Update app.py

app.py

@@ -38,15 +38,15 @@ def classifier_app(image):
     top1 = round( prediction[0][top_indices[0][0]].item(), 4)
     top2 = round( prediction[0][top_indices[0][1]].item(), 4)
     top3 = round( prediction[0][top_indices[0][2]].item(), 4)
-    others = round(1.0 - top1 - top2-top3, 4)
+    others = round(1.0 - top1 - top2, 4)
 
     len_1 = len(id2label[top_indices[0][0]])
     len_2 = len(id2label[top_indices[0][1]])
-    len_3 = len(id2label[top_indices[0][2]])
-    max_length = max(len_1, len_2, len_3, len('Others'))
+ #   len_3 = len(id2label[top_indices[0][2]])
+    max_length = max(len_1, len_2, len('Others'))
 
-    labels = [f'{id2label[top_indices[0][0]]}'.ljust(max_length), f'{id2label[top_indices[0][1]]}'.ljust(max_length), f'{id2label[top_indices[0][2]]}'.ljust(max_length), f'Others'.ljust(max_length)]
-    preds = [top1, top2,top3, others]
+    labels = [f'{id2label[top_indices[0][0]]}'.ljust(max_length), f'{id2label[top_indices[0][1]]}'.ljust(max_length), f'Others'.ljust(max_length)]
+    preds = [top1, top2, others]
     result = {label : float(pred) for label, pred in zip(labels, preds)}
 
     return result
@@ -56,6 +56,7 @@ interface = gr.Interface(
     fn=classifier_app,
     inputs="image",
     examples = ['cat_1.jpg','cat_2.jpg','cat_3.jpg'],
-    outputs="label"
+    outputs="label",
+    share=True
 )
 interface.launch()