modified

app.py

@@ -90,7 +90,6 @@ if uploaded_file is not None:
     with col1:
         st.image(edges, caption=f"{edge_method} Edge Detection", use_container_width=True)  # Display the edge detection result
     with col2:
-        st.write("### Explanation")  # Show explanation header
         explanation = explain_ai(f"Explain how {edge_method} edge detection works in computer vision.")  # Get explanation from AI
         st.text_area("Explanation", explanation, height=300)  # Display explanation in a text area
 
@@ -113,7 +112,6 @@ if uploaded_file is not None:
     with col1:
         st.image(segmented, caption=f"{seg_method} Segmentation", use_container_width=True)  # Display segmentation result
     with col2:
-        st.write("### Explanation")  # Show explanation header
         explanation = explain_ai(f"Explain how {seg_method} segmentation works in image processing.")  # Get explanation from AI
         st.text_area("Explanation", explanation, height=300)  # Display explanation in a text area
 
@@ -125,7 +123,6 @@ if uploaded_file is not None:
     with col1:
         st.image(hog_image, caption="HOG Features", use_container_width=True)  # Display HOG feature image
     with col2:
-        st.write("### Explanation")  # Show explanation header
         explanation = explain_ai("Explain how Histogram of Oriented Gradients (HOG) feature extraction works.")  # Get explanation from AI
         st.text_area("Explanation", explanation, height=300)  # Display explanation in a text area
 
@@ -149,6 +146,5 @@ if uploaded_file is not None:
     with col1:
         st.image(predictions, caption=f"{model_choice} Pixel Classification", use_container_width=True)  # Display classification result
     with col2:
-        st.write("### Explanation")  # Show explanation header
         explanation = explain_ai(f"Explain how {model_choice} is used for image classification.")  # Get explanation from AI
         st.text_area("Explanation", explanation, height=300)  # Display explanation in a text area