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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_img(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()
examples = ['images/cat.jpeg', 'images/dog.jpeg', 'images/dogcat.jpeg']
intf = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples,
                    title = 'Cat vs Dog Images')
intf.launch()