| 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) | |
| _, _, probs = learn.predict(img) | |
| return {labels[i]: float(probs[i]) for i in range(len(labels))} | |
| gr.Interface( | |
| fn=predict, | |
| inputs=gr.components.Image(shape=(400, 400)), | |
| outputs=gr.components.Label(num_top_classes=2), | |
| title="Does my sighthound have a corn?", | |
| description="Given a picture of a paw, does it have a corn?", | |
| examples=[ | |
| "corn_01.jpg", | |
| "corn_02.jpg", | |
| "corn_03.jpg", | |
| "no_corn_01.jpg", | |
| "no_corn_02.jpg", | |
| ], | |
| ).launch(enable_queue=True) | |