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import os |
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import sys |
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import shutil |
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if any(arg.startswith('--execution-provider') for arg in sys.argv): |
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os.environ['OMP_NUM_THREADS'] = '1' |
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import warnings |
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from typing import List |
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import platform |
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import signal |
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import argparse |
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import torch |
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import onnxruntime |
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import tensorflow |
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import pathlib |
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from time import time |
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import roop.globals |
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import roop.metadata |
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import roop.utilities as util |
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import roop.ui as ui |
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from settings import Settings |
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from roop.face_util import extract_face_images |
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from roop.ProcessEntry import ProcessEntry |
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from roop.ProcessMgr import ProcessMgr |
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from roop.ProcessOptions import ProcessOptions |
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clip_text = None |
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call_display_ui = None |
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process_mgr = None |
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if 'ROCMExecutionProvider' in roop.globals.execution_providers: |
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del torch |
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warnings.filterwarnings('ignore', category=FutureWarning, module='insightface') |
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warnings.filterwarnings('ignore', category=UserWarning, module='torchvision') |
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def parse_args() -> None: |
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signal.signal(signal.SIGINT, lambda signal_number, frame: destroy()) |
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program = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog, max_help_position=100)) |
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program.add_argument('-s', '--source', help='select a source image', dest='source_path') |
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program.add_argument('-t', '--target', help='select a target image or video', dest='target_path') |
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program.add_argument('-o', '--output', help='select output file or directory', dest='output_path') |
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program.add_argument('-f', '--folder', help='select a target folder with images or videos to batch process', dest='target_folder_path') |
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program.add_argument('--frame-processor', help='frame processors (choices: face_swapper, face_enhancer, ...)', dest='frame_processor', default=['face_swapper'], nargs='+') |
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program.add_argument('--keep-fps', help='keep target fps', dest='keep_fps', action='store_true') |
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program.add_argument('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true') |
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program.add_argument('--skip-audio', help='skip target audio', dest='skip_audio', action='store_true') |
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program.add_argument('--many-faces', help='process every face', dest='many_faces', action='store_true') |
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program.add_argument('--source-face_index', help='index position of source face in image', dest='source_face_index', type=int, default=0) |
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program.add_argument('--target-face_index', help='index position of target face in image', dest='target_face_index', type=int, default=0) |
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program.add_argument('--video-encoder', help='adjust output video encoder', dest='video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9']) |
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program.add_argument('--video-quality', help='adjust output video quality', dest='video_quality', type=int, default=18, choices=range(52), metavar='[0-51]') |
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program.add_argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int, default=suggest_max_memory()) |
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program.add_argument('--execution-provider', help='available execution provider (choices: cpu, ...)', dest='execution_provider', default=['cpu'], choices=suggest_execution_providers(), nargs='+') |
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program.add_argument('--execution-threads', help='number of execution threads', dest='execution_threads', type=int, default=suggest_execution_threads()) |
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program.add_argument('-v', '--version', action='version', version=f'{roop.metadata.name} {roop.metadata.version}') |
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args = program.parse_args() |
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roop.globals.source_path = args.source_path |
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roop.globals.target_path = args.target_path |
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roop.globals.output_path = util.normalize_output_path(roop.globals.source_path, roop.globals.target_path, args.output_path) |
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roop.globals.target_folder_path = args.target_folder_path |
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roop.globals.headless = args.source_path or args.target_path or args.output_path |
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if not roop.globals.headless: |
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roop.globals.frame_processors = ['face_swapper', 'face_enhancer'] |
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else: |
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roop.globals.frame_processors = args.frame_processor |
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roop.globals.keep_fps = args.keep_fps |
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roop.globals.keep_frames = args.keep_frames |
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roop.globals.skip_audio = args.skip_audio |
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roop.globals.many_faces = args.many_faces |
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roop.globals.source_face_index = args.source_face_index |
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roop.globals.target_face_index = args.target_face_index |
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roop.globals.video_encoder = args.video_encoder |
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roop.globals.video_quality = args.video_quality |
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roop.globals.max_memory = args.max_memory |
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roop.globals.execution_providers = decode_execution_providers(args.execution_provider) |
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roop.globals.execution_threads = args.execution_threads |
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def encode_execution_providers(execution_providers: List[str]) -> List[str]: |
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return [execution_provider.replace('ExecutionProvider', '').lower() for execution_provider in execution_providers] |
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def decode_execution_providers(execution_providers: List[str]) -> List[str]: |
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return [provider for provider, encoded_execution_provider in zip(onnxruntime.get_available_providers(), encode_execution_providers(onnxruntime.get_available_providers())) |
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if any(execution_provider in encoded_execution_provider for execution_provider in execution_providers)] |
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def suggest_max_memory() -> int: |
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if platform.system().lower() == 'darwin': |
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return 4 |
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return 16 |
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def suggest_execution_providers() -> List[str]: |
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return encode_execution_providers(onnxruntime.get_available_providers()) |
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def suggest_execution_threads() -> int: |
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if 'DmlExecutionProvider' in roop.globals.execution_providers: |
