import os import sys from typing import Any, Mapping, Sequence, Union import gradio as gr import torch from huggingface_hub import hf_hub_download from nodes import NODE_CLASS_MAPPINGS import spaces from comfy import model_management @spaces.GPU(duration=60) #modify the duration for the average it takes for your worflow to run, in seconds 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 app 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 init_extra_nodes() def advance_blur(input_image): import_custom_nodes() with torch.inference_mode(): load_images_node = NODE_CLASS_MAPPINGS["LoadImagesFromFolderKJ"]() source_images_batch = load_images_node.load_images( folder="source_faces/", width=1024, height=1024, keep_aspect_ratio="crop", image_load_cap=0, start_index=0, include_subfolders=False, ) loadimage = NODE_CLASS_MAPPINGS["LoadImage"]() loaded_input_image = loadimage.load_image( image=input_image, ) upscalemodelloader = NODE_CLASS_MAPPINGS["UpscaleModelLoader"]() upscale_model = upscalemodelloader.load_model( model_name="4x_NMKD-Siax_200k.pth" ) reactorbuildfacemodel = NODE_CLASS_MAPPINGS["ReActorBuildFaceModel"]() imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]() reactorfaceswap = NODE_CLASS_MAPPINGS["ReActorFaceSwap"]() imageupscalewithmodel = NODE_CLASS_MAPPINGS["ImageUpscaleWithModel"]() saveimage = NODE_CLASS_MAPPINGS["SaveImage"]() for q in range(1): face_model = reactorbuildfacemodel.blend_faces( save_mode=True, send_only=False, face_model_name="default", compute_method="Mean", images=get_value_at_index(source_images_batch, 0), ) resized_input_image = imageresize.execute( width=2560, height=2560, interpolation="bicubic", method="keep proportion", condition="downscale if bigger", multiple_of=0, image=get_value_at_index(loaded_input_image, 0), ) swapped_image = reactorfaceswap.execute( enabled=True, swap_model="inswapper_128.onnx", facedetection="retinaface_resnet50", face_restore_model="codeformer-v0.1.0.pth", face_restore_visibility=1, codeformer_weight=1, detect_gender_input="no", detect_gender_source="no", input_faces_index="0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99", source_faces_index="0", console_log_level=2, input_image=get_value_at_index(resized_input_image, 0), face_model=get_value_at_index(face_model, 0), ) upscaled_image = imageupscalewithmodel.upscale( upscale_model=get_value_at_index(upscale_model, 0), image=get_value_at_index(swapped_image, 0), ) final_image = imageresize.execute( width=2560, height=2560, interpolation="lanczos", method="keep proportion", condition="downscale if bigger", multiple_of=0, image=get_value_at_index(upscaled_image, 0), ) saved_image = saveimage.save_images( filename_prefix="advance_blur", images=get_value_at_index(final_image, 0), ) saved_path = f"output/{saved_image['ui']['images'][0]['filename']}" return saved_path if __name__ == "__main__": # Start your Gradio app with gr.Blocks() as app: # Add a title gr.Markdown("# Advance Blur") with gr.Row(): with gr.Column(): input_image = gr.Image(label="Input Image", type="filepath") generate_btn = gr.Button("Generate") with gr.Column(): # The output image output_image = gr.Image(label="Generated Image") # When clicking the button, it will trigger the `generate_image` function, with the respective inputs # and the output an image generate_btn.click( fn=advance_blur, inputs=[input_image], outputs=[output_image] ) app.launch(share=True)