import gradio as gr from fastai.vision.all import * learn_inf = load_learner('model.pkl') categories = learn_inf.dls.vocab def classify_image(img): pred,pred_idx,probs = learn_inf.predict(img) return dict(zip(categories, map(float, probs))) iface = gr.Interface( title = "Is it Huggable?", description = "An image classifier that tells if something's huggable or not?", fn=classify_image, inputs=gr.inputs.Image(shape=(224,224)), outputs=gr.outputs.Label(), examples=['examples/dog.jpg', 'examples/cactus.jpg', 'examples/plushie.jpg', 'examples/snowman.jpg', 'examples/chainsaw.jpg', 'examples/shark.jpg','examples/bunny.jpg', 'examples/knife.jpg', 'examples/tiger.jpg', 'examples/trex.jpg'], live=True, enable_queue=True ) iface.launch()