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return 1 |
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if 'ROCMExecutionProvider' in roop.globals.execution_providers: |
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return 1 |
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return 8 |
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def limit_resources() -> None: |
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gpus = tensorflow.config.experimental.list_physical_devices('GPU') |
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for gpu in gpus: |
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tensorflow.config.experimental.set_virtual_device_configuration(gpu, [ |
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tensorflow.config.experimental.VirtualDeviceConfiguration(memory_limit=1024) |
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]) |
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if roop.globals.max_memory: |
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memory = roop.globals.max_memory * 1024 ** 3 |
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if platform.system().lower() == 'darwin': |
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memory = roop.globals.max_memory * 1024 ** 6 |
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if platform.system().lower() == 'windows': |
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import ctypes |
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kernel32 = ctypes.windll.kernel32 |
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kernel32.SetProcessWorkingSetSize(-1, ctypes.c_size_t(memory), ctypes.c_size_t(memory)) |
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else: |
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import resource |
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resource.setrlimit(resource.RLIMIT_DATA, (memory, memory)) |
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def release_resources() -> None: |
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import gc |
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global process_mgr |
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if process_mgr is not None: |
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process_mgr.release_resources() |
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process_mgr = None |
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gc.collect() |
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if 'CUDAExecutionProvider' in roop.globals.execution_providers and torch.cuda.is_available(): |
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with torch.cuda.device('cuda'): |
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torch.cuda.empty_cache() |
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torch.cuda.ipc_collect() |
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def pre_check() -> bool: |
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if sys.version_info < (3, 9): |
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update_status('Python version is not supported - please upgrade to 3.9 or higher.') |
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return False |
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download_directory_path = util.resolve_relative_path('../models') |
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util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/inswapper_128.onnx']) |
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util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/GFPGANv1.4.onnx']) |
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util.conditional_download(download_directory_path, ['https://github.com/csxmli2016/DMDNet/releases/download/v1/DMDNet.pth']) |
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download_directory_path = util.resolve_relative_path('../models/CLIP') |
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util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/rd64-uni-refined.pth']) |
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download_directory_path = util.resolve_relative_path('../models/CodeFormer') |
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util.conditional_download(download_directory_path, ['https://huggingface.co/countfloyd/deepfake/resolve/main/CodeFormerv0.1.onnx']) |
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if not shutil.which('ffmpeg'): |
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update_status('ffmpeg is not installed.') |
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return True |
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def set_display_ui(function): |
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global call_display_ui |
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call_display_ui = function |
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def update_status(message: str) -> None: |
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global call_display_ui |
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print(message) |
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if call_display_ui is not None: |
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call_display_ui(message) |
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def start() -> None: |
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if roop.globals.headless: |
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faces = extract_face_images(roop.globals.source_path, (False, 0)) |
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roop.globals.INPUT_FACES.append(faces[roop.globals.source_face_index]) |
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faces = extract_face_images(roop.globals.target_path, (False, util.has_image_extension(roop.globals.target_path))) |
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roop.globals.TARGET_FACES.append(faces[roop.globals.target_face_index]) |
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if 'face_enhancer' in roop.globals.frame_processors: |
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roop.globals.selected_enhancer = 'GFPGAN' |
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batch_process(None, False, None) |
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def get_processing_plugins(use_clip): |
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processors = "faceswap" |
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if use_clip: |
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processors += ",mask_clip2seg" |
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if roop.globals.selected_enhancer == 'GFPGAN': |
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processors += ",gfpgan" |
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elif roop.globals.selected_enhancer == 'Codeformer': |
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processors += ",codeformer" |
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elif roop.globals.selected_enhancer == 'DMDNet': |
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processors += ",dmdnet" |
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return processors |
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def live_swap(frame, swap_mode, use_clip, clip_text, selected_index = 0): |
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global process_mgr |
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if frame is None: |
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return frame |
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if process_mgr is None: |
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process_mgr = ProcessMgr(None) |
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options = ProcessOptions(get_processing_plugins(use_clip), roop.globals.distance_threshold, roop.globals.blend_ratio, swap_mode, selected_index, clip_text) |
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process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) |
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return process_mgr.process_frame(frame) |
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def preview_mask(frame, clip_text): |
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import numpy as np |
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global process_mgr |
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maskimage = np.zeros((frame.shape), np.uint8) |
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if process_mgr is None: |
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process_mgr = ProcessMgr() |
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options = ProcessOptions("mask_clip2seg", roop.globals.distance_threshold, roop.globals.blend_ratio, "None", 0, clip_text) |
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process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) |
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return process_mgr.process_mask(frame, maskimage) |
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def batch_process(files:list[ProcessEntry], use_clip, new_clip_text, use_new_method, progress) -> None: |
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global clip_text, process_mgr |
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roop.globals.processing = True |
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release_resources() |
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limit_resources() |
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max_threads = suggest_execution_threads() |
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if max_threads == 1: |
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roop.globals.execution_threads = 1 |
