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

learn = load_learner('model_v4_98_percent_final.pkl')

categories = ('lotad', 'quagsire', 'slowpoke', 'snorlax')

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

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['lotad.jpg', 'quagsire.jpg', 'slowpoke.jpg', 'snorlax.jpg']

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()