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from fastai.vision.all import *
import gradio as gr
def is_glaucoma(x): return x[6] == 'g'
learn = load_learner('model2.pkl')
categories = ('Glaucoma', 'not Glaucoma')
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
image = gr.components.Image(height=192, width=192)
label = gr.components.Label()
examples = ['glaucoma.jpg', 'not glaucoma.jpg']
intf=gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)
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