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


learn = load_learner('model.pkl')

categories = ('wet','tawny','horned')

def classify_image(img):
    pred,idx,probs = learn.predict(img)
    return dict(zip(categories, map(float,probs)))

image = gr.inputs.Image(shape=(224,224))
label = gr.outputs.label()
examples = ['harpy.jpg','horned.jpg']

iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch()