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CONTRIBUTING.md

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+Please always push on the experimental to ensure we don't mess with the main branch. All the test will be done on the experimental and will be pushed to the main branch after few days of testing.

models/instructions.txt

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+just put the models in this folder

modules/capturer.py

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+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/core.py

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+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/face_analyser.py

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+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/globals.py

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+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
+camera_input_combobox = None
+webcam_preview_running = False

modules/metadata.py

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+name = 'Deep Live Cam'
+version = '1.3.0'
+edition = 'Portable'

modules/predicter.py

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+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)