#!/usr/bin/env python3 import os import sys # single thread doubles cuda performance - needs to be set before torch import if any(arg.startswith('--execution-provider') for arg in sys.argv): os.environ['OMP_NUM_THREADS'] = '1' # reduce tensorflow log level os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import warnings from typing import List import platform import signal import shutil import argparse import onnxruntime import tensorflow import roop.globals import roop.metadata import roop.ui as ui import spaces from roop.predictor import predict_image, predict_video from roop.processors.frame.core import get_frame_processors_modules from roop.utilities import has_image_extension, is_image, is_video, detect_fps, create_video, extract_frames, get_temp_frame_paths, restore_audio, create_temp, move_temp, clean_temp, normalize_output_path warnings.filterwarnings('ignore', category=FutureWarning, module='insightface') warnings.filterwarnings('ignore', category=UserWarning, module='torchvision') @spaces.GPU def parse_args() -> None: signal.signal(signal.SIGINT, lambda signal_number, frame: destroy()) program = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog, max_help_position=100)) program.add_argument('-s', '--source', help='select an source image', dest='source_path') program.add_argument('-t', '--target', help='select an target image or video', dest='target_path') program.add_argument('-o', '--output', help='select output file or directory', dest='output_path') program.add_argument('--frame-processor', help='frame processors (choices: face_swapper, face_enhancer, ...)', dest='frame_processor', default=['face_swapper'], nargs='+') program.add_argument('--keep-fps', help='keep target fps', dest='keep_fps', action='store_true') program.add.add_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true') program.add.add.argument('--skip-audio', help='skip target audio', dest='skip_audio', action='store_true') program.add.argument('--many-faces', help='process every face', dest='many_faces', action='store_true') program.add.argument('--reference-face-position', help='position of the reference face', dest='reference_face_position', type=int, default=0) program.add.argument('--reference-frame-number', help='number of the reference frame', dest='reference_frame_number', type=int, default=0) program.add.argument('--similar-face-distance', help='face distance used for recognition', dest='similar_face_distance', type=float, default=0.85) program.add.argument('--temp-frame-format', help='image format used for frame extraction', dest='temp_frame_format', default='png', choices=['jpg', 'png']) program.add.argument('--temp-frame-quality', help='image quality used for frame extraction', dest='temp_frame_quality', type=int, default=0, choices=range(101), metavar='[0-100]') program.add.argument('--output-video-encoder', help='encoder used for the output video', dest='output_video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc']) program.add.argument('--output-video-quality', help='quality used for the output video', dest='output_video_quality', type=int, default=35, choices=range(101), metavar='[0-100]') program.add.argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int) program.add.argument('--execution-provider', help='available execution provider (choices: cpu, cuda, ...)', dest='execution_provider', default=['cuda'], choices=suggest_execution_providers(), nargs='+') program.add.argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=suggest_execution_threads()) program.add.argument('-v', '--version', action='version', version=f'{roop.metadata.name} {roop.metadata.version}') args = program.parse_args() roop.globals.source_path = args.source_path roop.globals.target_path = args.target_path roop.globals.output_path = normalize_output_path(roop.globals.source_path, roop.globals.target_path, args.output_path) roop.globals.headless = roop.globals.source_path is not None and roop.globals.target_path is not None and roop.globals.output_path is not None roop.globals.frame_processors = args.frame_processor roop.globals.keep_fps = args.keep_fps roop.globals.keep_frames = args.keep_frames roop.globals.skip_audio = args.skip_audio roop.globals.many_faces = args.many_faces roop.globals.reference_face_position = args.reference_face_position roop.globals.reference_frame_number = args.reference_frame_number roop.globals.similar_face_distance = args.similar_face_distance roop.globals.temp_frame_format = args.temp_frame_format roop.globals.temp_frame_quality = args.temp_frame_quality roop.globals.output_video_encoder = args.output_video_encoder roop.globals.output_video_quality = args.output_video_quality roop.globals.max_memory = args.max_memory roop.globals.execution_providers = decode_execution_providers(args.execution_provider) roop.globals.execution_threads = args.execution_threads def encode_execution_providers(execution_providers: List[str]) -> List[str]: return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers] def decode_execution_providers(execution_providers: List[str]) -> List[str]: return [provider for provider, encoded_execution_provider in zip(onnxruntime.get_available_providers(), encode_execution_providers(onnxruntime.get_available_providers())) if any(execution_provider in encoded_execution_provider for execution_provider in execution_providers)] def suggest_execution_providers() -> List[str]: return encode_execution_providers(onnxruntime.get_available_providers()) def suggest_execution_threads() -> int: if 'CUDAExecutionProvider' in onnxruntime.get_available_providers(): return 8 return 1 def limit_resources() -> None: # prevent tensorflow memory leak gpus = tensorflow.config.experimental.list_physical_devices('GPU') for gpu in gpus: tensorflow.config.experimental.set_virtual_device_configuration(gpu, [ tensorflow.config.experimental.VirtualDeviceConfiguration(memory_limit=1024) ]) # limit memory usage if roop.globals.max_memory: memory = roop.globals.max_memory * 1024 ** 3 if platform.system().lower() == 'darwin': memory = roop.globals.max_memory * 1024 ** 6 if platform.system().lower() == 'windows': import ctypes kernel32 = ctypes.windll.kernel32 # type: ignore[attr-defined] kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory)) else: import resource resource.setrlimit(resource.RLIMIT_DATA, (memory, memory)) def pre_check() -> bool: if sys.version_info < (3, 9): update_status('Python version is not supported - please upgrade to 3.9 or higher.') return False if not shutil.which('ffmpeg'): update_status('ffmpeg is not installed.') return False return True def update_status(message: str, scope: str = 'ROOP.CORE') -> None: print(f'[{scope}] {message}') if not roop.globals.headless: ui.update_status(message) def start() -> None: for frame_processor in get_frame_processors_modules(roop.globals.frame_processors): if not frame_processor.pre_start(): return # process image to image if has_image_extension(roop.globals.target_path): if predict_image(roop.globals.target_path): destroy() shutil.copy2(roop.globals.target_path, roop.globals.output_path) # process frame for frame_processor in get_frame_processors_modules(roop.globals.frame_processors): update_status('Progressing...', frame_processor.NAME) frame_processor.process_image(roop.globals.source_path, roop.globals.output_path, roop.globals.output_path) frame_processor.post_process() # validate image if is_image(roop.globals.target_path): update_status('Processing to image succeed!') else: update_status('Processing to image failed!') return # process image to videos if predict_video(roop.globals.target_path): destroy() update_status('Creating temporary resources...') create_temp(roop.globals.target_path) # extract frames if roop.globals.keep_fps: fps = detect_fps(roop.globals.target_path) update_status(f'Extracting frames with {fps} FPS...') extract_frames(roop.globals.target_path, fps) else: update_status('Extracting frames with 30 FPS...') extract_frames(roop.globals.target_path) # process frame temp_frame_paths = get_temp_frame_paths(roop.globals.target_path) if temp_frame_paths: for frame_processor in get_frame_processors_modules(roop.globals.frame_processors): update_status('Progressing...', frame_processor.NAME) frame_processor.process_video(roop.globals.source_path, temp_frame_paths) frame_processor.post_process() else: update_status('Frames not found...') return # create video if roop.globals.keep_fps: fps = detect_fps(roop.globals.target_path) update_status(f'Creating video with {fps} FPS...') create_video(roop.globals.target_path, fps) else: update_status('Creating video with 30 FPS...') create_video(roop.globals.target_path) # handle audio if roop.globals.skip_audio: move_temp(roop.globals.target_path, roop.globals.output_path) update_status('Skipping audio...') else: if roop.globals.keep_fps: update_status('Restoring audio...') else: update_status('Restoring audio might cause issues as fps are not kept...') restore_audio(roop.globals.target_path, roop.globals.output_path) # clean temp update_status('Cleaning temporary resources...') clean_temp(roop.globals.target_path) # validate video if is_video(roop.globals.target_path): update_status('Processing to video succeed!') else: update_status('Processing to video failed!') def destroy() -> None: if roop.globals.target_path: clean_temp(roop.globals.target_path) sys.exit() def run() -> None: parse_args() if not pre_check(): return for frame_processor in get_frame_processors_modules(roop.globals.frame_processors): if not frame_processor.pre_check(): return limit_resources() if roop.globals.headless: start() else: window = ui.init(start, destroy) window.mainloop()