real time face swap and one-click video deepfake with only a single image
from typing import Any
import cv2


def get_video_frame(video_path: str, frame_number: int = 0) -> Any:
    capture = cv2.VideoCapture(video_path)
    frame_total = capture.get(cv2.CAP_PROP_FRAME_COUNT)
    capture.set(cv2.CAP_PROP_POS_FRAMES, min(frame_total, frame_number - 1))
    has_frame, frame = capture.read()
    capture.release()
    if has_frame:
        return frame
    return None


def get_video_frame_total(video_path: str) -> int:
    capture = cv2.VideoCapture(video_path)
    video_frame_total = int(capture.get(cv2.CAP_PROP_FRAME_COUNT))
    capture.release()
    return video_frame_total

modules/capturer.py
hacksider/Deep-Live-Cam
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

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

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:
    signal.signal(signal.SIGINT, lambda signal_number, frame: destroy())
    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('--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='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.video_encoder = args.video_encoder
    modules.globals.video_quality = args.video_quality
    modules.globals.max_memory = args.max_memory
    modules.globals.execution_providers = decode_execution_providers(args.execution_provider)
    modules.globals.execution_threads = args.execution_threads

    #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
    
    modules.globals.nsfw = 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:
    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
    return True


def update_status(message: str, scope: str = 'DLC.CORE') -> None:
    print(f'[{scope}] {message}')
    if not modules.globals.headless:
        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):
        if modules.globals.nsfw == False:
            from modules.predicter import predict_image
            if predict_image(modules.globals.target_path):
                destroy()
        shutil.copy2(modules.globals.target_path, modules.globals.output_path)
        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
            update_status('Progressing...', 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 succeed!')
        else:
            update_status('Processing to image failed!')
        return
    # process image to videos
    if modules.globals.nsfw == False:
        from modules.predicter import predict_video
        if predict_video(modules.globals.target_path):
            destroy()
    update_status('Creating temp 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('Progressing...', frame_processor.NAME)
        frame_processor.process_video(modules.globals.source_path, temp_frame_paths)
        release_resources()
    # handles fps
    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)
    # handle audio
    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)
    # clean and validate
    clean_temp(modules.globals.target_path)
    if is_video(modules.globals.target_path):
        update_status('Processing to video succeed!')
    else:
        update_status('Processing to video failed!')


def destroy() -> None:
    if modules.globals.target_path:
        clean_temp(modules.globals.target_path)
    quit()


def run() -> None:
    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()

modules/core.py
hacksider/Deep-Live-Cam
from typing import Any
import insightface

import modules.globals
from modules.typing import Frame

FACE_ANALYSER = None


def get_face_analyser() -> Any:
    global FACE_ANALYSER

    if FACE_ANALYSER is None:
        FACE_ANALYSER = insightface.app.FaceAnalysis(name='buffalo_l', providers=modules.globals.execution_providers)
        FACE_ANALYSER.prepare(ctx_id=0, det_size=(640, 640))
    return FACE_ANALYSER


def get_one_face(frame: Frame) -> Any:
    face = get_face_analyser().get(frame)
    try:
        return min(face, key=lambda x: x.bbox[0])
    except ValueError:
        return None


def get_many_faces(frame: Frame) -> Any:
    try:
        return get_face_analyser().get(frame)
    except IndexError:
        return None

modules/face_analyser.py
hacksider/Deep-Live-Cam
import os
from typing import List, Dict

ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
WORKFLOW_DIR = os.path.join(ROOT_DIR, 'workflow')

file_types = [
    ('Image', ('*.png','*.jpg','*.jpeg','*.gif','*.bmp')),
    ('Video', ('*.mp4','*.mkv'))
]

source_path = None
target_path = None
output_path = None
frame_processors: List[str] = []
keep_fps = None
keep_audio = None
keep_frames = None
many_faces = None
video_encoder = None
video_quality = None
max_memory = None
execution_providers: List[str] = []
execution_threads = None
headless = None
log_level = 'error'
fp_ui: Dict[str, bool] = {}
nsfw = None

