#!/usr/bin/env python3 import os import sys import shutil # 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' import warnings from typing import List import platform import signal import argparse import torch import onnxruntime import tensorflow import pathlib from time import time import roop.globals import roop.metadata import roop.utilities as util import roop.ui as ui from settings import Settings from roop.face_util import extract_face_images from roop.ProcessEntry import ProcessEntry from roop.ProcessMgr import ProcessMgr from roop.ProcessOptions import ProcessOptions clip_text = None call_display_ui = None process_mgr = None if 'ROCMExecutionProvider' in roop.globals.execution_providers: del torch 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 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('-f', '--folder', help='select a target folder with images or videos to batch process', dest='target_folder_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('--source-face_index', help='index position of source face in image', dest='source_face_index', type=int, default=0) program.add_argument('--target-face_index', help='index position of target face in image', dest='target_face_index', type=int, default=0) 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('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory()) 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 = util.normalize_output_path(roop.globals.source_path, roop.globals.target_path, args.output_path) roop.globals.target_folder_path = args.target_folder_path roop.globals.headless = args.source_path or args.target_path or args.output_path # Always enable all processors when using GUI if not roop.globals.headless: roop.globals.frame_processors = ['face_swapper', 'face_enhancer'] else: 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.source_face_index = args.source_face_index roop.globals.target_face_index = args.target_face_index roop.globals.video_encoder = args.video_encoder roop.globals.video_quality = args.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_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 roop.globals.execution_providers: return 1 if 'ROCMExecutionProvider' in roop.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_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 release_resources() -> None: import gc global process_mgr if process_mgr is not None: process_mgr.release_resources() process_mgr = None gc.collect() if 'CUDAExecutionProvider' in roop.globals.execution_providers and torch.cuda.is_available(): with torch.cuda.device('cuda'): torch.cuda.empty_cache() torch.cuda.ipc_collect() 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 download_directory_path = util.resolve_relative_path('../models') util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/inswapper_128.onnx']) util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/GFPGANv1.4.onnx']) util.conditional_download(download_directory_path, ['https://github.com/csxmli2016/DMDNet/releases/download/v1/DMDNet.pth']) download_directory_path = util.resolve_relative_path('../models/CLIP') util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/rd64-uni-refined.pth']) download_directory_path = util.resolve_relative_path('../models/CodeFormer') util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/CodeFormerv0.1.onnx']) if not shutil.which('ffmpeg'): update_status('ffmpeg is not installed.') return True def set_display_ui(function): global call_display_ui call_display_ui = function def update_status(message: str) -> None: global call_display_ui print(message) if call_display_ui is not None: call_display_ui(message) def start() -> None: if roop.globals.headless: faces = extract_face_images(roop.globals.source_path, (False, 0)) roop.globals.INPUT_FACES.append(faces[roop.globals.source_face_index]) faces = extract_face_images(roop.globals.target_path, (False, util.has_image_extension(roop.globals.target_path))) roop.globals.TARGET_FACES.append(faces[roop.globals.target_face_index]) if 'face_enhancer' in roop.globals.frame_processors: roop.globals.selected_enhancer = 'GFPGAN' batch_process(None, False, None) def get_processing_plugins(use_clip): processors = "faceswap" if use_clip: processors += ",mask_clip2seg" if roop.globals.selected_enhancer == 'GFPGAN': processors += ",gfpgan" elif roop.globals.selected_enhancer == 'Codeformer': processors += ",codeformer" elif roop.globals.selected_enhancer == 'DMDNet': processors += ",dmdnet" return processors def live_swap(frame, swap_mode, use_clip, clip_text, selected_index = 0): global process_mgr if frame is None: return frame if process_mgr is None: process_mgr = ProcessMgr(None) options = ProcessOptions(get_processing_plugins(use_clip), roop.globals.distance_threshold, roop.globals.blend_ratio, swap_mode, selected_index, clip_text) process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) return