Update app.py

app.py

@@ -10,20 +10,19 @@ learn = load_learner("resnet152_fit_one_cycle_freeze_91acc.pkl", cpu=True)
 categories = ('arbanasi', 'filibe', 'gjirokoster', 'iskodra', 'kula', 'kuzguncuk', 'larissa_ampelakia', 'mardin', 'ohrid', 'pristina', 'safranbolu', 'selanik', 'sozopol_suzebolu', 'tiran', 'varna')
 def classify_img(img):
   pred,idx,probs=learn.predict(img)
-  return dict(zip(categories, map(float, probs))), img.split("/")[2]
+  return dict(zip(categories, map(float, probs)))
 
 image=gr.inputs.Image(shape=(128,128))
 label=gr.outputs.Label()
 examples_=[]
 for i in glob.glob("valid/**/*.jpg", recursive=True):
-    print(i)
     examples_.append(i)
 
-examples=["filibe-1-1.jpg",
-          "ohrid-3-1.jpg",
-          "varna-1-1.jpg"]
+#examples=["filibe-1-1.jpg",
+#          "ohrid-3-1.jpg",
+#          "varna-1-1.jpg"]
 
 
-demo = gr.Interface(fn=classify_img, inputs=image, outputs=[label,"text"], examples=examples_)
+demo = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples_)
 
 demo.launch(inline=False)