modules/globals.py
hacksider/Deep-Live-Cam
name = 'Deep Live Cam'
version = '1.3.0'
edition = 'Portable'

modules/metadata.py
hacksider/Deep-Live-Cam
import numpy
import opennsfw2
from PIL import Image

from modules.typing import Frame

MAX_PROBABILITY = 0.85


def predict_frame(target_frame: Frame) -> bool:
    image = Image.fromarray(target_frame)
    image = opennsfw2.preprocess_image(image, opennsfw2.Preprocessing.YAHOO)
    model = opennsfw2.make_open_nsfw_model()
    views = numpy.expand_dims(image, axis=0)
    _, probability = model.predict(views)[0]
    return probability > MAX_PROBABILITY


def predict_image(target_path: str) -> bool:
    return opennsfw2.predict_image(target_path) > MAX_PROBABILITY


def predict_video(target_path: str) -> bool:
    _, probabilities = opennsfw2.predict_video_frames(video_path=target_path, frame_interval=100)
    return any(probability > MAX_PROBABILITY for probability in probabilities)

modules/predicter.py
hacksider/Deep-Live-Cam
import sys
import importlib
from concurrent.futures import ThreadPoolExecutor
from types import ModuleType
from typing import Any, List, Callable
from tqdm import tqdm

import modules
import modules.globals                   

FRAME_PROCESSORS_MODULES: List[ModuleType] = []
FRAME_PROCESSORS_INTERFACE = [
    'pre_check',
    'pre_start',
    'process_frame',
    'process_image',
    'process_video'
]


def load_frame_processor_module(frame_processor: str) -> Any:
    try:
        frame_processor_module = importlib.import_module(f'modules.processors.frame.{frame_processor}')
        for method_name in FRAME_PROCESSORS_INTERFACE:
            if not hasattr(frame_processor_module, method_name):
                sys.exit()
    except ImportError:
        sys.exit()
    return frame_processor_module


def get_frame_processors_modules(frame_processors: List[str]) -> List[ModuleType]:
    global FRAME_PROCESSORS_MODULES

    if not FRAME_PROCESSORS_MODULES:
        for frame_processor in frame_processors:
            frame_processor_module = load_frame_processor_module(frame_processor)
            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
    set_frame_processors_modules_from_ui(frame_processors)
    return FRAME_PROCESSORS_MODULES

def set_frame_processors_modules_from_ui(frame_processors: List[str]) -> None:
    global FRAME_PROCESSORS_MODULES
    for frame_processor, state in modules.globals.fp_ui.items():
        if state == True and frame_processor not in frame_processors:
            frame_processor_module = load_frame_processor_module(frame_processor)
            FRAME_PROCESSORS_MODULES.append(frame_processor_module)
            modules.globals.frame_processors.append(frame_processor)
        if state == False:
            frame_processor_module = load_frame_processor_module(frame_processor)
            try:
                FRAME_PROCESSORS_MODULES.remove(frame_processor_module)
                modules.globals.frame_processors.remove(frame_processor)
            except:
                pass

def multi_process_frame(source_path: str, temp_frame_paths: List[str], process_frames: Callable[[str, List[str], Any], None], progress: Any = None) -> None:
    with ThreadPoolExecutor(max_workers=modules.globals.execution_threads) as executor:
        futures = []
        for path in temp_frame_paths:
            future = executor.submit(process_frames, source_path, [path], progress)
            futures.append(future)
        for future in futures:
            future.result()


def process_video(source_path: str, frame_paths: list[str], process_frames: Callable[[str, List[str], Any], None]) -> None:
    progress_bar_format = '{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}{postfix}]'
    total = len(frame_paths)
    with tqdm(total=total, desc='Processing', unit='frame', dynamic_ncols=True, bar_format=progress_bar_format) as progress:
        progress.set_postfix({'execution_providers': modules.globals.execution_providers, 'execution_threads': modules.globals.execution_threads, 'max_memory': modules.globals.max_memory})
        multi_process_frame(source_path, frame_paths, process_frames, progress)

modules/processors/frame/core.py
hacksider/Deep-Live-Cam
from typing import Any, List
import cv2
import threading
import gfpgan

import modules.globals
import modules.processors.frame.core
from modules.core import update_status
from modules.face_analyser import get_one_face
from modules.typing import Frame, Face
from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video

