import gradio as gr
from fastai.learner import load_learner

categories = 'grizzly','black','teddy'
learn_inf = load_learner('model/trained_image_model.pkl')

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

image = gr.Image()
label = gr.Label()
examples = ["images/grizzly.jpg"]
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False, share=False)
# intf.launch(inline=False, share=True, auth=("admin", "pass1234"))

# demo = gr.Interface(
#     fn=greet,
#     inputs=["text", "slider"],
#     outputs=["text"],
#     analytics_enabled=False
# )

# demo.launch(auth=("admin", "pass1234"), share=True)