Create app.py

app.py

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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"
+            )