如何使用Keras获取top K预测

from keras.models import Sequential
from keras.layers import Dense
from keras.preprocessing import image
from keras.applications.imagenet_utils import decode_predictions

model = Sequential()
# 加载预训练的模型，例如VGG16
model.add(VGG16(weights='imagenet'))

img_path = 'path_to_image.jpg'
img = image.load_img(img_path, target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)

preds = model.predict(x)

# 解码预测结果，获取top K的预测
top_k = 5
decoded_preds = decode_predictions(preds, top=top_k)[0]