#/export
from fastai.vision.all import *
import gradio as gr

learn = load_learner('export.pkl')
categories = ('primary', 'clear', 'agriculture', 'road', 'water', 'partly_cloudly', 'cultivation', 'habitation', 'haze', 'cloudy', 'bare_ground', 'selective_logging', 'artisinal_mine', 'blooming', 'slash_burn', 'blow_down', 'conventional_mine')
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()
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label)
intf.launch(inline=False)