是否可以将TensorFlow对象检测接口的输出图像保存到文件夹中？

import tensorflow as tf
import matplotlib.pyplot as plt
import matplotlib.patches as patches

# 加载并配置模型
model = tf.saved_model.load('path/to/model')  # 替换为实际的模型路径

# 输入图像
image = tf.io.read_file('path/to/image.jpg')  # 替换为实际的图像路径
image = tf.image.decode_image(image)
image = tf.expand_dims(image, axis=0)

# 执行对象检测
output = model(image)

# 解析检测结果
detections = output['detection_boxes'][0].numpy()
classes = output['detection_classes'][0].numpy()
scores = output['detection_scores'][0].numpy()

# 可视化检测结果
fig, ax = plt.subplots(1)
ax.imshow(image[0])

for i in range(len(detections)):
    if scores[i] > 0.5:  # 设置一个阈值过滤低置信度的检测结果
        box = detections[i]
        class_name = classes[i]
        x_min, y_min, x_max, y_max = box
        w = x_max - x_min
        h = y_max - y_min

        # 绘制检测框
        rect = patches.Rectangle((x_min, y_min), w, h, linewidth=1, edgecolor='r', facecolor='none')
        ax.add_patch(rect)
        ax.text(x_min, y_min, f'{class_name}', fontsize=8, color='r')

# 保存输出图像
plt.savefig('path/to/output.jpg')  # 替换为实际的输出路径