Upload app.py

app.py

@@ -1,254 +1,254 @@
-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
-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="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
-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:
-        with gr.Row():
-            with gr.Column():
-                # Вложенный Row для групп (группы расположены горизонтально)
-                with gr.Row():
-                    # Первая группа
-                    with gr.Group():
-                        source_image = gr.Image(label="Source (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
-                    with gr.Group():
-                        target_image = gr.Image(label="Target (Body)", type="filepath")
-                        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")
-                        generate_btn = gr.Button("Generate")  # Кнопка генерации
-            
-            with gr.Column():
-                output_image = gr.Image(label="Generated Image")  # Вывод изображения
-                
-        with gr.Row():
-            with gr.Column(scale=1):
-                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("*** This Space uses only CPU. You have unlimited usage in HF Spaces on CPU.")
-                gr.Markdown("*** For avoiding queue - duplicate this space to your account (it's free). Top right corner - Three dots - Duplicate this Space. Make them Private. Enjoy!")
-                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)"
-                )
-                
-                # 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)
+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
+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="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
+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:
+        with gr.Row():
+            with gr.Column():
+                # Вложенный Row для групп (группы расположены горизонтально)
+                with gr.Row():
+                    # Первая группа
+                    with gr.Group():
+                        source_image = gr.Image(label="Source (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
+                    with gr.Group():
+                        target_image = gr.Image(label="Target (Body)", type="filepath")
+                        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")
+                        generate_btn = gr.Button("Generate")  # Кнопка генерации
+            
+            with gr.Column():
+                output_image = gr.Image(label="Generated Image")  # Вывод изображения
+                
+        with gr.Row():
+            with gr.Column(scale=1):
+                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 strength 0.7-0.8.")
+                gr.Markdown("*** This Space uses only CPU. You have unlimited usage in HF Spaces on CPU.")
+                gr.Markdown("*** For avoiding queue - duplicate this space to your account (it's free). Top right corner - Three dots - Duplicate this Space. Make them Private. Enjoy!")
+                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)"
+                )
+                
+                # 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)