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

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

learn = load_learner('model.pkl')

categories = ('Dog', 'Cat')

#define funciton for gradio to call
def classify_image(img):
    pred,idx,probs = learn.predice(img)
    return dict(zip(categories, map(float,probs)))  #gradio wants a dict of labels and probabilities of each

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example)
intf.launch(inline=False)