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 torch import onnxruntime import tensorflow # modules.globals should be imported first to ensure variables are initialized with defaults # before any command-line parsing or other logic attempts to modify them. import modules.globals import modules.metadata # import modules.ui as ui # UI import removed from modules.processors.frame.core import get_frame_processors_modules # utilities import needs to be after globals for some path normalizations if they were to use globals 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, get_temp_directory_path # Added get_temp_directory_path ) if 'ROCMExecutionProvider' in modules.globals.execution_providers: del torch warnings.filterwarnings('ignore', category=FutureWarning, module='insightface') warnings.filterwarnings('ignore', category=UserWarning, module='torchvision') def parse_args() -> None: # For CLI use # Default values in modules.globals are set when modules.globals is imported. # parse_args will overwrite them if CLI arguments are provided. signal.signal(signal.SIGINT, lambda signal_number, frame: cleanup_temp_files(quit_app=True)) # Pass quit_app for CLI context program = argparse.ArgumentParser() 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='pipeline of frame processors', dest='frame_processor', default=['face_swapper'], choices=['face_swapper', 'face_enhancer'], 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('--nsfw-filter', help='filter the NSFW image or video', dest='nsfw_filter', action='store_true', default=False) program.add_argument('--map-faces', help='map source target faces', dest='map_faces', action='store_true', default=False) program.add_argument('--mouth-mask', help='mask the mouth region', dest='mouth_mask', 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('-l', '--lang', help='Ui language', default="en") 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('-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.mouth_mask = args.mouth_mask modules.globals.nsfw_filter = args.nsfw_filter modules.globals.map_faces = args.map_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.lang = args.lang #for ENHANCER tumbler: if 'face_enhancer' in args.frame_processor: modules.globals.fp_ui['face_enhancer'] = True else: modules.globals.fp_ui['face_enhancer'] = False # translate deprecated args 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 cuda 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 [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_max_memory() -> int: if platform.system().lower() == 'darwin': return 4 return 16 def suggest_execution_providers() -> List[str]: return encode_execution_providers(onnxruntime.get_available_providers()) def suggest_execution_threads() -> int: if 'DmlExecutionProvider' in modules.globals.execution_providers: return 1 if 'ROCMExecutionProvider' 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 ** 6 if 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 resource.setrlimit(resource.RLIMIT_DATA, (memory, memory)) def release_resources() -> None: if 'CUDAExecutionProvider' in modules.globals.execution_providers: torch.cuda.empty_cache() def pre_check() -> bool: # For CLI and WebApp if sys.version_info < (3, 9): print('DLC.CORE: Python version is not supported - please upgrade to 3.9 or higher.') return False if not shutil.which('ffmpeg'): print('DLC.CORE: ffmpeg is not installed.') return False # Potentially add other checks, like if source/target paths are set (for CLI context) # For webapp, these will be set by the app itself. return True def update_status(message: str, scope: str = 'DLC.CORE') -> None: # For CLI and WebApp (prints to console) print(f'[{scope}] {message}') # UI update removed: # if not modules.globals.headless: # ui.update_status(message) # Renamed from start() def process_media() -> dict: # Returns a status dictionary # Ensure required paths are set in modules.globals if not modules.globals.source_path or not os.path.exists(modules.globals.source_path): return {'success': False, 'error': 'Source path not set or invalid.'} if not modules.globals.target_path or not os.path.exists(modules.globals.target_path): return {'success': False, 'error': 'Target path not set or invalid.'} if not modules.globals.output_path: # Output path must be determined by caller (e.g. webapp or CLI parse_args) return {'success': False, 'error': 'Output path not set.'} active_processors = get_frame_processors_modules(modules.globals.frame_processors) if not active_processors: return {'success': False, 'error': f"No valid frame processors could be initialized for: {modules.globals.frame_processors}. Check if they are installed and configured."