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)