Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+import torch
+from transformers import AutoProcessor, AutoModelForVision2Seq
+
+# Load the PaliGemma model and processor
+@st.cache_resource
+def load_model():
+    model_name = "google/paligemma2-3b-mix-224"
+    processor = AutoProcessor.from_pretrained(model_name)
+    model = AutoModelForVision2Seq.from_pretrained(model_name)
+    return processor, model
+
+processor, model = load_model()
+
+# Streamlit UI
+st.title("🖼️ Image Q&A using PaliGemma")
+
+uploaded_file = st.file_uploader("Upload an Image", type=["png", "jpg", "jpeg"])
+
+if uploaded_file:
+    image = Image.open(uploaded_file).convert("RGB")
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    question = st.text_input("Ask a question about the image:")
+    if question:
+        # Process the image and question
+        inputs = processor(text=question, images=image, return_tensors="pt")
+        with torch.no_grad():
+            output = model.generate(**inputs)
+        
+        answer = processor.batch_decode(output, skip_special_tokens=True)[0]
+        st.success(f"Answer: {answer}")