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


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


# im = PILImage.create("dog.jpg")
# im.thumbnail((192, 192))
# im

learn = load_learner("model.pkl")
# learn.predict(im)

categories = ("Dog", "Cat")


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


# classify_image(im)

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)