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

# determines if it's a cat from first letter
def is_cat(x): return x[0].isupper() 

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

categories = ('Dog', 'Cat')

def predict(img):
    pred,pred_idx,probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

# show it in a gradio interface
examples = [ 'cat1.png', 'dog1.png', 'python1.png']
gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(), examples=examples).launch()