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from fastai.vision.all import * | |
import gradio as gr | |
def get_x(r): return path/r['fname'] | |
def get_y(r): return r['car_body_style'] | |
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 = 'Car Body Style Classifier' | |
description = 'A car body style classifier trained on the [Cars Dataset](http://ai.stanford.edu/~jkrause/cars/car_dataset.html).' | |
examples = ['convertible.jpg', 'coupe.jpg', 'van.jpg'] | |
gr.Interface(fn=predict, | |
inputs=gr.inputs.Image(shape=(512, 512)), | |
outputs=gr.outputs.Label(num_top_classes=3), | |
title=title, | |
description=description, | |
examples=examples, | |
enable_queue=True).launch(share=True) |