# AUTOGENERATED! DO NOT EDIT! File to edit: DogCat.ipynb.

# %% auto 0
__all__ = ['temp', 'learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']

# %% DogCat.ipynb 1
from fastai.vision.all import *
import gradio as gr

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

# %% DogCat.ipynb 3
import pathlib

# Set the PosixPath to str
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath

# Load the model
learn = load_learner('model.pkl')

# Revert the change
pathlib.PosixPath = temp


# %% DogCat.ipynb 5
categories = ('Dog', 'Cat')

def classify_image(img):
    img = PILImage.create(img)
    img = img.resize((192, 192))
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

# %% DogCat.ipynb 7
image = gr.Image()
label = gr.Label()
examples = ['angry_chihuahua.png', 'CatOnCatnip.jpg', 'harrypotterDog.jpg', 'elbanialpxenu.jpg']

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