} for frame_processor in active_processors: if hasattr(frame_processor, 'pre_start') and callable(frame_processor.pre_start): if not frame_processor.pre_start(): # Some processors might have pre-start checks return {'success': False, 'error': f"Pre-start check failed for processor: {frame_processor.NAME if hasattr(frame_processor, 'NAME') else 'Unknown'}"} update_status('Processing...') # process image to image if is_image(modules.globals.target_path): # Use is_image from utilities # NSFW Check (temporarily commented out) # if modules.globals.nsfw_filter and predict_nsfw(modules.globals.target_path): # Assuming a predict_nsfw utility # return {'success': False, 'error': 'NSFW content detected in target image.', 'nsfw': True} try: # Ensure output directory exists os.makedirs(os.path.dirname(modules.globals.output_path), exist_ok=True) shutil.copy2(modules.globals.target_path, modules.globals.output_path) except Exception as e: return {'success': False, 'error': f"Error copying target file: {str(e)}"} for frame_processor in active_processors: update_status(f"Progressing with {frame_processor.NAME if hasattr(frame_processor, 'NAME') else 'Unknown Processor'}") try: if modules.globals.map_faces and modules.globals.simple_map and hasattr(frame_processor, 'process_image_v2'): # For mapped faces, process_image_v2 might only need the target and output paths, # as mappings are in Globals.simple_map. # The specific signature depends on processor implementation. # Assuming (target_path, output_path) for v2 for now. frame_processor.process_image_v2(modules.globals.output_path, modules.globals.output_path) elif hasattr(frame_processor, 'process_image'): # Standard processing if not map_faces or if processor lacks v2 frame_processor.process_image(modules.globals.source_path, modules.globals.output_path, modules.globals.output_path) else: update_status(f"Processor {frame_processor.NAME} has no suitable process_image or process_image_v2 method.") # Decide if this should be an error or just a skip release_resources() except Exception as e: import traceback traceback.print_exc() return {'success': False, 'error': f"Error during image processing with {frame_processor.NAME if hasattr(frame_processor, 'NAME') else 'Unknown Processor'}: {str(e)}"} if os.path.exists(modules.globals.output_path): # Check if output file was actually created update_status('Processing to image succeed!') return {'success': True, 'output_path': modules.globals.output_path} else: update_status('Processing to image failed! Output file not found.') return {'success': False, 'error': 'Output image file not found after processing.'} # process video if is_video(modules.globals.target_path): # Use is_video from utilities # NSFW Check (temporarily commented out) # if modules.globals.nsfw_filter and predict_nsfw(modules.globals.target_path): # Assuming a predict_nsfw utility # return {'success': False, 'error': 'NSFW content detected in target video.', 'nsfw': True} update_status('Creating temp resources...') # temp_frames_dir should be based on the target_path filename to ensure uniqueness temp_frames_dir = get_temp_directory_path(modules.globals.target_path) create_temp(temp_frames_dir) # Create the specific directory for frames update_status('Extracting frames...') extract_frames(modules.globals.target_path, temp_frames_dir) # Pass explicit temp_frames_dir processed_temp_frame_paths = get_temp_frame_paths(temp_frames_dir) # Get paths from the correct temp dir if not processed_temp_frame_paths: clean_temp(temp_frames_dir) return {'success': False, 'error': 'Failed to extract frames from video.'} for frame_processor in active_processors: update_status(f"Progressing with {frame_processor.NAME if hasattr(frame_processor, 'NAME') else 'Unknown Processor'}") try: if modules.globals.map_faces and modules.globals.simple_map and hasattr(frame_processor, 'process_video_v2'): # For mapped faces, process_video_v2 might only need the frame paths, # as mappings are in Globals.simple_map. # The specific signature depends on processor implementation. # Assuming (list_of_frame_paths) for v2 for now. frame_processor.process_video_v2(processed_temp_frame_paths) elif hasattr(frame_processor, 'process_video'): # Standard processing if not map_faces or if processor lacks v2 frame_processor.process_video(modules.globals.source_path, processed_temp_frame_paths) else: update_status(f"Processor {frame_processor.NAME} has no suitable process_video or process_video_v2 method.") # Decide if this should be an