updated o/p format

app.py

@@ -20,9 +20,9 @@ def classify_images(img):
     elif (len(idxs[0]>1)):
         prob = sorted(probs, reverse=True)
         idxs = torch.where(probs==prob[0])
-        return learn.dls.vocab[idxs][0]
+        return "cat: "+learn.dls.vocab[idxs][0]+" ; "+"prob: "+str(probs[idxs].item())
     else:
-        return learn.dls.vocab[idxs][0]
+        return "cat: "+learn.dls.vocab[idxs][0]+" ; "+"prob: "+str(probs[idxs].item())
 
 image = gr.inputs.Image(shape=(192,192))
 label = gr.outputs.Label()