import gradio as gr from fastai.vision.all import * import skimage learn = load_learner("model.pkl") labels = learn.dls.vocab def predict(img): img = PILImage.create(img) pred, pred_idx, probs = learn.predict(img) return {labels[i]: float(probs[i]) for i in range(len(labels))} title = "Hotdog or Not?" description = "upload a picture of a hotdog or hamburger and be amazed!" article = "

Blog post

" examples = ["siamese.jpg"] interpretation = "default" enable_queue = True gr.Interface( fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3), title=title, description=description, article=article, examples=examples, interpretation=interpretation, enable_queue=enable_queue, ).launch()