Update app.py

app.py

@@ -76,11 +76,39 @@ def predict_2(image):
                                                   patches_img.shape[2], patches_img.shape[3]])
       
         unpatched_prediction = unpatchify(patched_prediction, (image.shape[0], image.shape[1]))
+        labels = LABEL_NAMES
+        res = np.bincount(unpatched_prediction)/unpatched_prediction.shape[0]
+        out = dict(list(zip(labels, res)))
         unpatched_prediction = targets_classes_colors[unpatched_prediction]
+        
 
-        return 'Predicted Masked Image', unpatched_prediction
-
-
+        return out, unpatched_prediction
+
+LABEL_NAMES = ["unlabeled",    
+               "paved-area",  
+                     "dirt", 
+                    "grass",    
+                   "gravel",  
+                    "water",   
+                    "rocks",   
+                     "pool",   
+               "vegetation",  
+                     "roof",  
+                     "wall",  
+                   "window",  
+                     "door",  
+                    "fence",  
+               "fence-pole",  
+                   "person",  
+                      "dog",  
+                      "car",    
+                  "bicycle",  
+                     "tree",   
+                "bald-tree",  
+                "ar-marker",  
+                 "obstacle",    
+              "conflicting",
+            ]
 targets_classes_colors = np.array([[  0,   0,   0],
                           [128,  64, 128],
                           [130,  76,   0],
@@ -162,7 +190,7 @@ with my_app:
             img_source = gr.Image(label="Please select source Image")
             source_image_loader = gr.Button("Load above Image")
         with gr.Column():
-            output_label = gr.Label(label="Image Info")
+            output_label = gr.Label(label="Predicted Masked Image")
             img_output = gr.Image(label="Image Output")
     source_image_loader.click(
         predict_2,