| import gradio as gr | |
| from fastai.vision.all import * | |
| learn = load_learner('export.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))} | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.components.Image(shape=(512, 512)), | |
| outputs=gr.components.Label(num_top_classes=3), | |
| description="Pet Classifier", | |
| article="<p style='text-align: center'><a href='google.com' target='_blank'>Blog post</a></p>", | |
| live=True, | |
| enable_queue=True, | |
| ) | |
| iface.launch() | |