FACE_ENHANCER = None
THREAD_SEMAPHORE = threading.Semaphore()
THREAD_LOCK = threading.Lock()
NAME = 'DLC.FACE-ENHANCER'


def pre_check() -> bool:
    download_directory_path = resolve_relative_path('..\models')
    conditional_download(download_directory_path, ['https://github.com/TencentARC/GFPGAN/releases/download/v1.3.4/GFPGANv1.4.pth'])
    return True


def pre_start() -> bool:
    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
        update_status('Select an image or video for target path.', NAME)
        return False
    return True


def get_face_enhancer() -> Any:
    global FACE_ENHANCER

    with THREAD_LOCK:
        if FACE_ENHANCER is None:
            model_path = resolve_relative_path('..\models\GFPGANv1.4.pth')
            # todo: set models path https://github.com/TencentARC/GFPGAN/issues/399
            FACE_ENHANCER = gfpgan.GFPGANer(model_path=model_path, upscale=1) # type: ignore[attr-defined]
    return FACE_ENHANCER


def enhance_face(temp_frame: Frame) -> Frame:
    with THREAD_SEMAPHORE:
        _, _, temp_frame = get_face_enhancer().enhance(
            temp_frame,
            paste_back=True
        )
    return temp_frame


def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
    target_face = get_one_face(temp_frame)
    if target_face:
        temp_frame = enhance_face(temp_frame)
    return temp_frame


def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
    for temp_frame_path in temp_frame_paths:
        temp_frame = cv2.imread(temp_frame_path)
        result = process_frame(None, temp_frame)
        cv2.imwrite(temp_frame_path, result)
        if progress:
            progress.update(1)


def process_image(source_path: str, target_path: str, output_path: str) -> None:
    target_frame = cv2.imread(target_path)
    result = process_frame(None, target_frame)
    cv2.imwrite(output_path, result)


def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
    modules.processors.frame.core.process_video(None, temp_frame_paths, process_frames)

modules/processors/frame/face_enhancer.py
hacksider/Deep-Live-Cam
from typing import Any, List
import cv2
import insightface
import threading

import modules.globals
import modules.processors.frame.core
from modules.core import update_status
from modules.face_analyser import get_one_face, get_many_faces
from modules.typing import Face, Frame
from modules.utilities import conditional_download, resolve_relative_path, is_image, is_video

FACE_SWAPPER = None
THREAD_LOCK = threading.Lock()
NAME = 'DLC.FACE-SWAPPER'


def pre_check() -> bool:
    download_directory_path = resolve_relative_path('../models')
    conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128_fp16.onnx'])
    return True


def pre_start() -> bool:
    if not is_image(modules.globals.source_path):
        update_status('Select an image for source path.', NAME)
        return False
    elif not get_one_face(cv2.imread(modules.globals.source_path)):
        update_status('No face in source path detected.', NAME)
        return False
    if not is_image(modules.globals.target_path) and not is_video(modules.globals.target_path):
        update_status('Select an image or video for target path.', NAME)
        return False
    return True


def get_face_swapper() -> Any:
    global FACE_SWAPPER

    with THREAD_LOCK:
        if FACE_SWAPPER is None:
            model_path = resolve_relative_path('../models/inswapper_128_fp16.onnx')
            FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers)
    return FACE_SWAPPER


def swap_face(source_face: Face, target_face: Face, temp_frame: Frame) -> Frame:
    return get_face_swapper().get(temp_frame, target_face, source_face, paste_back=True)


def process_frame(source_face: Face, temp_frame: Frame) -> Frame:
    if modules.globals.many_faces:
        many_faces = get_many_faces(temp_frame)
        if many_faces:
            for target_face in many_faces:
                temp_frame = swap_face(source_face, target_face, temp_frame)
    else:
        target_face = get_one_face(temp_frame)
        if target_face:
            temp_frame = swap_face(source_face, target_face, temp_frame)
    return temp_frame


