app.py

import gradio as gr
import torch
import gradio as gr
from PIL import Image
import qrcode
from pathlib import Path
from multiprocessing import cpu_count
import requests
import io
import os
from PIL import Image

from diffusers import (
    DiffusionPipeline,
    StableDiffusionPipeline,
    StableDiffusionControlNetImg2ImgPipeline,
    ControlNetModel,
    DDIMScheduler,
    DPMSolverMultistepScheduler,
    DEISMultistepScheduler,
    HeunDiscreteScheduler,
    EulerDiscreteScheduler,
)

pipeline = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
def generate(prompt):
    return pipeline(prompt)

iface = gr.Interface(fn=generate, inputs="text", outputs="image")
iface.launch()