app.py

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+
+learn = load_learner("export.pkl")
+
+categories = ("Diabetic Retinopathy", "No Diabetic Retinopathy")
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['002c21358ce6_noDR.png','0182152c50de_noDR.png','15bed5adde74_DR.png', '0ceb222f6629_DR.png']
+title = 'Diabetic Retinopathy Predictor'
+description = 'This app predicts diabetic retinopathy, a potentially blinding disease, from color fundus photograms. For reference only.'
+article = "Author: <a href=\"https://huggingface.co/archietram\">Archie Tram</a>. "
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title=title, description=description, article=article)
+intf.launch(inline=False)

requirements.txt

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+fastai