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| import gradio as gr | |
| from fastai.vision.all import * | |
| import skimage | |
| 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 = "Bike or Car?" | |
| description = "Simple demo to determine if an image contains a bike or a car." | |
| examples = ['car.jpg', 'bike.jpg'] | |
| interpretation='default' | |
| gr.Interface(fn=predict, | |
| inputs=gr.inputs.Image(shape=(512, 512)), | |
| outputs=gr.outputs.Label(num_top_classes=2), | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| interpretation=interpretation).launch() | |