from fastai.vision.all import * import gradio as gr learn = load_learner('FastCloudsModel.pkl') # Cell categories = learn.dls.vocab def classify_image(img): pred,idx,probs = learn.predict(img) return dict(zip(categories, map(float,probs))) # Cell image = gr.inputs.Image(shape=(192, 192)) label = gr.outputs.Label() examples = ['cirrus.jpg', 'cumulus.jpeg'] # Cell intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) intf.launch()