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| import os | |
| import torch | |
| from comfy.model_management import CPUState # Импорт из того же файла | |
| # Отключаем CUDA, чтобы избежать инициализации | |
| os.environ["CUDA_VISIBLE_DEVICES"] = "" | |
| os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "" | |
| # Принудительно устанавливаем CPU режим | |
| import comfy.model_management | |
| comfy.model_management.cpu_state = CPUState.CPU | |
| import random | |
| import sys | |
| from typing import Sequence, Mapping, Any, Union | |
| import torch | |
| from PIL import Image | |
| from huggingface_hub import hf_hub_download | |
| import spaces | |
| import subprocess, sys | |
| import gradio | |
| import gradio_client | |
| import gradio as gr | |
| print("gradio version:", gradio.__version__) | |
| print("gradio_client version:", gradio_client.__version__) | |
| hf_hub_download(repo_id="facefusion/models-3.3.0", filename="hyperswap_1a_256.onnx", local_dir="models/hyperswap") | |
| hf_hub_download(repo_id="facefusion/models-3.3.0", filename="hyperswap_1b_256.onnx", local_dir="models/hyperswap") | |
| hf_hub_download(repo_id="facefusion/models-3.3.0", filename="hyperswap_1c_256.onnx", local_dir="models/hyperswap") | |
| hf_hub_download(repo_id="martintomov/comfy", filename="facedetection/yolov5l-face.pth", local_dir="models") | |
| ###hf_hub_download(repo_id="darkeril/collection", filename="detection_Resnet50_Final.pth", local_dir="models/facedetection") | |
| hf_hub_download(repo_id="gmk123/GFPGAN", filename="parsing_parsenet.pth", local_dir="models/facedetection") | |
| hf_hub_download(repo_id="MonsterMMORPG/tools", filename="1k3d68.onnx", local_dir="models/insightface/models/buffalo_l") | |
| hf_hub_download(repo_id="MonsterMMORPG/tools", filename="2d106det.onnx", local_dir="models/insightface/models/buffalo_l") | |
| hf_hub_download(repo_id="maze/faceX", filename="det_10g.onnx", local_dir="models/insightface/models/buffalo_l") | |
| hf_hub_download(repo_id="typhoon01/aux_models", filename="genderage.onnx", local_dir="models/insightface/models/buffalo_l") | |
| hf_hub_download(repo_id="maze/faceX", filename="w600k_r50.onnx", local_dir="models/insightface/models/buffalo_l") | |
| hf_hub_download(repo_id="vladmandic/insightface-faceanalysis", filename="buffalo_l.zip", local_dir="models/insightface/models/buffalo_l") | |
| def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any: | |
| """Returns the value at the given index of a sequence or mapping. | |
| If the object is a sequence (like list or string), returns the value at the given index. | |
| If the object is a mapping (like a dictionary), returns the value at the index-th key. | |
| Some return a dictionary, in these cases, we look for the "results" key | |
| Args: | |
| obj (Union[Sequence, Mapping]): The object to retrieve the value from. | |
| index (int): The index of the value to retrieve. | |
| Returns: | |
| Any: The value at the given index. | |
| Raises: | |
| IndexError: If the index is out of bounds for the object and the object is not a mapping. | |
| """ | |
| try: | |
| return obj[index] | |
| except KeyError: | |
| return obj["result"][index] | |
| def find_path(name: str, path: str = None) -> str: | |
| """ | |
| Recursively looks at parent folders starting from the given path until it finds the given name. | |
| Returns the path as a Path object if found, or None otherwise. | |
| """ | |
| # If no path is given, use the current working directory | |
| if path is None: | |
| path = os.getcwd() | |
| # Check if the current directory contains the name | |
| if name in os.listdir(path): | |
| path_name = os.path.join(path, name) | |
| print(f"{name} found: {path_name}") | |
| return path_name | |
| # Get the parent directory | |
| parent_directory = os.path.dirname(path) | |
| # If the parent directory is the same as the current directory, we've reached the root and stop the search | |
| if parent_directory == path: | |
| return None | |
| # Recursively call the function with the parent directory | |
| return find_path(name, parent_directory) | |
| def add_comfyui_directory_to_sys_path() -> None: | |
