diff --git a/modules/core.py b/modules/core.py index 3ec1617..25dd272 100644 --- a/modules/core.py +++ b/modules/core.py @@ -5,6 +5,8 @@ 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' +# Force TensorFlow to use Metal +os.environ['TENSORFLOW_METAL'] = '1' import warnings from typing import List import platform @@ -35,23 +37,17 @@ def parse_args() -> None: 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-fps', help='keep original fps', dest='keep_fps', action='store_true', default=True) 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('--keep-frames', help='keep temporary frames', dest='keep_frames', action='store_true', default=True) 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('--video-quality', help='adjust output video quality', dest='video_quality', type=int, default=50, 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-provider', help='execution provider', dest='execution_provider', default=['coreml'], 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 @@ -66,10 +62,9 @@ def parse_args() -> None: 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_providers = ['CoreMLExecutionProvider'] # Force CoreML 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: @@ -77,36 +72,6 @@ def parse_args() -> None: 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': @@ -115,39 +80,22 @@ def suggest_max_memory() -> int: def suggest_execution_providers() -> List[str]: - return encode_execution_providers(onnxruntime.get_available_providers()) + return ['coreml'] # Only suggest CoreML 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)) + memory = modules.globals.max_memory * 1024 ** 6 + import resource + resource.setrlimit(resource.RLIMIT_DATA, (memory, memory)) def release_resources() -> None: - if 'CUDAExecutionProvider' in modules.globals.execution_providers: - torch.cuda.empty_cache() + pass # No need to release CUDA resources def pre_check() -> bool: @@ -170,23 +118,28 @@ 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 + process_image() + else: + process_video() + + +def process_image(): + 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) + if is_image(modules.globals.target_path): + update_status('Processing to image succeed!') + else: + update_status('Processing to image failed!') + + +def process_video(): if modules.globals.nsfw == False: from modules.predicter import predict_video if predict_video(modules.globals.target_path): @@ -199,8 +152,6 @@ def start() -> None: 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) @@ -209,7 +160,6 @@ def start() -> None: 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...') @@ -218,7 +168,6 @@ def start() -> None: 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!') @@ -240,6 +189,69 @@ def run() -> None: if not frame_processor.pre_check(): return limit_resources() + print(f"ONNX Runtime version: {onnxruntime.__version__}") + print(f"Available execution providers: {onnxruntime.get_available_providers()}") + print(f"Selected execution provider: CoreMLExecutionProvider") + + # Configure ONNX Runtime to use only CoreML + onnxruntime.set_default_logger_severity(3) # Set to WARNING level + options = onnxruntime.SessionOptions() + options.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL + + # Test CoreML with a dummy model + try: + import numpy as np + from onnx import helper, TensorProto + + # Create a simple ONNX model + X = helper.make_tensor_value_info('input', TensorProto.FLOAT, [1, 3, 224, 224]) + Y = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1, 3, 224, 224]) + node = helper.make_node('Identity', ['input'], ['output']) + graph = helper.make_graph([node], 'test_model', [X], [Y]) + model = helper.make_model(graph) + + # Save the model + model_path = 'test_model.onnx' + with open(model_path, 'wb') as f: + f.write(model.SerializeToString()) + + # Create a CoreML session + session = onnxruntime.InferenceSession(model_path, options, providers=['CoreMLExecutionProvider']) + + # Run inference + input_data = np.random.rand(1, 3, 224, 224).astype(np.float32) + output = session.run(None, {'input': input_data}) + + print("CoreML init successful and being used") + print(f"Input shape: {input_data.shape}, Output shape: {output[0].shape}") + + # Clean up + os.remove(model_path) + except Exception as e: + print(f"Error testing CoreML: {str(e)}") + print("The application may not be able to use GPU acceleration") + + # Configure TensorFlow to use Metal + try: + tf_devices = tensorflow.config.list_physical_devices() + print("TensorFlow