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

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

learner = load_learner("cat-dog-model.pkl")

categories = ["Dog", "Cat"]

def classify_image(im):
    _pred, _idx, probs = learner.predict(im)
    return dict(zip(categories, map(float, probs)))

# create interface

im = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ["dog.jpg", "cat.jpg", "cog.jpg", "cog2.png", "cog3.png"]
examples = [f"imgs/{im}" for im in examples]

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