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| 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))} | |
| title = "Corgi coat colour classifer" | |
| description = "An image classifier that classifies photos of adorable corgis by their coat colours. This will entice you to become owned by a corgi and I make no apologies." | |
| examples = ['timtam.jpg'] | |
| interpretation='default' | |
| enable_queue=True | |
| gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=5),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch() | |