import threading |
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import DeepFakeAI.globals |
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import DeepFakeAI.processors.frame.core as frame_processors |
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from DeepFakeAI import wording |
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from DeepFakeAI.core import update_status |
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from DeepFakeAI.face_analyser import get_one_face, get_many_faces, find_similar_faces |
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from DeepFakeAI.face_reference import get_face_reference, set_face_reference |
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from DeepFakeAI.typing import Face, Frame |
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from DeepFakeAI.utilities import conditional_download, resolve_relative_path, is_image, is_video |
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FRAME_PROCESSOR = None |
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THREAD_LOCK = threading.Lock() |
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NAME = 'FACEFUSION.FRAME_PROCESSOR.FACE_SWAPPER' |
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def get_frame_processor() -> Any: |
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global FRAME_PROCESSOR |
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with THREAD_LOCK: |
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if FRAME_PROCESSOR is None: |
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model_path = resolve_relative_path('../.assets/models/inswapper_128.onnx') |
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FRAME_PROCESSOR = insightface.model_zoo.get_model(model_path, providers = DeepFakeAI.globals.execution_providers) |
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return FRAME_PROCESSOR |
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def clear_frame_processor() -> None: |
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global FRAME_PROCESSOR |
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FRAME_PROCESSOR = None |
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def pre_check() -> bool: |
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download_directory_path = resolve_relative_path('../.assets/models') |
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conditional_download(download_directory_path, ['https://github.com/DeepFakeAI/DeepFakeAI-assets/releases/download/models/inswapper_128.onnx']) |
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return True |
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def pre_process() -> bool: |
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if not is_image(DeepFakeAI.globals.source_path): |
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update_status(wording.get('select_image_source') + wording.get('exclamation_mark'), NAME) |
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return False |
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elif not get_one_face(cv2.imread(DeepFakeAI.globals.source_path)): |
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update_status(wording.get('no_source_face_detected') + wording.get('exclamation_mark'), NAME) |
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return False |
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if not is_image(DeepFakeAI.globals.target_path) and not is_video(DeepFakeAI.globals.target_path): |
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update_status(wording.get('select_image_or_video_target') + wording.get('exclamation_mark'), NAME) |
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return False |
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return True |
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def post_process() -> None: |
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clear_frame_processor() |
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def swap_face(source_face : Face, target_face : Face, temp_frame : Frame) -> Frame: |
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return get_frame_processor().get(temp_frame, target_face, source_face, paste_back = True) |
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def process_frame(source_face : Face, reference_face : Face, temp_frame : Frame) -> Frame: |
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if 'reference' in DeepFakeAI.globals.face_recognition: |
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similar_faces = find_similar_faces(temp_frame, reference_face, DeepFakeAI.globals.reference_face_distance) |
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if similar_faces: |
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for similar_face in similar_faces: |
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temp_frame = swap_face(source_face, similar_face, temp_frame) |
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if 'many' in DeepFakeAI.globals.face_recognition: |
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many_faces = get_many_faces(temp_frame) |
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if many_faces: |
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for target_face in many_faces: |
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temp_frame = swap_face(source_face, target_face, temp_frame) |
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return temp_frame |
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def process_frames(source_path : str, temp_frame_paths : List[str], update: Callable[[], None]) -> None: |
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source_face = get_one_face(cv2.imread(source_path)) |
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reference_face = get_face_reference() if 'reference' in DeepFakeAI.globals.face_recognition else None |
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for temp_frame_path in temp_frame_paths: |
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temp_frame = cv2.imread(temp_frame_path) |
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result_frame = process_frame(source_face, reference_face, temp_frame) |
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cv2.imwrite(temp_frame_path, result_frame) |
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if update: |
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update() |
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def process_image(source_path : str, target_path : str, output_path : str) -> None: |
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source_face = get_one_face(cv2.imread(source_path)) |
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target_frame = cv2.imread(target_path) |
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reference_face = get_one_face(target_frame, DeepFakeAI.globals.reference_face_position) if 'reference' in DeepFakeAI.globals.face_recognition else None |
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result_frame = process_frame(source_face, reference_face, target_frame) |
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cv2.imwrite(output_path, result_frame) |
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def process_video(source_path : str, temp_frame_paths : List[str]) -> None: |
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conditional_set_face_reference(temp_frame_paths) |
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frame_processors.process_video(source_path, temp_frame_paths, process_frames) |
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def conditional_set_face_reference(temp_frame_paths : List[str]) -> None: |
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if 'reference' in DeepFakeAI.globals.face_recognition and not get_face_reference(): |
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reference_frame = cv2.imread(temp_frame_paths[DeepFakeAI.globals.reference_frame_number]) |
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reference_face = get_one_face(reference_frame, DeepFakeAI.globals.reference_face_position) |
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set_face_reference(reference_face) |
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