__all__ = ['cloud_learn', 'classify_image', 'cloud_categories', 'cloud_examples', 'intf']

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

model_path = Path('models')
image_path = Path('images')

cloud_categories = (
  'Cirrus', 
  'Cirrostratus',
  'Cirrocumulus',
  'Altostratus',
  'Altocumulus',
  'Stratus',
  'Stratocumulus',
  'Nimbostratus',
  'Cumulus',
  'Cumulonimbus',
  'Lenticular'
)

cloud_examples = [str(image_path / f"{c}.jpg") for c in cloud_categories]
cloud_learn = load_learner(model_path/'cloudmodel.pkl')


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


intf = gr.Interface(fn=classify_image, 
    inputs=gr.inputs.Image(shape=(192, 192)), 
    outputs=gr.outputs.Label(), 
    examples=cloud_examples)

intf.launch(inline=False)