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


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


learn = load_learner("model.pkl")
categories = ("Dog", "Cat")


def classify_image(img):
    # The prediction returns the prediction as a string, the index of the prediction and the probability
    prediction, idx, probability = learn.predict(img)
    return dict(zip(categories, map(float, probability)))


image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ["dog.jpg", "cat.jpg", "dunno.jpg"]

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