import os import sys import warnings import platform import signal import shutil import argparse from typing import List # Set environment variables for CUDA performance and TensorFlow logging if any(arg.startswith('--execution-provider') for arg in sys.argv): os.environ['OMP_NUM_THREADS'] = '1' os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' import torch import onnxruntime import tensorflow import modules.globals import modules.metadata import modules.ui as ui from modules.processors.frame.core import get_frame_processors_modules from modules.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 ) # Filter warnings warnings.filterwarnings('ignore', category=FutureWarning, module='insightface') warnings.filterwarnings('ignore', category=UserWarning, module='torchvision') # Cross-platform resource management if platform.system() == 'Darwin' and 'ROCMExecutionProvider' in modules.globals.execution_providers: del torch def parse_args() -> None: signal.signal(signal.SIGINT, lambda signal_number, frame: destroy()) program = argparse.ArgumentParser() program.add_argument('-s', '--source', help='Select a source image', dest='source_path') program.add_argument('-t', '--target', help='Select a 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='Pipeline of frame processors', dest='frame_processor', default=['face_swapper'], choices=['face_swapper', 'face_enhancer', 'super_resolution'], nargs='+') program.add_argument('--keep-fps', help='Keep original fps', dest='keep_fps', action='store_true', default=False) program.add_argument('--keep-audio', help='Keep original audio', dest='keep_audio', action='store_true', default=True) program.add_argument('--keep-frames', help='Keep temporary frames', dest='keep_frames', action='store_true', default=False) program.add_argument('--many-faces', help='Process every face', dest='many_faces', action='store_true', default=False) program.add_argument('--video-encoder', help='Adjust output video encoder', dest='video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9']) program.add_argument('--video-quality', help='Adjust output video quality', dest='video_quality', type=int, default=18, choices=range(52), metavar='[0-51]') program.add_argument('--live-mirror', help='The live camera display as you see it in the front-facing camera frame', dest='live_mirror', action='store_true', default=False) program.add_argument('--live-resizable', help='The live camera frame is resizable', dest='live_resizable', action='store_true', default=False) program.add_argument('--max-memory', help='Maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory()) program.add_argument('--execution-provider', help='Execution provider', 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('--headless', help='Run in headless mode', dest='headless', default=False, action='store_true') program.add_argument('--enhancer-upscale-factor', help='Sets the upscale factor for the enhancer. Only applies if `face_enhancer` is set as a frame-processor', dest='enhancer_upscale_factor', type=int, default=1) program.add_argument('--source-image-scaling-factor', help='Set the upscale factor for source images', dest='source_image_scaling_factor', default=2, type=int) program.add_argument('-r', '--super-resolution-scale-factor', dest='super_resolution_scale_factor', help='Set the upscale factor for super resolution', default=4, choices=[2, 3, 4], type=int) program.add_argument('-v', '--version', action='version', version=f'{modules.metadata.name} {modules.metadata.version}') # Register deprecated args program.add_argument('-f', '--face', help=argparse.SUPPRESS, dest='source_path_deprecated') program.add_argument('--cpu-cores', help=argparse.SUPPRESS, dest='cpu_cores_deprecated', type=int) program.add_argument('--gpu-vendor', help=argparse.SUPPRESS, dest='gpu_vendor_deprecated') program.add_argument('--gpu-threads', help=argparse.SUPPRESS, dest='gpu_threads_deprecated', type=int) args = program.parse_args() modules.globals.source_path = args.source_path modules.globals.target_path = args.target_path modules.globals.output_path = normalize_output_path(modules.globals.source_path, modules.globals.target_path, args.output_path) modules.globals.frame_processors = args.frame_processor modules.globals.headless = args.source_path or args.target_path or args.output_path modules.globals.keep_fps = args.keep_fps modules.globals.keep_audio = args.keep_audio modules.globals.keep_frames = args.keep_frames modules.globals.many_faces = args.many_faces modules.globals.video_encoder = args.video_encoder modules.globals.video_quality = args.video_quality modules.globals.live_mirror = args.live_mirror modules.globals.live_resizable = args.live_resizable modules.globals.max_memory = args.max_memory modules.globals.execution_providers = decode_execution_providers(args.execution_provider) modules.globals.execution_threads = args.execution_threads modules.globals.headless = args.headless modules.globals.enhancer_upscale_factor = args.enhancer_upscale_factor modules.globals.source_image_scaling_factor = args.source_image_scaling_factor modules.globals.sr_scale_factor = args.super_resolution_scale_factor # Handle face enhancer tumbler modules.globals.fp_ui['face_enhancer'] = 'face_enhancer' in args.frame_processor modules.globals.nsfw = False # Handle deprecated arguments handle_deprecated_args(args) def handle_deprecated_args(args) -> None: """Handle deprecated arguments by translating them to the new format.""" if args.source_path_deprecated: print('\033[33mArgument -f and --face are deprecated. Use -s and --source instead.\033[0m') modules.globals.source_path = args.source_path_deprecated modules.globals.output_path = normalize_output_path(args.source_path_deprecated, modules.globals.target_path, args.output_path) if args.cpu_cores_deprecated: print('\033[33mArgument --cpu-cores is deprecated. Use --execution-threads instead.\033[0m') modules.globals.execution_threads = args.cpu_cores_deprecated if args.gpu_vendor_deprecated == 'apple': print('\033[33mArgument --gpu-vendor apple is deprecated. Use --execution-provider coreml instead.\033[0m') modules.globals.execution_providers = decode_execution_providers(['coreml']) if args.gpu_vendor_deprecated == 'nvidia': print('\033[33mArgument --gpu-vendor nvidia is deprecated. Use --execution-provider cuda instead.