Update app.py

app.py

@@ -61,8 +61,15 @@ def render_intent_bars(labels, percentages):
 def main():
     st.set_page_config(layout="wide")
     st.title("Shopping Intent Classification - SEO by DEJAN")
-    st.write("Multi-label image classification model [extracted from Chrome](https://dejanmarketing.com/product-image-optimisation-with-chromes-convolutional-neural-network/).
-    The model can be deployed in an automated pipeline capable of classifying product images in bulk. Enter a URL to fetch and classify all images on the page. Javascript-based website scraping currently unsupported.")
+    st.write("Enter a URL to fetch and classify all images on the page. Javascript-based website scraping currently unsupported.")
+    
+    st.markdown("""
+    Multi-label image classification model [extracted from Chrome](https://dejanmarketing.com/product-image-optimisation-with-chromes-convolutional-neural-network/).
+    The model can be deployed in an automated pipeline capable of classifying product images in bulk.
+
+    Interested in using this in an automated pipeline for bulk image classification?
+    Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
+    """)
 
     model_url = "https://huggingface.co/dejanseo/shopping-intent/resolve/main/model.tflite"
     model_path = "model.tflite"
@@ -83,7 +90,7 @@ def main():
                 "No Shopping Intent",
                 "Fashion & Style",
                 "Home & Garden",
-                "General"
+                "Tools, Vehicles, Electronics & Appliances"
             ]
 
             for img_url in img_urls:
@@ -106,11 +113,5 @@ def main():
                 except Exception as e:
                     st.write(f"Could not process image {img_url}: {e}")
 
-    # Additional information at the end
-    st.markdown("""
-    Interested in using this in an automated pipeline for bulk image classification?
-    Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
-    """)
-
 if __name__ == "__main__":
     main()