import pathlib
import platform
if platform.system()=='Linux': pathlib.WindowsPath=pathlib.PosixPath

import dill
import gradio as gr

with open('model_dill.pkl','rb') as f: learn=dill.load(f)

labels=['Dog','Cat']

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

gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs=gr.Label(num_top_classes=2),
    examples=['dog.jpg','cat.jpg','dcat.jpg']
).launch()