gnarlynerd/tutorial2

1import gradio as gr2from fastcore.all import *3from fastai.vision.all import *4from fastai.vision.widgets import *5 6 7def is_cat(x): return x[0].isupper()8learn = load_learner('model.pkl')9categories = ('Dog', 'Cat')10 11def classify_image(img):12    pred,idx,probs = learn.predict(img)13    return dict(zip(categories, map(float,probs)))14 15image = gr.inputs.Image(shape=(192, 192))16label = gr.outputs.Label()17examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']18 19intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)20intf.launch(inline=False)21 22 23 24 25 26