Initial commit hyperswap

20250929213116_OPTIM-FAIL_app.py

@@ -1,270 +0,0 @@
-import os
-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
-
-# ---------------------------------------------------------------------------------
-# 🛠️ Monkey-patch для gradio_client: игнорируем булевы схемы и не падаем на TypeError
-# ---------------------------------------------------------------------------------
-import gradio_client.utils as _gc_utils
-
-# Сохраняем оригинальные функции
-_orig_js2pt = _gc_utils._json_schema_to_python_type
-_orig_get_type = _gc_utils.get_type
-
-def _safe_json_schema_to_python_type(schema, defs=None):
-    """
-    Если schema — bool (True/False), возвращаем 'Any',
-    иначе — вызываем оригинальный код.
-    """
-    if isinstance(schema, bool):
-        return "Any"
-    return _orig_js2pt(schema, defs)
-
-def _safe_get_type(schema):
-    """
-    Если schema — bool, возвращаем 'Any',
-    иначе — вызываем оригинальную функцию get_type.
-    """
-    if isinstance(schema, bool):
-        return "Any"
-    return _orig_get_type(schema)
-
-# Заменяем в модуле
-_gc_utils._json_schema_to_python_type = _safe_json_schema_to_python_type
-_gc_utils.get_type               = _safe_get_type
-# ---------------------------------------------------------------------------------
-
-# Дальше уже можно безопасно импортировать Gradio
-
-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="ezioruan/inswapper_128.onnx", filename="inswapper_128.onnx", local_dir="models/insightface")
-hf_hub_download(repo_id="martintomov/comfy", filename="facerestore_models/GPEN-BFR-512.onnx", local_dir="models")
-
-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"]()
-reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
-saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
-
-@spaces.GPU(duration=20)
-def generate_image(source_image, target_image, target_index, swap_model, face_restore_model, restore_strength):
-    with torch.inference_mode():
-        loadimage_2 = loadimage.load_image(image=source_image)
-        loadimage_3 = loadimage.load_image(image=target_image)
-
-        reactorfaceswap_76 = reactorfaceswap.execute(
-            enabled=True,
-            swap_model=swap_model, # Используем выбранную модель
-            facedetection="YOLOv5l",
-            face_restore_model=face_restore_model,
-            face_restore_visibility=restore_strength,
-            codeformer_weight=0.5,
-            detect_gender_input="no",
-            detect_gender_source="no",
-            input_faces_index=str(target_index),  # Преобразуем в строку
-            source_faces_index="0",
-            console_log_level=1,
-            input_image=get_value_at_index(loadimage_3, 0),
-            source_image=get_value_at_index(loadimage_2, 0),
-        )
-
-        saveimage_77 = saveimage.save_images(
-            filename_prefix="ComfyUI",
-            images=get_value_at_index(reactorfaceswap_76, 0),
-        )
-
-        saved_path = f"output/{saveimage_77['ui']['images'][0]['filename']}"
-        return saved_path
-
-if __name__ == "__main__":
-    with gr.Blocks() as app:
-        # Заголовок
-        gr.Markdown("# ComfyUI Reactor Fast Face Swap Hyperswap")        
-
-        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=["inswapper_128.onnx", "hyperswap_1a_256.onnx", "hyperswap_1b_256.onnx", "hyperswap_1c_256.onnx"],
-                            value="hyperswap_1b_256.onnx",
-                            label="Swap Model"
-                        )
-                        face_restore_model = gr.Dropdown(choices=["none", "GPEN-BFR-512.onnx"], value="none", label="Face Restore Model")
-                        restore_strength = gr.Slider(minimum=0, maximum=1, step=0.05, value=0.7, label="Face Restore Strength")
-
-                    # Вторая группа (обратите внимание — она должна быть на том же уровне, что и первая)
-                    with gr.Group():
-                        target_image = gr.Image(label="Target Image (Body)", type="filepath")
-                        # restore_strength = gr.Slider(minimum=0, maximum=1, step=0.05, value=0.7, label="Face Restore Strength")
-                        target_index = gr.Dropdown(choices=[0, 1, 2, 3, 4], value=0, label="Target Face Index")
-                        gr.Markdown("Index_0 = Largest Face. To switch for another target face - switch to Index_1, Index_2, e.t.c")
-
-                # Кнопка генерации
-                generate_btn = gr.Button("Generate")
-                gr.Markdown(
-                    "***Hyperswap_1b_256.onnx is the best (in most cases) - but sometimes model produce FAIL swap (do not do any swapping). It's known inner bug."
-                )
-                gr.Markdown(
-                    "***Hyperswap models do not need Face Restorer - use it with None. Inswapper_128 need Face Restorer - use it with GPEN-BFR-512 at strenght 0.7-0.8."
-                )
-                gr.Markdown(
-                    "***ComfyUI Reactor Fast 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)"
-                )
-
-            with gr.Column():
-                # Вывод изображения
-                output_image = gr.Image(label="Generated Image")
-
-            # Связываем клик кнопки с функцией
-            generate_btn.click(
-                fn=generate_image,
-                inputs=[source_image, target_image, target_index, swap_model, face_restore_model, restore_strength],
-                outputs=[output_image]
-            )
-
-    app.launch(share=True)

app.py

@@ -142,21 +142,21 @@ def import_custom_nodes() -> None:
     # Initializing custom nodes
     # Запускаем корутину и ждём её завершения
     loop.run_until_complete(init_extra_nodes())
-#   init_extra_nodes()
 
 import_custom_nodes()
 from nodes import NODE_CLASS_MAPPINGS
 
-@spaces.GPU(duration=10)
+# --- Глобальная загрузка моделей (один раз при старте) ---
+loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
+reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
+saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
+
+@spaces.GPU
 def generate_image(source_image, target_image, target_index, swap_model, face_restore_model, restore_strength):
     with torch.inference_mode():
-        loadimage = NODE_CLASS_MAPPINGS["LoadImage"]()
         loadimage_2 = loadimage.load_image(image=source_image)
         loadimage_3 = loadimage.load_image(image=target_image)
 
-        reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]()
-        saveimage = NODE_CLASS_MAPPINGS["SaveImage"]()
-
         reactorfaceswap_76 = reactorfaceswap.execute(
             enabled=True,
             swap_model=swap_model, # Используем выбранную модель
@@ -210,12 +210,10 @@ if __name__ == "__main__":
 
                 # Кнопка генерации
                 generate_btn = gr.Button("Generate")
-                gr.Markdown(
-                    "***Hyperswap_1b_256.onnx is the best (in most cases) - but sometimes model produce FAIL swap (do not do any swapping). It's known inner bug."
-                )
-                gr.Markdown(
-                    "***Hyperswap models do not need Face Restorer - use it with None. Inswapper_128 need Face Restorer - use it with GPEN-BFR-512 at strenght 0.7-0.8."
-                )
+                gr.Markdown("***Hyperswap_1b_256.onnx is the best (in most cases) - but sometimes model produce FAIL swap (do not do any swapping). It's known inner bug.")
+                gr.Markdown("***Hyperswap models do not need Face Restorer - use it with None. Inswapper_128 need Face Restorer - use it with GPEN-BFR-512 at strenght 0.7-0.8.")
+            #   gr.Markdown("***Standard time of one generation - 23 sec per image.")
+                gr.Markdown("***Use Private window in your browser (this clear coockies) and SoftEther VPN (this change your IP) - for expand your limit.")
                 gr.Markdown(
                     "***ComfyUI Reactor Fast Face Swap Hyperswap running directly on Gradio. - "
                     "[How to convert your any ComfyUI workflow to Gradio]"