我有 3 類課程Tree, Stump, Ground。我為這些類別列出了一個清單：CATEGORIES = ["Tree", "Stump", "Ground"]當我打印我的預測時，它給了我輸出[[0. 1. 0.]]我已經閱讀了 numpy 的 Argmax，但我不完全確定在這種情況下如何使用它。我試過使用print(np.argmax(prediction))但這給了我1. 太好了，但我想找出索引是什么1，然后打印出類別而不是最高值。import cv2import tensorflow as tfimport numpy as npCATEGORIES = ["Tree", "Stump", "Ground"]def prepare(filepath):    IMG_SIZE = 150 # This value must be the same as the value in Part1    img_array = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)    new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))    return new_array.reshape(-1, IMG_SIZE, IMG_SIZE, 1)# Able to load a .model, .h3, .chibai and even .dogmodel = tf.keras.models.load_model("models/test.model")prediction = model.predict([prepare('image.jpg')])print("Predictions:")print(prediction)print(np.argmax(prediction))我希望我的預測告訴我：Predictions:[[0. 1. 0.]]Stump