\033[0m') modules.globals.execution_providers = decode_execution_providers(['cuda']) if args.gpu_vendor_deprecated == 'amd': print('\033[33mArgument --gpu-vendor amd is deprecated. Use --execution-provider rocm instead.\033[0m') modules.globals.execution_providers = decode_execution_providers(['rocm']) if args.gpu_threads_deprecated: print('\033[33mArgument --gpu-threads is deprecated. Use --execution-threads instead.\033[0m') modules.globals.execution_threads = args.gpu_threads_deprecated def encode_execution_providers(execution_providers: List[str]) -> List[str]: return [provider.replace('ExecutionProvider', '').lower() for provider in execution_providers] def decode_execution_providers(execution_providers: List[str]) -> List[str]: available_providers = onnxruntime.get_available_providers() encoded_providers = encode_execution_providers(available_providers) selected_providers = [available_providers[encoded_providers.index(req)] for req in execution_providers if req in encoded_providers] # Default to CPU if no suitable providers are found return selected_providers if selected_providers else ['CPUExecutionProvider'] def suggest_max_memory() -> int: return 4 if platform.system().lower() == 'darwin' else 16 def suggest_execution_providers() -> List[str]: return encode_execution_providers(onnxruntime.get_available_providers()) def suggest_execution_threads() -> int: if 'dml' in modules.globals.execution_providers: return 1 if 'rocm' in modules.globals.execution_providers: return 1 return 8 def limit_resources() -> None: # Prevent TensorFlow memory leak gpus = tensorflow.config.experimental.list_physical_devices('GPU') for gpu in gpus: tensorflow.config.experimental.set_memory_growth(gpu, True) # Limit memory usage if modules.globals.max_memory: memory = modules.globals.max_memory * 1024 ** 3 if platform.system().lower() == 'darwin': memory = modules.globals.max_memory * 1024 ** 3 elif platform.system().lower() == 'windows': import ctypes kernel32 = ctypes.windll.kernel32 kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory)) else: import resource try: soft, hard = resource.getrlimit(resource.RLIMIT_DATA) if memory > hard: print( f"Warning: Requested memory limit {memory / (1024 ** 3)} GB exceeds system's hard limit. Setting to maximum allowed {hard / (1024 ** 3)} GB.") memory = hard resource.setrlimit(resource.RLIMIT_DATA, (memory, memory)) except ValueError as e: print(f"Warning: Could not set memory limit: {e}. Continuing with default limits.") def release_resources() -> None: if 'cuda' in modules.globals.execution_providers: torch.cuda.empty_cache() 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 if 'cuda' in modules.globals.execution_providers and not torch.cuda.is_available(): update_status('CUDA is not available. Please check your GPU or CUDA installation.') return False return True def update_status(message: str, scope: str = 'DLC.CORE') -> None: print(f'[{scope}] {message}') if not modules.globals.headless and ui.status_label: ui.update_status(message) def start() -> None: for frame_processor in get_frame_processors_modules(modules.globals.frame_processors): if not frame_processor.pre_start(): return # Process image to image if has_image_extension(modules.globals.target_path): process_image_to_image() return # Process image to video process_image_to_video() def process_image_to_image() -> None: if modules.globals.nsfw: from modules.predicter import predict_image if predict_image(modules.globals.target_path): destroy(to_quit=False) update_status('Processing to image ignored!') return try: shutil.copy2(modules.globals.target_path, modules.globals.output_path) except Exception as e: print("Error copying file:", str(e)) for frame_processor in get_frame_processors_modules(modules.globals.frame_processors): update_status('Processing...', frame_processor.NAME) frame_processor.process_image(modules.globals.source_path, modules.globals.output_path, modules.globals.output_path) release_resources() if is_image(modules.globals.target_path): update_status('Processing to image succeeded!') else: update_status('Processing to image failed!') def process_image_to_video() -> None: if modules.globals.nsfw: from modules.predicter import predict_video if predict_video(modules.globals.target_path): destroy(to_quit=False) update_status('Processing to video ignored!') return update_status('Creating temporary resources...') create_temp(modules.globals.target_path) update_status('Extracting frames...') extract_frames(modules.globals.target_path) temp_frame_paths = get_temp_frame_paths(modules.globals.target_path) for frame_processor in get_frame_processors_modules(modules.globals.frame_processors): update_status('Processing...', frame_processor.NAME) frame_processor.process_video(modules.globals.source_path, temp_frame_paths) release_resources() handle_video_fps() handle_video_audio() clean_temp(modules.globals.target_path) if is_video(modules.globals.target_path): update_status('Processing to video succeeded!') else: update_status('Processing to video failed!') def handle_video_fps() -> None: if modules.globals.keep_fps: update_status('Detecting fps...') fps = detect_fps(modules.globals.target_path) update_status(f'Creating video with {fps} fps...') create_video(modules.globals.target_path, fps) else: update_status('Creating video with 30.0 fps...') create_video(modules.globals.target_path) def handle_video_audio() -> None: if modules.globals.keep_audio: if modules.globals.keep_fps: update_status('Restoring audio...') else: update_status('Restoring audio might cause issues as fps are not kept...') restore_audio(modules.globals.target_path, modules.globals.output_path) else: move_temp(modules.globals.target_path, modules.globals.output_path) def destroy(to_quit=True) -> None: if modules.globals.target_path: clean_temp(modules.globals.target_path) if to_quit: quit() def run() -> None: try: parse_args() if not pre_check(): return for frame_processor in get_frame_processors_modules(modules.globals.frame_processors): if not frame_processor.pre_check(): return limit_resources() if modules.globals.headless: start() else: window = ui.init(start, destroy) window.mainloop() except Exception as e: print(f"UI initialization failed: {str(e)}") update_status(f"UI initialization failed: {str(e)}") destroy() # Ensure any resources are cleaned up on failure