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


# Define a function for determining if image is a cat
def is_cat(x):
    return x[0].isupper()


# Load pretrained model
learn = load_learner("model.pkl")

categories = ("Dog", "Cat")


def classify_image(img):
    """
    Classify an image as a dog or cat.
    :param img: Image to classify
    :return: Dictionary of probabilities for each class
    """
    pred, 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 = ["dog.jpg", "cat.jpg", "tiger.jpg", "wolf.jpg"]

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