Delete app.py

app.py

@@ -1,53 +0,0 @@
-import streamlit as st
-from diffusers import StableDiffusionPipeline
-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 v2-1 model!")
-
-# Sidebar for user inputs
-st.sidebar.title("Input Options")
-prompt = st.sidebar.text_input("Enter your prompt", "A futuristic cityscape at sunset, vibrant colors, 8k")
-generate_button = st.sidebar.button("Generate Image")
-
-# Load the pipeline when the app starts
-@st.cache_resource
-def load_pipeline():
-    # Use a smaller and more efficient model
-    pipe = StableDiffusionPipeline.from_pretrained(
-        "stabilityai/stable-diffusion-2-1", 
-        torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-        revision="fp16" if torch.cuda.is_available() else None
-    )
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    pipe = pipe.to(device)
-    return pipe
-
-pipe = load_pipeline()
-
-# Generate image when button is clicked
-if generate_button:
-    st.write(f"### Prompt: {prompt}")
-    with st.spinner("Generating image... Please wait."):
-        try:
-            # Generate the image
-            with torch.autocast("cuda" if torch.cuda.is_available() else "cpu"):
-                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"
-                )
-        except Exception as e:
-            st.error(f"An error occurred: {e}")