updated app.py

app.py

@@ -4,17 +4,21 @@ import skimage
 
 learn = load_learner('movements_05_02_22_4pm.pkl')
 
+labels = learn.dls.vocab
 def predict(img):
-    labels = learn.dls.vocab
     img = PILImage.create(img)
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 examples = [f"Image{n:02d}.jpg" for n in range(20)]
+interpretation='default'
+title = "Art Movement Classifier"
+description = "What Art Movement Matches the Image Best? Expressionism | Impressionism | Hudson River School | Ukiyo-e | Pre-Raphaelite"
 
 gr.Interface(fn=predict,
              inputs=gr.inputs.Image(shape=((512,512))),
              outputs=gr.outputs.Label(num_top_classes=5),
-             title = "Art Movements",
+             title = title,
              examples =  examples,
-             description= "What Art Movement Matches the Image Best? Expressionism | Impressionism | Hudson River School | Ukiyo-e | Pre-Raphaelite").launch(share=True, enable_queue=True)
+             interpretation = interpretation,
+             description = description).launch(share=True, enable_queue=True)