如何在使用CIFAR-10训练的模型中测试我的新图像？(使用tensorflow)

import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt

model = tf.keras.models.load_model('cifar10_model.h5')

# 加载并预处理测试图像
image = plt.imread('test_image.jpg')
image = tf.image.resize(image, (32, 32))  # 调整图像大小为32x32
image = np.expand_dims(image, axis=0)  # 增加一个维度，适配模型输入

# 进行图像分类预测
predictions = model.predict(image)
class_index = np.argmax(predictions[0])

# 获取预测结果标签
class_labels = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
predicted_label = class_labels[class_index]

print('预测结果：', predicted_label)