| """ | |
| Add 'ComfyUI' to the sys.path | |
| """ | |
| comfyui_path = find_path("ComfyUI") | |
| if comfyui_path is not None and os.path.isdir(comfyui_path): | |
| sys.path.append(comfyui_path) | |
| print(f"'{comfyui_path}' added to sys.path") | |
| def add_extra_model_paths() -> None: | |
| """ | |
| Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path. | |
| """ | |
| try: | |
| from main import load_extra_path_config | |
| except ImportError: | |
| print( | |
| "Could not import load_extra_path_config from main.py. Looking in utils.extra_config instead." | |
| ) | |
| from utils.extra_config import load_extra_path_config | |
| extra_model_paths = find_path("extra_model_paths.yaml") | |
| if extra_model_paths is not None: | |
| load_extra_path_config(extra_model_paths) | |
| else: | |
| print("Could not find the extra_model_paths config file.") | |
| add_comfyui_directory_to_sys_path() | |
| add_extra_model_paths() | |
| def import_custom_nodes() -> None: | |
| """Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS | |
| This function sets up a new asyncio event loop, initializes the PromptServer, | |
| creates a PromptQueue, and initializes the custom nodes. | |
| """ | |
| import asyncio | |
| import execution | |
| from nodes import init_extra_nodes | |
| import server | |
| # Creating a new event loop and setting it as the default loop | |
| loop = asyncio.new_event_loop() | |
| asyncio.set_event_loop(loop) | |
| # Creating an instance of PromptServer with the loop | |
| server_instance = server.PromptServer(loop) | |
| execution.PromptQueue(server_instance) | |
| # Initializing custom nodes | |
| # Запускаем корутину и ждём её завершения | |
| loop.run_until_complete(init_extra_nodes()) | |
| import_custom_nodes() | |
| from nodes import NODE_CLASS_MAPPINGS | |
| # --- Глобальная загрузка моделей (один раз при старте) --- | |
| loadimage = NODE_CLASS_MAPPINGS["LoadImage"]() | |
| vhs_loadvideo = NODE_CLASS_MAPPINGS["VHS_LoadVideo"]() | |
| reactoroptions = NODE_CLASS_MAPPINGS["ReActorOptions"]() | |
| vhs_videoinfoloaded = NODE_CLASS_MAPPINGS["VHS_VideoInfoLoaded"]() | |
| reactorfaceswapopt = NODE_CLASS_MAPPINGS["ReActorFaceSwapOpt"]() | |
| vhs_videocombine = NODE_CLASS_MAPPINGS["VHS_VideoCombine"]() | |
| # @spaces.GPU(duration=60) | |
| def generate_image(source_image, input_video, input_index, input_faces_order, swap_model, pingpong, loop_count, select_every_nth, use_audio): | |
| with torch.inference_mode(): | |
| loadimage_29 = loadimage.load_image(image=source_image) | |
| vhs_loadvideo_51 = vhs_loadvideo.load_video( | |
| video=input_video, | |
| force_rate=0, | |
| custom_width=0, | |
| custom_height=0, | |
| frame_load_cap=0, | |
| skip_first_frames=0, | |
| select_every_nth=select_every_nth, | |
| format="AnimateDiff", | |
| unique_id=17765013700631265033, | |
| ) | |
| reactoroptions_107 = reactoroptions.execute( | |
| input_faces_order=input_faces_order, | |
| input_faces_index=str(input_index), # Преобразуем в строку | |
| detect_gender_input="no", | |
| source_faces_order="large-small", | |
| source_faces_index="0", | |
| detect_gender_source="no", | |
| console_log_level=1, | |
| ) | |
| for q in range(1): | |
| vhs_videoinfoloaded_105 = vhs_videoinfoloaded.get_video_info( | |
| video_info=get_value_at_index(vhs_loadvideo_51, 3) | |
| ) | |
| reactorfaceswapopt_106 = reactorfaceswapopt.execute( | |
| enabled=True, | |
| swap_model=swap_model, # Используем выбранную модель | |
| facedetection="YOLOv5l", | |
| face_restore_model="none", | |
| face_restore_visibility=1, | |
| codeformer_weight=0.5, | |
| input_image=get_value_at_index(vhs_loadvideo_51, 0), | |
| source_image=get_value_at_index(loadimage_29, 0), | |
| options=get_value_at_index(reactoroptions_107, 0), | |
| ) | |
| # Формируем аргументы для combine_video | |
| combine_kwargs = dict( | |
| frame_rate=get_value_at_index(vhs_videoinfoloaded_105, 0), | |
| loop_count=loop_count, | |
| filename_prefix="vidswap", | |
| format="video/h264-mp4", | |
| pix_fmt="yuv420p", | |
| crf=20, | |
| save_metadata=False, | |
| trim_to_audio=False, | |
| pingpong=pingpong, | |
| save_output=True, | |