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imagefiles:list[ProcessEntry] = [] |
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videofiles:list[ProcessEntry] = [] |
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update_status('Sorting videos/images') |
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for index, f in enumerate(files): |
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fullname = f.filename |
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if util.has_image_extension(fullname): |
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destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'.{roop.globals.CFG.output_image_format}') |
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destination = util.replace_template(destination, index=index) |
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pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) |
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f.finalname = destination |
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imagefiles.append(f) |
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elif util.is_video(fullname) or util.has_extension(fullname, ['gif']): |
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destination = util.get_destfilename_from_path(fullname, roop.globals.output_path, f'__temp.{roop.globals.CFG.output_video_format}') |
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f.finalname = destination |
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videofiles.append(f) |
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if process_mgr is None: |
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process_mgr = ProcessMgr(progress) |
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options = ProcessOptions(get_processing_plugins(use_clip), roop.globals.distance_threshold, roop.globals.blend_ratio, roop.globals.face_swap_mode, 0, new_clip_text) |
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process_mgr.initialize(roop.globals.INPUT_FACES, roop.globals.TARGET_FACES, options) |
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if(len(imagefiles) > 0): |
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update_status('Processing image(s)') |
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origimages = [] |
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fakeimages = [] |
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for f in imagefiles: |
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origimages.append(f.filename) |
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fakeimages.append(f.finalname) |
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process_mgr.run_batch(origimages, fakeimages, roop.globals.execution_threads) |
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origimages.clear() |
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fakeimages.clear() |
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if(len(videofiles) > 0): |
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for index,v in enumerate(videofiles): |
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if not roop.globals.processing: |
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end_processing('Processing stopped!') |
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return |
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fps = v.fps if v.fps > 0 else util.detect_fps(v.filename) |
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update_status(f'Creating {os.path.basename(v.finalname)} with {fps} FPS...') |
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start_processing = time() |
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if roop.globals.keep_frames or not use_new_method: |
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util.create_temp(v.filename) |
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update_status('Extracting frames...') |
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util.extract_frames(v.filename,v.startframe,v.endframe, fps) |
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if not roop.globals.processing: |
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end_processing('Processing stopped!') |
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return |
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temp_frame_paths = util.get_temp_frame_paths(v.filename) |
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process_mgr.run_batch(temp_frame_paths, temp_frame_paths, roop.globals.execution_threads) |
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if not roop.globals.processing: |
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end_processing('Processing stopped!') |
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return |
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util.create_video(v.filename, f.finalname, fps) |
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if not roop.globals.keep_frames: |
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util.delete_temp_frames(temp_frame_paths[0]) |
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else: |
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if util.has_extension(v.filename, ['gif']): |
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skip_audio = True |
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else: |
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skip_audio = roop.globals.skip_audio |
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process_mgr.run_batch_inmem(v.filename, v.finalname, v.startframe, v.endframe, fps,roop.globals.execution_threads, skip_audio) |
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if not roop.globals.processing: |
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end_processing('Processing stopped!') |
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return |
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video_file_name = v.finalname |
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if os.path.isfile(video_file_name): |
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destination = '' |
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if util.has_extension(v.filename, ['gif']): |
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gifname = util.get_destfilename_from_path(v.filename, roop.globals.output_path, '.gif') |
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destination = util.replace_template(gifname, index=index) |
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pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) |
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update_status('Creating final GIF') |
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util.create_gif_from_video(video_file_name, destination) |
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if os.path.isfile(destination): |
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os.remove(video_file_name) |
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else: |
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skip_audio = roop.globals.skip_audio |
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destination = util.replace_template(video_file_name, index=index) |
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pathlib.Path(os.path.dirname(destination)).mkdir(parents=True, exist_ok=True) |
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if not skip_audio: |
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util.restore_audio(video_file_name, v.filename, v.startframe, v.endframe, destination) |
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if os.path.isfile(destination): |
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os.remove(video_file_name) |
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else: |
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shutil.move(video_file_name, destination) |
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update_status(f'\nProcessing {os.path.basename(destination)} took {time() - start_processing} secs') |
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else: |
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update_status(f'Failed processing {os.path.basename(v.finalname)}!') |
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end_processing('Finished') |
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def end_processing(msg:str): |
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update_status(msg) |
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roop.globals.target_folder_path = None |
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release_resources() |
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def destroy() -> None: |
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if roop.globals.target_path: |
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util.clean_temp(roop.globals.target_path) |
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release_resources() |
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sys.exit() |
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def run() -> None: |
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parse_args() |
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if not pre_check(): |
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return |
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roop.globals.CFG = Settings('config.yaml') |
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if roop.globals.headless: |
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start() |
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else: |
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ui.run() |
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