added extra condition to filter out the one with highest prob if the model should return a list

app.py

@@ -17,6 +17,10 @@ def classify_images(img):
     idxs = torch.where(probs>=0.90)
     if len(idxs[0])==0:
         return 'None'
+    elif (len(idxs[0]>1)):
+        prob = sorted(probs, reverse=True)
+        idxs = torch.where(probs==prob[0])
+        return learn.dls.vocab[idxs][0]
     else:
         return learn.dls.vocab[idxs][0]