#!/usr/bin/env python from __future__ import annotations import gradio as gr import torch torch.jit.script = lambda f: f import spaces from app_canny import create_demo as create_demo_canny from app_depth import create_demo as create_demo_depth from model import Model from settings import ALLOW_CHANGING_BASE_MODEL, DEFAULT_MODEL_ID, SHOW_DUPLICATE_BUTTON from transformers.utils.hub import move_cache move_cache() DESCRIPTION = "ControlNet" if not torch.cuda.is_available(): DESCRIPTION += "\n
Running on CPU.
" model = Model(base_model_id=DEFAULT_MODEL_ID, task_name="Canny") with gr.Blocks(css="style.css") as demo: gr.Markdown(DESCRIPTION) gr.DuplicateButton( value="Duplicate Space for private use", elem_id="duplicate-button", visible=SHOW_DUPLICATE_BUTTON, ) with gr.Tabs(): with gr.TabItem("Depth"): create_demo_depth(model.process_depth) with gr.TabItem("Canny"): create_demo_canny(model.process_canny) with gr.Accordion(label="Base model", open=False): with gr.Row(): with gr.Column(scale=5): current_base_model = gr.Text(label="Current base model") with gr.Column(scale=1): check_base_model_button = gr.Button("Check current base model") with gr.Row(): with gr.Column(scale=5): new_base_model_id = gr.Text( label="New base model", max_lines=1, placeholder="runwayml/stable-diffusion-v1-5", info="The base model must be compatible with Stable Diffusion v1.5.", interactive=ALLOW_CHANGING_BASE_MODEL, ) with gr.Column(scale=1): change_base_model_button = gr.Button( "Change base model", interactive=ALLOW_CHANGING_BASE_MODEL ) if not ALLOW_CHANGING_BASE_MODEL: gr.Markdown( """The base model is not allowed to be changed in this Space so as not to slow down the demo, but it can be changed if you duplicate the Space.""" ) check_base_model_button.click( fn=lambda: model.base_model_id, outputs=current_base_model, queue=False, api_name="check_base_model", ) gr.on( triggers=[new_base_model_id.submit, change_base_model_button.click], fn=model.set_base_model, inputs=new_base_model_id, outputs=current_base_model, api_name=False, ) if __name__ == "__main__": demo.queue(max_size=20).launch()