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

learn = load_learner("classifier.pkl")

labels = learn.dls.vocab
examples = ['dolphin.jpg', 'shark.jpg', 'whale.jpg']

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

gr.Interface(fn=predict,
             inputs=gr.inputs.Image(shape=(512,512)),
             outputs=gr.outputs.Label(num_top_classes=3),
             examples=examples).launch(share=True, debug=False)