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

learn = load_learner('export.pkl')


labels = learn.dls.vocab

def predict(img):
   img = PILImage.create(img)
   img = img.resize((512, 512))
   pred,pred_idx,probs = learn.predict(img)
   return {labels[i]: float(probs[i]) for i in range(len(labels))}

examples = ['image1.jpg', 'image2.jpg']
interpretation='default'
enable_queue=True

gr.Interface(fn=predict, inputs=gr.components.Image(), outputs=gr.outputs.Label(num_top_classes=3), examples=examples, interpretation=interpretation, enable_queue=enable_queue).launch()