app.py

#!/usr/bin/env python

from __future__ import annotations

import os
import pathlib
import shlex
import subprocess

import gradio as gr
import torch

from app_generated_image import create_prompt_demo
from app_real_image import create_real_image_demo

DESCRIPTION = "# [Plug-and-Play diffusion features](https://github.com/MichalGeyer/plug-and-play)"

if (SPACE_ID := os.getenv("SPACE_ID")) is not None:
    DESCRIPTION += f'\n<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings. <a href="https://huggingface.co/spaces/{SPACE_ID}?duplicate=true"><img style="display: inline; margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space" /></a></p>'
if not torch.cuda.is_available():
    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"

if torch.cuda.is_available():
    weight_dir = pathlib.Path("plug-and-play/models/ldm/stable-diffusion-v1")
    if not weight_dir.exists():
        subprocess.run(shlex.split("mkdir -p plug-and-play/models/ldm/stable-diffusion-v1/"))
        subprocess.run(
            shlex.split(
                "wget https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt -O plug-and-play/models/ldm/stable-diffusion-v1/model.ckpt"
            )
        )

with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)
    with gr.Tabs():
        with gr.TabItem("Use real image as input"):
            create_real_image_demo()
        with gr.TabItem("Use prompt as input"):
            create_prompt_demo()

if __name__ == "__main__":
    demo.queue(max_size=10).launch()