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import gradio as gr
from fastai.vision.all import *
path = Path()
learn_inf = load_learner(path / 'export.pkl')
labels = ['beach', 'field', 'lake']
def predict(img):
img = PILImage.create(img)
pred, pred_idx, probs = learn_inf.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
gr_interface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=len(labels)), interpretation="default")
gr_interface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),
outputs=gr.outputs.Label(num_top_classes=len(labels)),
interpretation="default")
gr_interface.launch()
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