Update app.py

app.py

@@ -54,7 +54,7 @@ def image_classifier(input_image, top_classes=3, show_cam=True, target_layers=[2
     o = softmax(output.flatten())
 
     confidences = {classes[i]: float(o[i]) for i in range(10)}
-    confidences_sorted = sorted(confidences.items(), key=lambda x:x[1],reverse=True)
+    confidences_sorted = dict(sorted(confidences.items(), key=lambda x:x[1],reverse=True))
     #confidences = dict(list(confidences_sorted.items())[0: top_classes])
     confidences = {k: confidences_sorted[k] for k in list(confidences_sorted)[:top_classes]}
     _, label = torch.max(output, 1)