Update app.py

app.py

@@ -10,13 +10,13 @@ def predict(img):
     category, idx, probs = neural_net.predict(img)
     return dict(zip(labels, map(float, probs)))
     
-title = 'Natural Landscape Classifier'
+title = 'Natural Landscape Photo Classifier'
 description = 'Click an example photo or upload an image of your own!'
 examples = ['farm.jpg', 'lake.jpg', 'solar.jpg', 'neighborhood.jpg']
 inputs=gr.Image(type='pil',
                label='Photo')
 outputs = gr.Label(value={labels[i]: 0 for i in range(len(labels))},
-                  label='Your photo is a...',
+                  label='The photo is a...',
                   show_label=True)
 
 iface = gr.Interface(fn=predict,