Bit-50-Glaucoma / app.py
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import gradio as gr
from transformers import pipeline
pipeline = pipeline(task="image-classification", model="Fu-chiang/bit-50-Glaucoma")
def predict(image):
predictions = pipeline(image)
return {p["label"]: p["score"] for p in predictions}
gr.Interface(
predict,
inputs=gr.inputs.Image(label="Upload the fundus image", type="filepath"),
outputs=gr.outputs.Label(num_top_classes=2),
title="Glaucoma or Normal?",
).launch()