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| from fastai.vision.all import PILImage, load_learner | |
| from gradio import Interface | |
| from gradio.components import Image, Label | |
| TITLE = "Chicken Breed Classifier" | |
| DESCRIPTION = """A chicken breed classifier trained using the dataset here: https://www.kaggle.com/datasets/edkenthazledine/chicken-breeds | |
| There are many breeds of chicken, and getting lots of pictures of them is hard! | |
| This can identify (to varying degrees of accuracy, the model is ~90% accurate): American Gamefowl, Australorp, Burford Brown, Crevecoeur, Derbyshire Redcap, Easter Egger, Light Sussex, Sapphire Gem, Speckled Sussex, Wyandotte | |
| """ | |
| EXAMPLES = ["wyandotte.jpg"] | |
| learn = load_learner("export_10b_90p.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 = Interface( | |
| fn=predict, | |
| inputs=Image(shape=(512, 512)), | |
| outputs=Label(num_top_classes=3), | |
| title=TITLE, | |
| description=DESCRIPTION, | |
| examples=EXAMPLES, | |
| ) | |
| iface.launch(enable_queue=True) | |