# import all the fastai stuff.
from fastai.vision.all import *

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

# load our model.
learn = load_learner('model.pkl')

# define a prediction function, not sure what this means.
labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    # this returns 
    #   predicted category
    #   index
    #   probabilities of each category
    pred,pred_idx,probs = learn.predict(img)
    # we return a weird dictionary or JSON?
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

import gradio as gr

gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch()