app.py

app.py

@@ -1,42 +0,0 @@
-#import streamlit as st
-
-#x = st.slider('Select a value')
-#st.write(x)
-
-
-import torch
-from diffusers import StableDiffusionPipeline
-import streamlit as st
-from PIL import Image
-
-# Streamlit UI Setup
-st.title("Stable Diffusion Demo")
-
-# Text input for prompt
-prompt = st.text_input("Enter your prompt:", "A sunset over a mountain range")
-
-# Load the model once, so that it doesn't reload on every change
-@st.cache_resource
-def load_model():
-    pipe = StableDiffusionPipeline.from_pretrained(
-        "CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
-    )
-    pipe = pipe.to("cuda")
-    return pipe
-
-pipe = load_model()
-
-# Generate image on button click
-if st.button("Generate Image"):
-    with st.spinner("Generating image..."):
-        image = pipe(prompt).images[0]
-
-        # Display the generated image in the app
-        st.image(image, caption=f"Generated image for prompt: {prompt}")
-
-# Optionally, save the image
-if st.button("Save Image"):
-    file_name = "generated_image.png"
-    image.save(file_name)
-    st.success(f"Image saved as {file_name}")
-