Try different object

app.py

@@ -5,26 +5,10 @@ import gradio as gr
 # Cell
 learn = load_learner('model.pkl')
 
-# Cell
-# categories = ('Toronto, Canada', 'Denver, Colorado, USA', 'Emeryville, California, USA','Lehi, Utah, USA', 'Los Angeles, California, USA', 'College Park, Maryland, USA','Mexico City, Mexico', 'Arden Hills, Minnesota, USA', 'São Paulo, Brazil','New York, New York, USA', 'Portland, Oregon, USA', 'San Francisco, California, USA','Seattle, Washington, USA', 'Shanghai, China', 'Guangzhou, China', 'Hong Kong, China','Noida, India', 'Dublin, Ireland', 'Milan, Italy', 'Rome, Italy', 'Chisinau, Moldova','Amsterdam, Netherlands', 'Austin, Texas, USA', 'McLean, Virginia, USA','Washington D.C., USA', 'Atlanta, Georgia, USA', 'Waltham, Massachusetts, USA','Cambridge, Massachusetts, USA', 'San Jose, California, USA', 'Chicago, Illinois, USA','Ottawa, Canada', 'Bangalore, India', 'Mumbai, India', 'Gurgaon, India','Tokyo, Japan', 'Seoul, South Korea', 'Singapore, Singapore', 'Shenzhen, China','Bangkok, Thailand', 'Taipei, Taiwan', 'Melbourne, Australia', 'Sydney, Australia','Canberra, Australia', 'Yerevan, Armenia', 'Diegem, Belgium', 'Copenhagen, Denmark','Paris, France', 'Munich, Germany', 'Berlin, Germany', 'Hamburg, Germany','Basel, Switzerland', 'Zurich, Switzerland', 'Warsaw, Poland', 'Bucharest, Romania','Johannesburg, South Africa', 'Madrid, Spain', 'Barcelona, Spain', 'Stockholm, Sweden','Maidenhead, United Kingdom', 'London, United Kingdom', 'Edinburgh, Scotland')
-
-
 labels = learn.dls.vocab
 def predict(img):
     img = PILImage.create(img)
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-# def classify_image(img):
-#     pred,idx,probs = learn.predict(img)
-#     return dict(zip(categories, map(float,probs)))
-
-# Cell
-# image = gr.inputs.Image(shape=(192, 192))
-# label = gr.outputs.Label()
-# examples = []
-
-# intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
-# intf.launch(inline=False)
-
-gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
+gr.Interface(fn=predict, inputs=gr.Image(shape=(512, 512)), outputs=gr.Label(num_top_classes=3)).launch(share=True)