# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/app.ipynb.

# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
from fastai.vision.all import *
import gradio as gr
from pathlib import Path

project_dir = Path(__file__).parent

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

learn = load_learner("model.pkl")

categories = ("Dog", "Cat")

def classify_image(img):
    img = PILImage.create(img)
    _, _, probs = learn.predict(img)
    return dict(zip(categories, [float(p) for p in probs]))

image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = str((project_dir / "examples").absolute())
print(examples)
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label,
                    title = "Dog/Cat Classifier",
                    description = "A dog/cat classifier.",
                    examples=examples,
                    interpretation="default")
intf.launch()