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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() |