Update app.py

app.py

@@ -7,15 +7,12 @@ neural_net = load_learner('trained-NN.pkl')
 labels = neural_net.dls.vocab
 
 def predict(img):
-    # img = PILImage.create(img)
     category, idx, probs = neural_net.predict(img)
     return dict(zip(labels, map(float, probs)))
-    # return {'cat': 0.3, 'dog': 0.7}
-    # return img.rotate(45)
     
 title = 'Natural Landscape Classifier'
 
-examples = ['farm.png']
+examples = 'farm.png'
 
 iface = gr.Interface(fn=predict, 
                      inputs=gr.Image(type='pil'),