def process_frames(source_path: str, temp_frame_paths: List[str], progress: Any = None) -> None:
    source_face = get_one_face(cv2.imread(source_path))
    for temp_frame_path in temp_frame_paths:
        temp_frame = cv2.imread(temp_frame_path)
        try:
            result = process_frame(source_face, temp_frame)
            cv2.imwrite(temp_frame_path, result)
        except Exception as exception:
            print(exception)
            pass
        if progress:
            progress.update(1)


def process_image(source_path: str, target_path: str, output_path: str) -> None:
    source_face = get_one_face(cv2.imread(source_path))
    target_frame = cv2.imread(target_path)
    result = process_frame(source_face, target_frame)
    cv2.imwrite(output_path, result)


def process_video(source_path: str, temp_frame_paths: List[str]) -> None:
    modules.processors.frame.core.process_video(source_path, temp_frame_paths, process_frames)

modules/processors/frame/face_swapper.py
hacksider/Deep-Live-Cam
from typing import Any

from insightface.app.common import Face
import numpy

Face = Face
Frame = numpy.ndarray[Any, Any]

modules/typing.py
hacksider/Deep-Live-Cam
import os
import webbrowser
import customtkinter as ctk
from typing import Callable, Tuple
import cv2
from PIL import Image, ImageOps

import modules.globals
import modules.metadata
from modules.face_analyser import get_one_face
from modules.capturer import get_video_frame, get_video_frame_total
from modules.processors.frame.core import get_frame_processors_modules
from modules.utilities import is_image, is_video, resolve_relative_path

ROOT = None
ROOT_HEIGHT = 700
ROOT_WIDTH = 600

PREVIEW = None
PREVIEW_MAX_HEIGHT = 700
PREVIEW_MAX_WIDTH = 1200

RECENT_DIRECTORY_SOURCE = None
RECENT_DIRECTORY_TARGET = None
RECENT_DIRECTORY_OUTPUT = None

preview_label = None
preview_slider = None
source_label = None
target_label = None
status_label = None

img_ft, vid_ft = modules.globals.file_types


def init(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
    global ROOT, PREVIEW

    ROOT = create_root(start, destroy)
    PREVIEW = create_preview(ROOT)

    return ROOT


def create_root(start: Callable[[], None], destroy: Callable[[], None]) -> ctk.CTk:
    global source_label, target_label, status_label

    ctk.deactivate_automatic_dpi_awareness()
    ctk.set_appearance_mode('system')
    ctk.set_default_color_theme(resolve_relative_path('ui.json'))

    root = ctk.CTk()
    root.minsize(ROOT_WIDTH, ROOT_HEIGHT)
    root.title(f'{modules.metadata.name} {modules.metadata.version} {modules.metadata.edition}')
    root.configure()
    root.protocol('WM_DELETE_WINDOW', lambda: destroy())

    source_label = ctk.CTkLabel(root, text=None)
    source_label.place(relx=0.1, rely=0.1, relwidth=0.3, relheight=0.25)

    target_label = ctk.CTkLabel(root, text=None)
    target_label.place(relx=0.6, rely=0.1, relwidth=0.3, relheight=0.25)

    source_button = ctk.CTkButton(root, text='Select a face', cursor='hand2', command=lambda: select_source_path())
    source_button.place(relx=0.1, rely=0.4, relwidth=0.3, relheight=0.1)

    target_button = ctk.CTkButton(root, text='Select a target', cursor='hand2', command=lambda: select_target_path())
    target_button.place(relx=0.6, rely=0.4, relwidth=0.3, relheight=0.1)

    keep_fps_value = ctk.BooleanVar(value=modules.globals.keep_fps)
    keep_fps_checkbox = ctk.CTkSwitch(root, text='Keep fps', variable=keep_fps_value, cursor='hand2', command=lambda: setattr(modules.globals, 'keep_fps', not modules.globals.keep_fps))
    keep_fps_checkbox.place(relx=0.1, rely=0.6)

    keep_frames_value = ctk.BooleanVar(value=modules.globals.keep_frames)
    keep_frames_switch = ctk.CTkSwitch(root, text='Keep frames', variable=keep_frames_value, cursor='hand2', command=lambda: setattr(modules.globals, 'keep_frames', keep_frames_value.get()))
    keep_frames_switch.place(relx=0.1, rely=0.65)

