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import streamlit as st
from diffusers import DiffusionPipeline
from PIL import Image
import torch
# Load the diffusion pipeline model
@st.cache_resource
def load_pipeline():
try:
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
pipe.load_lora_weights("kothariyashhh/GenAi-Texttoimage")
pipe = pipe.to("cuda") # Move model to GPU if available
return pipe
except Exception as e:
st.error(f"Error loading model: {e}")
return None
pipe = load_pipeline()
# Streamlit app
st.title("Text-to-Image Generation App")
# User input for prompt
user_prompt = st.text_input("Enter your image prompt", value="a photo of Yash Kothari with bike")
# Button to generate the image
if st.button("Generate Image"):
if user_prompt and pipe:
with st.spinner("Generating image..."):
try:
# Generate the image
image = pipe(user_prompt).images[0]
# Display the generated image
st.image(image, caption="Generated Image", use_column_width=True)
except Exception as e:
st.error(f"Error generating image: {e}")
else:
if not pipe:
st.error("Model not loaded. Please check the logs.")
else:
st.error("Please enter a valid prompt.")
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