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

learn = load_learner('model.pkl')

categories = ['abraham_grampa_simpson', 'agnes_skinner', 'apu_nahasapeemapetilon', 'barney_gumble', 
              'bart_simpson', 'carl_carlson', 'charles_montgomery_burns', 'chief_wiggum', 
              'cletus_spuckler', 'comic_book_guy', 'disco_stu', 'edna_krabappel', 'fat_tony', 
              'gil', 'groundskeeper_willie', 'homer_simpson', 'kent_brockman', 'krusty_the_clown', 
              'lenny_leonard', 'lionel_hutz', 'lisa_simpson', 'maggie_simpson', 'marge_simpson', 
              'martin_prince', 'mayor_quimby', 'milhouse_van_houten', 'miss_hoover', 'moe_szyslak', 
              'ned_flanders', 'nelson_muntz', 'otto_mann', 'patty_bouvier', 'principal_skinner', 
              'professor_john_frink', 'rainier_wolfcastle', 'ralph_wiggum', 'selma_bouvier', 
              'sideshow_bob', 'sideshow_mel', 'snake_jailbird', 'troy_mcclure', 'waylon_smithers']

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return {cat: float(prob) for cat, prob in zip(categories, probs)}

demo = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(),
    outputs=gr.Label(),
    examples=[
        'ednar.jpg',
        'maggie.jpg',
        'bart.jpg'
    ]
)

demo.launch()