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

learn = load_learner('model.pkl')

categories = ('Flower','Sunflower')

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

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['images/0.png','images/1.png','images/2.png','images/3.png','images/4.png','images/5.png','images/6.png','images/7.png','images/8.png','images/9.png']

iface = gr.Interface(fn=classify, inputs=image, outputs=label, examples=examples)
iface.launch()