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

# %% auto 0
__all__ = ['learn', 'categories', 'examples', 'intf', 'label_func', 'classify_image']

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

# Define a labeling function: if filename starts with uppercase, it's a cat; otherwise, it's a dog
def label_func(f):
    # Return "Cat" for cat (uppercase first letter), "Dog" for dog (lowercase)
    return "Cat" if f[0].isupper() else "Dog"

# %% load.ipynb 3
learn = load_learner('catdog_model.pkl')

# %% load.ipynb 5
categories = ['Cat', 'Dog']

def classify_image(img):
    pred, pred_idx, probs = learn.predict(img)
    return {categories[i]: float(probs[i]) for i in range(len(categories))}

# %% load.ipynb 7
examples = ['examples/cat.jpg', 'examples/dog.jpeg', 'examples/catdog.png']

intf = gr.Interface(fn=classify_image, 
                    inputs=gr.Image(), 
                    outputs=gr.Label(),
                    examples=examples,
                    title="Cat vs Dog Classifier",
                    description="Upload an image of a cat or a dog, and the model will predict which it is.")
intf.launch(share=True, inline=False)