devices:", tf_devices) + if any('GPU' in device.name for device in tf_devices): + print("TensorFlow is using GPU (Metal)") + else: + print("TensorFlow is not using GPU") + except Exception as e: + print(f"Error configuring TensorFlow: {str(e)}") + + # Configure PyTorch to use MPS (Metal Performance Shaders) + try: + if torch.backends.mps.is_available(): + print("PyTorch is using MPS (Metal Performance Shaders)") + torch.set_default_device('mps') + else: + print("PyTorch MPS is not available") + except Exception as e: + print(f"Error configuring PyTorch: {str(e)}") + if modules.globals.headless: start() else: diff --git a/modules/processors/frame/face_swapper.py b/modules/processors/frame/face_swapper.py index 4b4a222..1e39ffd 100644 --- a/modules/processors/frame/face_swapper.py +++ b/modules/processors/frame/face_swapper.py @@ -17,7 +17,7 @@ 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']) + conditional_download(download_directory_path, ['https://huggingface.co/hacksider/deep-live-cam/blob/main/inswapper_128.onnx']) return True @@ -39,7 +39,7 @@ def get_face_swapper() -> Any: with THREAD_LOCK: if FACE_SWAPPER is None: - model_path = resolve_relative_path('../models/inswapper_128_fp16.onnx') + model_path = resolve_relative_path('../models/inswapper_128.onnx') FACE_SWAPPER = insightface.model_zoo.get_model(model_path, providers=modules.globals.execution_providers) return FACE_SWAPPER diff --git a/modules/ui.py b/modules/ui.py index 1d0bb69..220eec4 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -257,11 +257,11 @@ def webcam_preview(): 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, 960) # Set the width of the resolution - cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 540) # Set the height of the resolution + cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1024) # Set the width of the resolution + cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 768) # Set the height of the resolution cap.set(cv2.CAP_PROP_FPS, 60) # Set the frame rate of the webcam - PREVIEW_MAX_WIDTH = 960 - PREVIEW_MAX_HEIGHT = 540 + PREVIEW_MAX_WIDTH = 1024 + PREVIEW_MAX_HEIGHT = 768 preview_label.configure(image=None) # Reset the preview image before startup @@ -285,7 +285,7 @@ def webcam_preview(): 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 = 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) diff --git a/modules/utilities.py b/modules/utilities.py index 782395f..e3f5930 100644 --- a/modules/utilities.py +++ b/modules/utilities.py @@ -9,6 +9,7 @@ import urllib from pathlib import Path from typing import List, Any from tqdm import tqdm +import cv2 import modules.globals @@ -44,7 +45,19 @@ def detect_fps(target_path: str) -> float: 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')]) + cap = cv2.VideoCapture(target_path) + + frame_count = 0 + while True: + ret, frame = cap.read() + if not ret: + break + + # Save the frame + cv2.imwrite(os.path.join(temp_directory_path, f'{frame_count:04d}.png'), frame) + frame_count += 1 + + cap.release() def create_video(target_path: str, fps: float = 30.0) -> None: diff --git a/requirements.txt b/requirements.txt index f65195e..9396c93 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,23 +1,26 @@ ---extra-index-url https://download.pytorch.org/whl/cu118 +# Deep Live Cam requirements -numpy==1.23.5 +# Core dependencies +numpy==1.26.4 +onnxruntime-silicon==1.16.3 opencv-python==4.8.1.78 -onnx==1.16.0 -insightface==0.7.3 -psutil==5.9.8 -tk==0.1.0 -customtkinter==5.2.2 pillow==9.5.0 -torch==2.0.1+cu118; sys_platform != 'darwin' -torch==2.0.1; sys_platform == 'darwin' -torchvision==0.15.2+cu118; sys_platform != 'darwin' -torchvision==0.15.2; sys_platform == 'darwin' -onnxruntime==1.18.0; sys_platform == 'darwin' and platform_machine != 'arm64' -onnxruntime-silicon==1.16.3; sys_platform == 'darwin' and platform_machine == 'arm64' -onnxruntime-gpu==1.18.0; sys_platform != 'darwin' -tensorflow==2.13.0rc1; sys_platform == 'darwin' -tensorflow==2.12.1; sys_platform != 'darwin' -opennsfw2==0.10.2 -protobuf==4.23.2 +insightface==0.7.3 +torch==2.1.0 # Add the specific version you're using +tensorflow==2.16.1 # Add the specific version you're using + +# Image processing +scikit-image==0.24.0 +matplotlib==3.9.1.post1 + +# Machine learning +scikit-learn==1.5.1 + +# Utilities tqdm==4.66.4 -gfpgan==1.3.8 +requests==2.32.3 +prettytable==3.11.0 + +# Optional dependencies (comment out if not needed) +# albumentations==1.4.13 +# coloredlogs==15.0.1