FaceSwap / roop /core.py
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#!/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()