CompleteAGI/CatOrDog

1import gradio as gr2from fastai.vision.all import *3 4 5def is_cat(x): return x[0].isupper()6 7 8learn = load_learner('model.pkl')9 10categories = ('Dog', 'Cat')11 12 13def classify_image(img):14    pred, ids, probs = learn.predict(img)15    return dict(zip(categories, map(float, probs)))16 17title = "Cat Or Dog?"18description = "A cat or dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."19 20image = gr.inputs.Image(shape=(192, 192))21label = gr.outputs.Label()22examples = ['dog1.jpg', 'cat1.jpg', 'dunno1.jpg']23 24iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title=title, description=description)25iface.launch(inline=False)