Update app.py

app.py

@@ -225,7 +225,7 @@ def segment_image(image):
     # overlayed_img_modernity_pil = Image.fromarray(cv2.cvtColor(overlayed_img_modernity, cv2.COLOR_BGR2RGB))
     # overlayed_img_typicality_pil = Image.fromarray(cv2.cvtColor(overlayed_img_typicality, cv2.COLOR_BGR2RGB))
 
-    return "Automobiles detected in the image", cropped_car_pil, modernity_scores, typicality_scores , most_similar_group#, overlayed_img_modernity_pil,  overlayed_img_typicality_pil
+    return "Automobiles detected in the image", cropped_car_pil, modernity_scores, typicality_scores , most_similar_group, overlayed_img_modernity_pil,  overlayed_img_typicality_pil
 
 
 # Create Gradio interface
@@ -238,8 +238,8 @@ iface = gr.Interface(
         gr.Textbox(label="Modernity Score"),
         gr.Textbox(label="Typicality Score"),
         gr.Textbox(label="most_similar_group"),
-        gr.Image(label="Grad-CAM for Type"),
-        gr.Image(label="Grad-CAM for Year")
+        gr.Image(label="Grad-CAM for Year"),
+        gr.Image(label="Grad-CAM for Type")
     ],
     title="Automobile Detection and Scoring using Mask R-CNN",
     description="Upload an image, and the system will detect and segment automobiles, crop the largest car, and predict its modernity and typicality scores. Grad-CAM heatmaps will also be generated."