workflow_api.py

import os
import random
import sys
from typing import Sequence, Mapping, Any, Union
import torch


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.
    """
    from main 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_custom_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_custom_nodes()


from nodes import SaveImage, NODE_CLASS_MAPPINGS, LoadImage


def main():
    import_custom_nodes()
    with torch.inference_mode():
        loadimage = LoadImage()
        loadimage_13 = loadimage.load_image(image="tree-736885_640.jpg")

        supir_model_loader = NODE_CLASS_MAPPINGS["SUPIR_model_loader"]()
        supir_model_loader_58 = supir_model_loader.process(
            supir_model="supir-voq.ckpt",
            sdxl_model="juggernautxl.safetensors",
            fp8_unet=False,
            diffusion_dtype="auto",
        )

        imageresize = NODE_CLASS_MAPPINGS["ImageResize+"]()
        imageresize_18 = imageresize.execute(
            width=1280,
            height=1280,
            interpolation="lanczos",
            keep_proportion=False,
            condition="always",
            multiple_of=0,
            image=get_value_at_index(loadimage_13, 0),
        )

        supir_first_stage = NODE_CLASS_MAPPINGS["SUPIR_first_stage"]()
        supir_first_stage_7 = supir_first_stage.process(
            use_tiled_vae=True,
            encoder_tile_size=512,
            decoder_tile_size=512,
            encoder_dtype="auto",
            SUPIR_VAE=get_value_at_index(supir_model_loader_58, 1),
            image=get_value_at_index(imageresize_18, 0),
        )

        supir_encode = NODE_CLASS_MAPPINGS["SUPIR_encode"]()
        supir_encode_21 = supir_encode.encode(
            use_tiled_vae=True,
            encoder_tile_size=512,
            encoder_dtype="auto",
            SUPIR_VAE=get_value_at_index(supir_first_stage_7, 0),
            image=get_value_at_index(supir_first_stage_7, 1),
        )

        supir_conditioner = NODE_CLASS_MAPPINGS["SUPIR_conditioner"]()
        supir_sample = NODE_CLASS_MAPPINGS["SUPIR_sample"]()
        supir_decode = NODE_CLASS_MAPPINGS["SUPIR_decode"]()
        image_comparer_rgthree = NODE_CLASS_MAPPINGS["Image Comparer (rgthree)"]()
        playsoundpysssss = NODE_CLASS_MAPPINGS["PlaySound|pysssss"]()
        colormatch = NODE_CLASS_MAPPINGS["ColorMatch"]()
        saveimage = SaveImage()

        for q in range(10):
            supir_conditioner_12 = supir_conditioner.condition(
                positive_prompt="a red car, high quality, detailed",
                negative_prompt="bad quality, blurry, messy",
                SUPIR_model=get_value_at_index(supir_model_loader_58, 0),
                latents=get_value_at_index(supir_first_stage_7, 2),
            )

            supir_sample_8 = supir_sample.sample(
                seed=random.randint(1, 2**64),
                steps=10,
                cfg_scale_start=5,
                cfg_scale_end=5,
                EDM_s_churn=5,
                s_noise=1.003,
                DPMPP_eta=1,
                control_scale_start=0.9,
                control_scale_end=0.9500000000000001,
                restore_cfg=10,
                keep_model_loaded=False,
                sampler="RestoreDPMPP2MSampler",
                sampler_tile_size=1024,
                sampler_tile_stride=512,
                SUPIR_model=get_value_at_index(supir_model_loader_58, 0),
                latents=get_value_at_index(supir_encode_21, 0),
                positive=get_value_at_index(supir_conditioner_12, 0),
                negative=get_value_at_index(supir_conditioner_12, 1),
            )

            supir_decode_9 = supir_decode.decode(
                use_tiled_vae=True,
                decoder_tile_size=512,
                SUPIR_VAE=get_value_at_index(supir_model_loader_58, 1),
                latents=get_value_at_index(supir_sample_8, 0),
            )

            image_comparer_rgthree_15 = image_comparer_rgthree.compare_images(
                image_a=get_value_at_index(loadimage_13, 0),
                image_b=get_value_at_index(supir_first_stage_7, 1),
            )

            playsoundpysssss_38 = playsoundpysssss.nop(
                mode="always",
                volume=0.5,
                file="notify.mp3",
                any=get_value_at_index(supir_decode_9, 0),
            )

            colormatch_57 = colormatch.colormatch(
                method="mkl",
                image_ref=get_value_at_index(loadimage_13, 0),
                image_target=get_value_at_index(supir_decode_9, 0),
            )

            saveimage_39 = saveimage.save_images(
                filename_prefix="SUPIR_", images=get_value_at_index(colormatch_57, 0)
            )

            image_comparer_rgthree_59 = image_comparer_rgthree.compare_images(
                image_a=get_value_at_index(colormatch_57, 0),
                image_b=get_value_at_index(loadimage_13, 0),
            )


if __name__ == "__main__":
    main()