# AUTOGENERATED! DO NOT EDIT! File to edit: testnbdev.ipynb.
from fastai.vision.all import *
import gradio as gr

def is_cat(x): return x[0].isupper() 
learn = load_learner("model.pkl") 

categories = ('Dog', 'Cat')
def classify_image(img):
  pred,idx,probs = learn.predict(img)
  return dict(zip(categories, map(float,probs))) # need to understand this line. 

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples = ["cat.jpg", "dog.jpg", "grizzlybear.jpg", "box.jpg", "boxes.jpg", "dog_and_cat.jpg", "dog_and_cat2.jpg", "dog_and_cat3.png"]

iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
iface.launch()