Create app.py

app.py

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+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+from PIL import Image
+import io
+import base64
+
+# Model ID
+model_id = "stabilityai/stable-diffusion-2-1"
+
+# Load the model from Hugging Face Hub
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
+
+# Streamlit app title and description
+st.title("Stable Diffusion Image Generation")
+st.write("Generate images using the Stability AI's Stable Diffusion model.")
+
+# Input for the prompt
+prompt = st.text_input("Enter a prompt for the image:")
+
+# Generate button
+if st.button("Generate Image"):
+    if prompt:
+        with st.spinner('Generating image...'):
+            # Generate image
+            image = pipe(prompt).images[0]
+
+            # Convert image to displayable format
+            buffered = io.BytesIO()
+            image.save(buffered, format="PNG")
+            img_str = base64.b64encode(buffered.getvalue()).decode()
+
+            # Display the image
+            st.image(image, caption="Generated Image", use_column_width=True)
+
+            # Option to download the image
+            st.markdown(
+                f'<a href="data:image/png;base64,{img_str}" download="generated_image.png">Download Image</a>',
+                unsafe_allow_html=True,
+            )
+    else:
+        st.error("Please enter a prompt to generate an image.")