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import streamlit as st
from diffusers import DiffusionPipeline
import torch
from PIL import Image
# Title and description of the app
st.title("🖼️ Stable Diffusion Image Generator")
st.write("Generate images from text using the Stable Diffusion v1.5 model!")
# Sidebar for user inputs
st.sidebar.title("Input Options")
prompt = st.sidebar.text_input("Enter your prompt", "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k")
generate_button = st.sidebar.button("Generate Image")
# Load the pipeline when the app starts
@st.cache_resource
def load_pipeline():
pipe = DiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
torch_dtype=torch.float16
)
device = "cuda" if torch.cuda.is_available() else "cpu"
return pipe.to(device)
pipe = load_pipeline()
# Generate image when button is clicked
if generate_button:
st.write(f"### Prompt: {prompt}")
with st.spinner("Generating image... Please wait."):
# Generate the image
image = pipe(prompt).images[0]
# Display the generated image
st.image(image, caption="Generated Image", use_column_width=True)
# Option to download the image
img_path = "generated_image.png"
image.save(img_path)
with open(img_path, "rb") as img_file:
st.download_button(
label="Download Image",
data=img_file,
file_name="generated_image.png",
mime="image/png"
)
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