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import gradio as gr
from fastai.vision.all import *
import skimage
learn = load_learner('model_basketball.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 = "Basketball player classifier"
description = "Basketball player classifier created with Gradio and HuggingFace Spaces."
interpretation='default'
enable_queue=True
gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,interpretation=interpretation,enable_queue=enable_queue).launch() |