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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) | |