# import gradio as gr
#
# def greet(name):
#     return "Hello " + name + "!!"
#
# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()

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


def is_catan(x):
    # print(x[:5])
    # print(x[:5] == 'Catan')
    return x[:5] == 'Catan'


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

# Cell
# 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 = ['board-game-catan-IMG_4671.jpg', 'photo-of-macbook-catan-IMG_4817.jpg']

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