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# from fastbook import *
from fastai.vision.all import *
path = Path()
path.ls(file_exts='.pkl')
learn_inf = load_learner(path/'export.pkl')
labels = learn_inf.dls.vocab
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))}
p = predict('images/grizzly.jpg')
print(p)
import gradio as gr
gr.Interface(examples=['images/grizzly.jpg'],fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
# print(learn_inf.dls.vocab) |