    # for FRAME PROCESSOR ENHANCER tumbler:
    enhancer_value = ctk.BooleanVar(value=modules.globals.fp_ui['face_enhancer'])
    enhancer_switch = ctk.CTkSwitch(root, text='Face Enhancer', variable=enhancer_value, cursor='hand2', command=lambda: update_tumbler('face_enhancer',enhancer_value.get()))
    enhancer_switch.place(relx=0.1, rely=0.7)

    keep_audio_value = ctk.BooleanVar(value=modules.globals.keep_audio)
    keep_audio_switch = ctk.CTkSwitch(root, text='Keep audio', variable=keep_audio_value, cursor='hand2', command=lambda: setattr(modules.globals, 'keep_audio', keep_audio_value.get()))
    keep_audio_switch.place(relx=0.6, rely=0.6)

    many_faces_value = ctk.BooleanVar(value=modules.globals.many_faces)
    many_faces_switch = ctk.CTkSwitch(root, text='Many faces', variable=many_faces_value, cursor='hand2', command=lambda: setattr(modules.globals, 'many_faces', many_faces_value.get()))
    many_faces_switch.place(relx=0.6, rely=0.65)

    nsfw_value = ctk.BooleanVar(value=modules.globals.nsfw)
    nsfw_switch = ctk.CTkSwitch(root, text='NSFW', variable=nsfw_value, cursor='hand2', command=lambda: setattr(modules.globals, 'nsfw', nsfw_value.get()))
    nsfw_switch.place(relx=0.6, rely=0.7)

    start_button = ctk.CTkButton(root, text='Start', cursor='hand2', command=lambda: select_output_path(start))
    start_button.place(relx=0.15, rely=0.80, relwidth=0.2, relheight=0.05)

    stop_button = ctk.CTkButton(root, text='Destroy', cursor='hand2', command=lambda: destroy())
    stop_button.place(relx=0.4, rely=0.80, relwidth=0.2, relheight=0.05)

    preview_button = ctk.CTkButton(root, text='Preview', cursor='hand2', command=lambda: toggle_preview())
    preview_button.place(relx=0.65, rely=0.80, relwidth=0.2, relheight=0.05)

    live_button = ctk.CTkButton(root, text='Live', cursor='hand2', command=lambda: webcam_preview())
    live_button.place(relx=0.40, rely=0.86, relwidth=0.2, relheight=0.05)

    status_label = ctk.CTkLabel(root, text=None, justify='center')
    status_label.place(relx=0.1, rely=0.9, relwidth=0.8)

    donate_label = ctk.CTkLabel(root, text='Deep Live Cam', justify='center', cursor='hand2')
    donate_label.place(relx=0.1, rely=0.95, relwidth=0.8)
    donate_label.configure(text_color=ctk.ThemeManager.theme.get('URL').get('text_color'))
    donate_label.bind('<Button>', lambda event: webbrowser.open('https://paypal.me/hacksider'))

    return root


def create_preview(parent: ctk.CTkToplevel) -> ctk.CTkToplevel:
    global preview_label, preview_slider

    preview = ctk.CTkToplevel(parent)
    preview.withdraw()
    preview.title('Preview')
    preview.configure()
    preview.protocol('WM_DELETE_WINDOW', lambda: toggle_preview())
    preview.resizable(width=False, height=False)

    preview_label = ctk.CTkLabel(preview, text=None)
    preview_label.pack(fill='both', expand=True)

    preview_slider = ctk.CTkSlider(preview, from_=0, to=0, command=lambda frame_value: update_preview(frame_value))

    return preview


def update_status(text: str) -> None:
    status_label.configure(text=text)
    ROOT.update()


def update_tumbler(var: str, value: bool) -> None:
    modules.globals.fp_ui[var] = value


def select_source_path() -> None:
    global RECENT_DIRECTORY_SOURCE, img_ft, vid_ft

