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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'outputs', 'examples', 'title', 'description', 'article', 'interpretation',
'enable_queue', 'is_cat', 'classify_image']
# %% app.ipynb 2
import gradio as gr
from fastai.vision.all import *
def is_cat(x): return x[0].isupper()
# %% app.ipynb 4
learn = load_learner('model.pkl')
# %% app.ipynb 6
categories = ('Dog', 'Cat')
def classify_image(img):
pred,pred_idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# return {labels[i]: float(probs[i]) for i in range(len(labels))}
# %% app.ipynb 8
image = gr.inputs.Image(shape=(512, 512))
label = outputs=gr.outputs.Label()
examples = ['puppy.jpeg']
title = "Dog vs Cat Classifier"
description = "A Dog vs Cat classifier trained on the Oxford Pets dataset with fastai."
article="<p style='text-align: center'><a href='https://sirgil.org' target='_blank'>Sirgil Home</a></p>"
interpretation='default'
enable_queue=True
gr.Interface(fn=classify_image,inputs=image,outputs=label,title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
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