from fastai.vision.all import * import gradio as gr learn = load_learner('petClassifierModel.pkl') categories = learn.dls.vocab 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() examples = ['basset_hound2.jpg','Boxer.jpg','cocker_spaniel.jpg','Keeshond.jpg','Siamese.jpg', 'russian-blue-cat.jpg'] iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) iface.launch()