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app.py
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import gradio as gr
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# Create title, description and article strings
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title = "DeepFundus 👀"
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description = "A ResNet50 feature extractor computer vision model to classify retina pathology from optical funduscopic images."
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article = "Created for fun."
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# Create the Gradio demo
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demo = gr.Interface(fn=predict, # mapping function from input to output
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inputs=gr.Image(type="pil"), # what are the inputs?
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outputs=[gr.Label(num_top_classes=8, label="Predictions"), # what are the outputs?
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gr.Number(label="Prediction time (s)")], # our fn has two outputs, therefore we have two outputs
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examples=example_list,
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title=title,
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description=description,
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article=article)
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# Launch the demo!
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demo.launch(debug=False, # print errors locally?
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share=True) # generate a publically shareable URL?
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