from fastai.vision.all import *
import gradio as gr
# from fastbook import * 
# from fastdownload import download_url

# def greet(name):
#     return "Hello " + name + "!!"

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()

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)))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
example = ['cat.jpg', 'dog.jpg']

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