#using gradio for deployment:
from fastai.vision.all import *
import gradio as gr

def is_bear(x): return x[0].isupper()

learn = load_learner("model.pkl")

categories = ("grizzly bears", "black bears", "teddy bears")

#Since gradio doesnt recognize tensors, we are uasing map function:
def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples =["black_teddy.jpg", "grizzly_bear.jpg", "black_bear.jpg"]

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