    PREVIEW.withdraw()
    source_path = ctk.filedialog.askopenfilename(title='select an source image', initialdir=RECENT_DIRECTORY_SOURCE, filetypes=[img_ft])
    if is_image(source_path):
        modules.globals.source_path = source_path
        RECENT_DIRECTORY_SOURCE = os.path.dirname(modules.globals.source_path)
        image = render_image_preview(modules.globals.source_path, (200, 200))
        source_label.configure(image=image)
    else:
        modules.globals.source_path = None
        source_label.configure(image=None)


def select_target_path() -> None:
    global RECENT_DIRECTORY_TARGET, img_ft, vid_ft

    PREVIEW.withdraw()
    target_path = ctk.filedialog.askopenfilename(title='select an target image or video', initialdir=RECENT_DIRECTORY_TARGET, filetypes=[img_ft, vid_ft])
    if is_image(target_path):
        modules.globals.target_path = target_path
        RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
        image = render_image_preview(modules.globals.target_path, (200, 200))
        target_label.configure(image=image)
    elif is_video(target_path):
        modules.globals.target_path = target_path
        RECENT_DIRECTORY_TARGET = os.path.dirname(modules.globals.target_path)
        video_frame = render_video_preview(target_path, (200, 200))
        target_label.configure(image=video_frame)
    else:
        modules.globals.target_path = None
        target_label.configure(image=None)


def select_output_path(start: Callable[[], None]) -> None:
    global RECENT_DIRECTORY_OUTPUT, img_ft, vid_ft

    if is_image(modules.globals.target_path):
        output_path = ctk.filedialog.asksaveasfilename(title='save image output file', filetypes=[img_ft], defaultextension='.png', initialfile='output.png', initialdir=RECENT_DIRECTORY_OUTPUT)
    elif is_video(modules.globals.target_path):
        output_path = ctk.filedialog.asksaveasfilename(title='save video output file', filetypes=[vid_ft], defaultextension='.mp4', initialfile='output.mp4', initialdir=RECENT_DIRECTORY_OUTPUT)
    else:
        output_path = None
    if output_path:
        modules.globals.output_path = output_path
        RECENT_DIRECTORY_OUTPUT = os.path.dirname(modules.globals.output_path)
        start()


def render_image_preview(image_path: str, size: Tuple[int, int]) -> ctk.CTkImage:
    image = Image.open(image_path)
    if size:
        image = ImageOps.fit(image, size, Image.LANCZOS)
    return ctk.CTkImage(image, size=image.size)


def render_video_preview(video_path: str, size: Tuple[int, int], frame_number: int = 0) -> ctk.CTkImage:
    capture = cv2.VideoCapture(video_path)
    if frame_number:
        capture.set(cv2.CAP_PROP_POS_FRAMES, frame_number)
    has_frame, frame = capture.read()
    if has_frame:
        image = Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
        if size:
            image = ImageOps.fit(image, size, Image.LANCZOS)
        return ctk.CTkImage(image, size=image.size)
    capture.release()
    cv2.destroyAllWindows()


def toggle_preview() -> None:
    if PREVIEW.state() == 'normal':
        PREVIEW.withdraw()
    elif modules.globals.source_path and modules.globals.target_path:
        init_preview()
        update_preview()
        PREVIEW.deiconify()


def init_preview() -> None:
    if is_image(modules.globals.target_path):
        preview_slider.pack_forget()
    if is_video(modules.globals.target_path):
        video_frame_total = get_video_frame_total(modules.globals.target_path)
        preview_slider.configure(to=video_frame_total)
        preview_slider.pack(fill='x')
        preview_slider.set(0)


def update_preview(frame_number: int = 0) -> None:
    if modules.globals.source_path and modules.globals.target_path:
        temp_frame = get_video_frame(modules.globals.target_path, frame_number)
        if modules.globals.nsfw == False:
            from modules.predicter import predict_frame
            if predict_frame(temp_frame):
                quit()
        for frame_processor in get_frame_processors_modules(modules.globals.frame_processors):
            temp_frame = frame_processor.process_frame(
                get_one_face(cv2.imread(modules.globals.source_path)),
                temp_frame
            )
        image = Image.fromarray(cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB))
        image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
        image = ctk.CTkImage(image, size=image.size)
        preview_label.configure(image=image)

def webcam_preview():
    if modules.globals.source_path is None:
        # No image selected
        return
    
    global preview_label, PREVIEW

    cap = cv2.VideoCapture(0)  # Use index for the webcam (adjust the index accordingly if necessary)    
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)  # Set the width of the resolution
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 360)  # Set the height of the resolution
    cap.set(cv2.CAP_PROP_FPS, 60)  # Set the frame rate of the webcam
    PREVIEW_MAX_WIDTH = 640
    PREVIEW_MAX_HEIGHT = 360

    preview_label.configure(image=None)  # Reset the preview image before startup

    PREVIEW.deiconify()  # Open preview window

    frame_processors = get_frame_processors_modules(modules.globals.frame_processors)

    source_image = None  # Initialize variable for the selected face image

    while True:
        ret, frame = cap.read()
        if not ret:
            break

        # Select and save face image only once
        if source_image is None and modules.globals.source_path:
            source_image = get_one_face(cv2.imread(modules.globals.source_path))

        temp_frame = frame.copy()  #Create a copy of the frame

        for frame_processor in frame_processors:
            temp_frame = frame_processor.process_frame(source_image, temp_frame)

        image = cv2.cvtColor(temp_frame, cv2.COLOR_BGR2RGB)  # Convert the image to RGB format to display it with Tkinter
        image = Image.fromarray(image)
        image = ImageOps.contain(image, (PREVIEW_MAX_WIDTH, PREVIEW_MAX_HEIGHT), Image.LANCZOS)
        image = ctk.CTkImage(image, size=image.size)
        preview_label.configure(image=image)
        ROOT.update()

    cap.release()
    PREVIEW.withdraw()  # Close preview window when loop is finished
modules/ui.py
hacksider/Deep-Live-Cam
import glob
import mimetypes
import os
import platform
import shutil
import ssl
import subprocess
import urllib
from pathlib import Path
from typing import List, Any
from tqdm import tqdm

import modules.globals

TEMP_FILE = 'temp.mp4'
TEMP_DIRECTORY = 'temp'

# monkey patch ssl for mac
if platform.system().lower() == 'darwin':
    ssl._create_default_https_context = ssl._create_unverified_context


def run_ffmpeg(args: List[str]) -> bool:
    commands = ['ffmpeg', '-hide_banner', '-hwaccel', 'auto', '-loglevel', modules.globals.log_level]
    commands.extend(args)
    try:
        subprocess.check_output(commands, stderr=subprocess.STDOUT)
        return True
    except Exception:
        pass
    return False


def detect_fps(target_path: str) -> float:
    command = ['ffprobe', '-v', 'error', '-select_streams', 'v:0', '-show_entries', 'stream=r_frame_rate', '-of', 'default=noprint_wrappers=1:nokey=1', target_path]
    output = subprocess.check_output(command).decode().strip().split('/')
    try:
        numerator, denominator = map(int, output)
        return numerator / denominator
    except Exception:
        pass
    return 30.0


def extract_frames(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
    run_ffmpeg(['-i', target_path, '-pix_fmt', 'rgb24', os.path.join(temp_directory_path, '%04d.png')])


def create_video(target_path: str, fps: float = 30.0) -> None:
    temp_output_path = get_temp_output_path(target_path)
    temp_directory_path = get_temp_directory_path(target_path)
    run_ffmpeg(['-r', str(fps), '-i', os.path.join(temp_directory_path, '%04d.png'), '-c:v', modules.globals.video_encoder, '-crf', str(modules.globals.video_quality), '-pix_fmt', 'yuv420p', '-vf', 'colorspace=bt709:iall=bt601-6-625:fast=1', '-y', temp_output_path])


