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from fastai.vision.all import * | |
import gradio as gr | |
learn = load_learner('model.pth') | |
def classify_image(img): | |
celebrity_name,_,probs = learn.predict(img) | |
results = dict(zip(list(learn.dls.vocab),probs)) | |
best_results = sorted(results, key=results.get, reverse=True)[:5] | |
probabilities = {key: float(results[key]) for key in best_results} | |
return probabilities | |
image = gr.inputs.Image(shape=(224,224)) | |
label = gr.outputs.Label() | |
examples = ['emma_watson.jpg', "tom_hanks.jpeg"] | |
iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
iface.launch(inline=False) |