add built-in extension system

import os

from modules import paths

def preload(parser):

    parser.add_argument("--ldsr-models-path", type=str, help="Path to directory with LDSR model file(s).", default=os.path.join(paths.models_path, 'LDSR'))

from basicsr.utils.download_util import load_file_from_url

from modules.upscaler import Upscaler, UpscalerData

from modules.ldsr_model_arch import LDSR

from modules import shared

from ldsr_model_arch import LDSR

from modules import shared, script_callbacks

class UpscalerLDSR(Upscaler):

            return img

        ddim_steps = shared.opts.ldsr_steps

        return ldsr.super_resolution(img, ddim_steps, self.scale)

def on_ui_settings():

    import gradio as gr

    shared.opts.add_option("ldsr_steps", shared.OptionInfo(100, "LDSR processing steps. Lower = faster", gr.Slider, {"minimum": 1, "maximum": 200, "step": 1}, section=('upscaling', "Upscaling")))

script_callbacks.on_ui_settings(on_ui_settings)

import os

from modules import paths

def preload(parser):

    parser.add_argument("--scunet-models-path", type=str, help="Path to directory with ScuNET model file(s).", default=os.path.join(paths.models_path, 'ScuNET'))

import modules.upscaler

from modules import devices, modelloader

from modules.scunet_model_arch import SCUNet as net

from scunet_model_arch import SCUNet as net

class UpscalerScuNET(modules.upscaler.Upscaler):

        if model is None:

            return img

        device = devices.device_scunet

        device = devices.get_device_for('scunet')

        img = np.array(img)

        img = img[:, :, ::-1]

        img = np.moveaxis(img, 2, 0) / 255

        return PIL.Image.fromarray(output, 'RGB')

    def load_model(self, path: str):

        device = devices.device_scunet

        device = devices.get_device_for('scunet')

        if "http" in path:

            filename = load_file_from_url(url=self.model_url, model_dir=self.model_path, file_name="%s.pth" % self.name,

                                          progress=True)