from fastai.vision.all import *
import gradio as gr
import timm
import dill
import os

learn = load_learner('./models/catan-model-paperspace-5.pkl', pickle_module=dill)
# learn = load_learner('catan-model.pkl', pickle_module=dill)

# categories = learn.dls.vocab
categories = ('Not Catan', 'Catan')


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


# Cell
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples_dir_path = './examples/'
examples = [(examples_dir_path + filename) for filename in os.listdir(examples_dir_path) if filename[:1] != '.']

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