process_mgr.process_frame(frame) def preview_mask(frame, clip_text): import numpy as np global process_mgr maskimage = np.zeros((frame.shape), np.uint8) if process_mgr is None: process_mgr = ProcessMgr() options = ProcessOptions("mask_clip2seg", roop.globals.distance_threshold, roop.globals.blend_ratio, "None", 0, clip_text) process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) return process_mgr.process_mask(frame, maskimage) def batch_process(files:list[ProcessEntry], use_clip, new_clip_text, use_new_method, progress) -> None: global clip_text, process_mgr roop.globals.processing = True release_resources() limit_resources() # limit threads for some providers max_threads = suggest_execution_threads() if max_threads == 1: roop.globals.execution_threads = 1 imagefiles:list[ProcessEntry] = [] videofiles:list[ProcessEntry] = [] update_status('Sorting videos/images') for index, f in enumerate(files): fullname = f.filename if util.has_image_extension(fullname): destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'.{roop.globals.CFG.output_image_format}') destination = util.replace_template(destination, index=index) pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) f.finalname = destination imagefiles.append(f) elif util.is_video(fullname) or util.has_extension(fullname, ['gif']): destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'__temp.{roop.globals.CFG.output_video_format}') f.finalname = destination videofiles.append(f) if process_mgr is None: process_mgr = ProcessMgr(progress) options = ProcessOptions(get_processing_plugins(use_clip), roop.globals.distance_threshold, roop.globals.blend_ratio, roop.globals.face_swap_mode, 0, new_clip_text) process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) if(len(imagefiles) > 0): update_status('Processing image(s)') origimages = [] fakeimages = [] for f in imagefiles: origimages.append(f.filename) fakeimages.append(f.finalname) process_mgr.run_batch(origimages, fakeimages, roop.globals.execution_threads) origimages.clear() fakeimages.clear() if(len(videofiles) > 0): for index,v in enumerate(videofiles): if not roop.globals.processing: end_processing('Processing stopped!') return fps = v.fps if v.fps > 0 else util.detect_fps(v.filename) update_status(f'Creating {os.path.basename(v.finalname)} with {fps} FPS...') start_processing = time() if roop.globals.keep_frames or not use_new_method: util.create_temp(v.filename) update_status('Extracting frames...') util.extract_frames(v.filename,v.startframe,v.endframe, fps) if not roop.globals.processing: end_processing('Processing stopped!') return temp_frame_paths = util.get_temp_frame_paths(v.filename) process_mgr.run_batch(temp_frame_paths, temp_frame_paths, roop.globals.execution_threads) if not roop.globals.processing: end_processing('Processing stopped!') return util.create_video(v.filename, f.finalname, fps) if not roop.globals.keep_frames: util.delete_temp_frames(temp_frame_paths[0]) else: if util.has_extension(v.filename, ['gif']): skip_audio = True else: skip_audio = roop.globals.skip_audio process_mgr.run_batch_inmem(v.filename, v.finalname, v.startframe, v.endframe, fps,roop.globals.execution_threads, skip_audio) if not roop.globals.processing: end_processing('Processing stopped!') return video_file_name = v.finalname if os.path.isfile(video_file_name): destination = '' if util.has_extension(v.filename, ['gif']): gifname = util.get_destfilename_from_path(v.filename, roop.globals.output_path, '.gif') destination = util.replace_template(gifname, index=index) pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) update_status('Creating final GIF') util.create_gif_from_video(video_file_name, destination) if os.path.isfile(destination): os.remove(video_file_name) else: skip_audio = roop.globals.skip_audio destination = util.replace_template(video_file_name, index=index) pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) if not skip_audio: util.restore_audio(video_file_name, v.filename, v.startframe, v.endframe, destination) if os.path.isfile(destination): os.remove(video_file_name) else: shutil.move(video_file_name, destination) update_status(f'\nProcessing {os.path.basename(destination)} took {time() - start_processing} secs') else: update_status(f'Failed processing {os.path.basename(v.finalname)}!') end_processing('Finished') def end_processing(msg:str): update_status(msg) roop.globals.target_folder_path = None release_resources() def destroy() -> None: if roop.globals.target_path: util.clean_temp(roop.globals.target_path) release_resources() sys.exit() def run() -> None: parse_args() if not pre_check(): return roop.globals.CFG = Settings('config.yaml') if roop.globals.headless: start() else: ui.run()