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

# %% auto 0
__all__ = ['learn', 'image', 'label', 'intf', 'pet_class', 'classify_image']

# %% ../app.ipynb 1
from fastai.vision.all import *
import gradio as gr
import io
from PIL import Image

def pet_class(x): return x

# %% ../app.ipynb 2
learn = load_learner('model.pkl')

# %% ../app.ipynb 3
#categories = ('basketball ball','golf ball', 'rugby ball', 'soccer ball')

def classify_image(img, top_k=5):
    pred_class, pred_idx, probs = learn.predict(img)
    categories = learn.dls.vocab
    sorted_probs_indices = probs.argsort(descending=True)
    top_categories = [categories[i] for i in sorted_probs_indices[:top_k]]
    top_probs = probs[sorted_probs_indices[:top_k]]
    return dict(zip(top_categories, map(float, top_probs)))

# %% ../app.ipynb 4
image = gr.components.Image(shape=(192,192))
label = gr.components.Label()
#examples = ['basketball.png', 'golf_ball.jpg', 'rugby_ball.jpg', 'soccer_ball.jpg']

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