Create app.py

app.py

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+import streamlit as st
+from transformers import PaliGemmaProcessor, PaliGemmaForConditionalGeneration
+from PIL import Image
+import torch
+import os
+
+def load_model():
+    """Load PaliGemma2 model and processor."""
+    processor = PaliGemmaProcessor.from_pretrained("google/paligemma2")
+    model = PaliGemmaForConditionalGeneration.from_pretrained("google/paligemma2")
+    return processor, model
+
+def process_image(image, processor, model):
+    """Extract text from image using PaliGemma2."""
+    # Preprocess the image
+    inputs = processor(images=image, return_tensors="pt")
+    
+    # Generate predictions
+    with torch.no_grad():
+        generated_ids = model.generate(**inputs)
+        text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    
+    return text
+
+def main():
+    # Set page configuration
+    st.set_page_config(page_title="Text Reading with PaliGemma2", layout="centered")
+    st.title("Text Reading from Images using PaliGemma2")
+
+    # Load model and processor
+    with st.spinner("Loading PaliGemma2 model... This may take a few moments."):
+        processor, model = load_model()
+    st.success("Model loaded successfully!")
+
+    # User input: upload image
+    uploaded_image = st.file_uploader("Upload an image containing text", type=["png", "jpg", "jpeg"])
+
+    if uploaded_image is not None:
+        # Display uploaded image
+        image = Image.open(uploaded_image)
+        st.image(image, caption="Uploaded Image", use_column_width=True)
+
+        # Extract text button
+        if st.button("Extract Text"):
+            with st.spinner("Processing image..."):
+                extracted_text = process_image(image, processor, model)
+                st.success("Text extraction complete!")
+                st.subheader("Extracted Text")
+                st.write(extracted_text)
+
+    # Footer
+    st.markdown("---")
+    st.markdown("**Built with [PaliGemma2](https://huggingface.co/google/paligemma2) and Streamlit**")
+
+if __name__ == "__main__":
+    main()