import gradio as gr
from fastbook import *
from fastai.vision.widgets import *

categories = ('Kidby', 'Kirby', 'Simonetti')

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))
    
class PILImageRGBA(PILImage): _show_args,_open_args = {'cmap':'Viridis'},{'mode': 'RGB'} # Used for loading RGBA input images
    
learn = load_learner('model.pkl')

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ['kidby.jpg', 'kirby.jpg', 'simonetti.jpg']

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