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from fastai.vision.all import *
import gradio as gr
import pathlib

def is_cat(x): return x[0].isupper()

learn = load_learner('dogcatmodell.pkl')

categories = ('Cat', 'Dog')
def classify_image(img):
    pred, _, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

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

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