Tensorflow对象检测中的裁剪框并将其显示为jpg图像

import tensorflow as tf
from object_detection.utils import visualization_utils as vis_util
from PIL import Image
import numpy as np

# 加载预训练模型
model = tf.saved_model.load('path_to_saved_model')

# 加载标签映射
category_index = {1: {'id': 1, 'name': 'person'}, 2: {'id': 2, 'name': 'car'}}  # 示例标签映射

# 读取图像
image_np = np.array(Image.open('path_to_image.jpg'))

# 运行模型进行检测
input_tensor = tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.float32)
detections = model(input_tensor)

# 可视化检测结果
vis_util.visualize_boxes_and_labels_on_image_array(
    image_np,
    detections['detection_boxes'][0].numpy(),
    detections['detection_classes'][0].numpy().astype(np.int64),
    detections['detection_scores'][0].numpy(),
    category_index,
    use_normalized_coordinates=True,
    line_thickness=8)

# 保存图像为JPEG
output_image = Image.fromarray(np.uint8(image_np)).save('output_image.jpg')