import streamlit as st
from PIL import Image
import torch
from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline
import io

@st.cache_resource
def load_model():
    controlnet = ControlNetModel.from_pretrained("monster-labs/control_v1p_sdxl_qrcode_monster")
    pipeline = StableDiffusionXLControlNetPipeline.from_pretrained(
        "stabilityai/stable-diffusion-xl-base-1.0",
        controlnet=controlnet,
        torch_dtype=torch.float16
    )
    return pipeline.to("cuda" if torch.cuda.is_available() else "cpu")

pipeline = load_model()

st.title("QR Code Image Generator")

uploaded_file = st.file_uploader("Choose a QR code image", type=["png", "jpg", "jpeg"])
prompt = st.text_input("Enter your prompt")
num_inference_steps = st.slider("Number of inference steps", 1, 100, 30)
guidance_scale = st.slider("Guidance scale", 1.0, 20.0, 7.5)

if uploaded_file is not None and prompt:
    qr_image = Image.open(uploaded_file).convert("RGB")
    
    if st.button("Generate Image"):
        with st.spinner("Generating image..."):
            image = pipeline(
                prompt,
                image=qr_image,
                num_inference_steps=num_inference_steps,
                guidance_scale=guidance_scale
            ).images[0]
            
            st.image(image, caption="Generated Image")
            
            # Option to download the generated image
            buf = io.BytesIO()
            image.save(buf, format="PNG")
            btn = st.download_button(
                label="Download image",
                data=buf.getvalue(),
                file_name="generated_image.png",
                mime="image/png"
            )