def restore_audio(target_path: str, output_path: str) -> None:
    temp_output_path = get_temp_output_path(target_path)
    done = run_ffmpeg(['-i', temp_output_path, '-i', target_path, '-c:v', 'copy', '-map', '0:v:0', '-map', '1:a:0', '-y', output_path])
    if not done:
        move_temp(target_path, output_path)


def get_temp_frame_paths(target_path: str) -> List[str]:
    temp_directory_path = get_temp_directory_path(target_path)
    return glob.glob((os.path.join(glob.escape(temp_directory_path), '*.png')))


def get_temp_directory_path(target_path: str) -> str:
    target_name, _ = os.path.splitext(os.path.basename(target_path))
    target_directory_path = os.path.dirname(target_path)
    return os.path.join(target_directory_path, TEMP_DIRECTORY, target_name)


def get_temp_output_path(target_path: str) -> str:
    temp_directory_path = get_temp_directory_path(target_path)
    return os.path.join(temp_directory_path, TEMP_FILE)


def normalize_output_path(source_path: str, target_path: str, output_path: str) -> Any:
    if source_path and target_path:
        source_name, _ = os.path.splitext(os.path.basename(source_path))
        target_name, target_extension = os.path.splitext(os.path.basename(target_path))
        if os.path.isdir(output_path):
            return os.path.join(output_path, source_name + '-' + target_name + target_extension)
    return output_path


def create_temp(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
    Path(temp_directory_path).mkdir(parents=True, exist_ok=True)


def move_temp(target_path: str, output_path: str) -> None:
    temp_output_path = get_temp_output_path(target_path)
    if os.path.isfile(temp_output_path):
        if os.path.isfile(output_path):
            os.remove(output_path)
        shutil.move(temp_output_path, output_path)


def clean_temp(target_path: str) -> None:
    temp_directory_path = get_temp_directory_path(target_path)
    parent_directory_path = os.path.dirname(temp_directory_path)
    if not modules.globals.keep_frames and os.path.isdir(temp_directory_path):
        shutil.rmtree(temp_directory_path)
    if os.path.exists(parent_directory_path) and not os.listdir(parent_directory_path):
        os.rmdir(parent_directory_path)


def has_image_extension(image_path: str) -> bool:
    return image_path.lower().endswith(('png', 'jpg', 'jpeg'))


def is_image(image_path: str) -> bool:
    if image_path and os.path.isfile(image_path):
        mimetype, _ = mimetypes.guess_type(image_path)
        return bool(mimetype and mimetype.startswith('image/'))
    return False


def is_video(video_path: str) -> bool:
    if video_path and os.path.isfile(video_path):
        mimetype, _ = mimetypes.guess_type(video_path)
        return bool(mimetype and mimetype.startswith('video/'))
    return False


def conditional_download(download_directory_path: str, urls: List[str]) -> None:
    if not os.path.exists(download_directory_path):
        os.makedirs(download_directory_path)
    for url in urls:
        download_file_path = os.path.join(download_directory_path, os.path.basename(url))
        if not os.path.exists(download_file_path):
            request = urllib.request.urlopen(url) # type: ignore[attr-defined]
            total = int(request.headers.get('Content-Length', 0))
            with tqdm(total=total, desc='Downloading', unit='B', unit_scale=True, unit_divisor=1024) as progress:
                urllib.request.urlretrieve(url, download_file_path, reporthook=lambda count, block_size, total_size: progress.update(block_size)) # type: ignore[attr-defined]


def resolve_relative_path(path: str) -> str:
    return os.path.abspath(os.path.join(os.path.dirname(__file__), path))

modules/utilities.py
hacksider/Deep-Live-Cam
#!/usr/bin/env python3

from modules import core

if __name__ == '__main__':
    core.run()

run.py
hacksider/Deep-Live-Cam