| images=get_value_at_index(reactorfaceswapopt_106, 0), | |
| unique_id=17889577966051683261, | |
| ) | |
| if use_audio: | |
| combine_kwargs["audio"] = get_value_at_index(vhs_loadvideo_51, 2) | |
| vhs_videocombine_28 = vhs_videocombine.combine_video(**combine_kwargs) | |
| saved_path = f"output/{vhs_videocombine_28['ui']['gifs'][0]['filename']}" | |
| return saved_path | |
| if __name__ == "__main__": | |
| with gr.Blocks() as app: | |
| with gr.Row(): | |
| with gr.Column(): | |
| # Вложенный Row для групп | |
| with gr.Row(): | |
| # Первая группа | |
| with gr.Group(): | |
| source_image = gr.Image(label="Source Image (Face)", type="filepath") | |
| swap_model = gr.Dropdown( | |
| choices=["hyperswap_1a_256.onnx", "hyperswap_1b_256.onnx", "hyperswap_1c_256.onnx"], | |
| value="hyperswap_1b_256.onnx", | |
| label="Swap Model" | |
| ) | |
| input_index = gr.Dropdown(choices=[0, 1, 2, 3, 4], value=0, label="Target Face Index") | |
| input_faces_order_dropdown = gr.Dropdown( | |
| choices=[ | |
| "left-right", | |
| "right-left", | |
| "top-bottom", | |
| "bottom-top", | |
| "large-small" | |
| ], | |
| value="large-small", # значение по умолчанию | |
| label="Target Faces Order") | |
| # Вторая группа (обратите внимание — она должна быть на том же уровне, что и первая) | |
| with gr.Group(): | |
| input_video = gr.Video(label="Target Video (Body)") | |
| select_every_nth = gr.Dropdown(choices=[1, 2], value=1, label='"1" = choose every frame, "2" - every second frame') | |
| loop_count = gr.Dropdown(choices=[0, 1, 2, 3, 4], value=0, label='"Loop_Count" = repeat loop append to your video') | |
| pingpong_checkbox = gr.Checkbox(label='"Pingpong" = reverse append to your video', value=False) | |
| audio_checkbox = gr.Checkbox(label='"Audio" = enable audio', value=False) | |
| # Кнопка генерации | |
| generate_btn = gr.Button("Check: Audio? Loop Count? Pingpong? Generate!") | |
| with gr.Column(): | |
| # Вывод результата | |
| output_video = gr.Video(label="Generated Video") | |
| # with gr.Accordion("Notes (click to open)", open=False): | |
| # gr.Markdown("Added text here") | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| text = """ | |
| ***Hyperswap_1b_256.onnx is the best (in most cases) - but model has inner bug - sometimes they produce "FAIL" swap (working, but do not do any swapping - on SOME faces. So, for stability - do test image to image face swap on one screenshot from your video first). Most stable version is Hyperswap_1a_256.onnx. | |
| ***Target_Face_Index: Index_0 = First Face. To switch for another target face - switch to Index_1, Index_2, e.t.c. | |
| ***Note: "1" or "2" - 'every frame' or 'every second frame' - if you have video 60fps or 48 fps - you can choose "2" to select every 2nd frame - for two time reduce total number of frames in video (got 30 fps and 24 fps video, accordingly). | |
| ***Video 05 sec * 24 fps = 120 frames/720p = takes 275 sec (4.5 min) for generating. Overall: SECONDS --> MINUTES. | |
| ***To cancel job - just close your browser's page. | |
| ***If needed, use AdvancedLivePortrait to correct faces on video before swapping. Here is [workflow](https://openart.ai/workflows/ocelot_vibrant_0/advanced-liveportrait-for-video-as-source/hV07PExjpK3JEd6kNnkr) for ComfyUI. | |
| ***Use Avidemux - simple but powerful freeware video editor. [Download](https://www.avidemux.org/nightly/) - choose win64 v2.8.2 for Windows 10. | |
| ***Use MediaInfo (freeware) to get information about video file - [Download](https://mediaarea.net/en/MediaInfo) | |
| ***Free and easy hosting for short mp4 files - [https://sendvid.com/](https://sendvid.com/) | |
| ***"ComfyUI Reactor Video Face Swap Hyperswap running directly on Gradio. - [How to convert your any ComfyUI workflow to Gradio](https://huggingface.co/blog/run-comfyui-workflows-on-spaces) | |
| """ | |
| gr.Markdown(text) | |
| # Связываем клик кнопки с функцией | |
| generate_btn.click( | |
| fn=generate_image, | |
| inputs=[source_image, input_video, input_index, input_faces_order_dropdown, swap_model, pingpong_checkbox, loop_count, select_every_nth, audio_checkbox], | |
| outputs=[output_video] | |
| ) | |
| app.launch(share=True) | |