from fastai.vision.all import *
import gradio as gr

def is_cat(x): return x[0].isupper() 

def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

learn = load_learner('model.pkl')
labels = learn.dls.vocab

input = gr.inputs.Image(shape=(512, 512))    
output = gr.outputs.Label(num_top_classes=3)

gr.Interface(fn=predict, inputs=input, outputs=output).launch(share=True)