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import streamlit as st
from diffusers import DiffusionPipeline
import torch
from PIL import Image
from io import BytesIO
# Load the diffusion pipeline
@st.cache_resource
def load_pipeline():
return DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0").to("cuda" if torch.cuda.is_available() else "cpu")
pipeline = load_pipeline()
def generate_image(prompt):
# Generate image
with torch.no_grad():
result = pipeline(prompt).images[0]
return result
def main():
st.title("Stable Diffusion Image Generator")
# Get user input
prompt = st.text_input("Enter a prompt for image generation:")
if st.button("Generate Image"):
if prompt:
# Generate and display the image
image = generate_image(prompt)
st.image(image, caption="Generated Image")
else:
st.warning("Please enter a prompt.")
if __name__ == "__main__":
main()
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