error or just a skip release_resources() except Exception as e: import traceback traceback.print_exc() clean_temp(temp_frames_dir) return {'success': False, 'error': f"Error during video processing with {frame_processor.NAME if hasattr(frame_processor, 'NAME') else 'Unknown Processor'}: {str(e)}"} video_fps = detect_fps(modules.globals.target_path) if modules.globals.keep_fps else 30.0 update_status(f'Creating video with {video_fps} fps...') # Temp video output path for video without audio # output_path is the final destination, temp_video_output_path is intermediate temp_video_output_path = normalize_output_path(modules.globals.target_path, os.path.dirname(modules.globals.output_path), '_temp_novideoaudio') if not temp_video_output_path: clean_temp(temp_frames_dir) return {'success': False, 'error': 'Could not normalize temporary video output path.'} frames_pattern = os.path.join(temp_frames_dir, "%04d.png") if not create_video(frames_pattern, video_fps, temp_video_output_path, modules.globals.video_quality, modules.globals.video_encoder): clean_temp(temp_frames_dir) if os.path.exists(temp_video_output_path): os.remove(temp_video_output_path) return {'success': False, 'error': 'Failed to create video from processed frames.'} if modules.globals.keep_audio: update_status('Restoring audio...') if not restore_audio(temp_video_output_path, modules.globals.target_path, modules.globals.output_path): update_status('Audio restoration failed. Moving video without new audio to output.') shutil.move(temp_video_output_path, modules.globals.output_path) # Fallback: move the no-audio video else: # Audio restored, temp_video_output_path was used as source, now remove it if it still exists if os.path.exists(temp_video_output_path) and temp_video_output_path != modules.globals.output_path : os.remove(temp_video_output_path) else: shutil.move(temp_video_output_path, modules.globals.output_path) clean_temp(temp_frames_dir) if os.path.exists(modules.globals.output_path): update_status('Processing to video succeed!') return {'success': True, 'output_path': modules.globals.output_path} else: update_status('Processing to video failed! Output file not found.') return {'success': False, 'error': 'Output video file not found after processing.'} return {'success': False, 'error': 'Target file type not supported (not image or video).'} # Renamed from destroy() def cleanup_temp_files(quit_app: bool = False) -> None: # quit_app is for CLI context if modules.globals.target_path: # Check if target_path was ever set temp_frames_dir = get_temp_directory_path(modules.globals.target_path) if os.path.exists(temp_frames_dir): # Check if temp_frames_dir exists before cleaning clean_temp(temp_frames_dir) if quit_app: sys.exit() # Use sys.exit for a cleaner exit than quit() def run() -> None: # CLI focused run parse_args() # Sets globals from CLI args if not pre_check(): cleanup_temp_files(quit_app=True) return # Initialize processors and check their specific pre-requisites # This was implicitly part of the old start() before iterating active_processors = get_frame_processors_modules(modules.globals.frame_processors) if not active_processors: update_status(f"Failed to initialize frame processors: {modules.globals.frame_processors}. Exiting.") cleanup_temp_files(quit_app=True) return all_processors_ready = True for frame_processor in active_processors: if hasattr(frame_processor, 'pre_check') and callable(frame_processor.pre_check): if not frame_processor.pre_check(): all_processors_ready = False # Processor should print its own error message via update_status or print break if not all_processors_ready: cleanup_temp_files(quit_app=True) return limit_resources() # modules.globals.headless is set by parse_args if CLI args are present # This run() is now CLI-only, so headless is effectively always true in this context if modules.globals.headless: processing_result = process_media() if processing_result['success']: update_status(f"CLI processing finished successfully. Output: {processing_result.get('output_path', 'N/A')}") else: update_status(f"CLI processing failed: {processing_result.get('error', 'Unknown error')}") if processing_result.get('nsfw'): update_status("NSFW content was detected and processing was halted.") else: # This block should ideally not be reached if parse_args correctly sets headless # or if run() is only called in a CLI context. # For safety, we can print a message. update_status("Warning: core.run() called in a mode that seems non-headless, but UI is disabled. Processing will not start.") cleanup_temp_files(quit_app=True) # Cleanup and exit for CLI