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

path = Path()
learn_inf = load_learner(path / 'export.pkl')

labels = ['beach', 'field', 'lake']

def predict(img):
    img = PILImage.create(img)
    pred, pred_idx, probs = learn_inf.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}


gr_interface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
                            outputs=gr.outputs.Label(num_top_classes=len(labels)), interpretation="default")

gr_interface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
                            outputs=gr.outputs.Label(num_top_classes=len(labels)),
                            interpretation="default")
gr_interface.launch()