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

# Cell
learn = load_learner('/kaggle/input/kitchen-detector-model/model.pkl')

# Cell
categories = ('kitchen', 'not_kitchen')

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 = ['/kaggle/input/kitchen-data-set/kitchen-data-set/kitchen/209154559.jpeg', '/kaggle/input/kitchen-data-set/kitchen-data-set/not_kitchen/209154922.jpeg']

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