realsense bag文件时间戳获取的方式有两种：

（1）使用ros读取bag文件，ROS支持python和c++，这里使用的是python语言

import rosbag

filename = r'D:\datasets\D415\static_20210914\20210913_165702.bag'


bag = rosbag.Bag(filename, 'r')

info = bag.get_type_and_topic_info()
print(info)



cnt_depth = info.topics.get('/device_0/sensor_0/Depth_0/image/data').message_count

print('深度图数量是：', cnt_depth)

cnt_color = info.topics.get('/device_0/sensor_1/Color_0/image/data').message_count

print('彩色图数量是：', cnt_color)

bag_data = bag.read_messages('/device_0/sensor_0/Depth_0/image/data')

t_tmp = 0
t = 0

for topic, msg, t in bag_data:
    print(msg.header.stamp.to_sec(), t.to_nsec() - t_tmp)
    t_tmp = t.to_nsec()

（2）使用pyrealsense2，也可以c++版本的librealsense

#####################################################
##               Read bag from file                ##
#####################################################


# First import library
import pyrealsense2 as rs
# Import Numpy for easy array manipulation
import numpy as np
# Import OpenCV for easy image rendering
import cv2
# Import argparse for command-line options
import argparse
# Import os.path for file path manipulation
import os.path

# Create object for parsing command-line options
parser = argparse.ArgumentParser(description="Read recorded bag file and display depth stream in jet colormap.\
                                Remember to change the stream fps and format to match the recorded.")
# Add argument which takes path to a bag file as an input
parser.add_argument("-i", "--input", type=str, help="Path to the bag file")
# Parse the command line arguments to an object
args = parser.parse_args()

args.input = r'D:\datasets\20210824\1\20210824_103849.bag'

# Safety if no parameter have been given
if not args.input:
    print("No input paramater have been given.")
    print("For help type --help")
    exit()
# Check if the given file have bag extension
if os.path.splitext(args.input)[1] != ".bag":
    print("The given file is not of correct file format.")
    print("Only .bag files are accepted")
    exit()
try:
    # Create pipeline
    pipeline = rs.pipeline()

    # Create a config object
    config = rs.config()

    # Tell config that we will use a recorded device from file to be used by the pipeline through playback.
    rs.config.enable_device_from_file(config, args.input, repeat_playback=False)

    # Configure the pipeline to stream the depth stream
    # Change this parameters according to the recorded bag file resolution
    config.enable_stream(rs.stream.depth, rs.format.z16, 30)

    # Start streaming from file
    pipeline.start(config)

    # whq
    device = pipeline.get_active_profile().get_device()
    playback = device.as_playback()
    playback.set_real_time(False)

    # Create opencv window to render image in
    cv2.namedWindow("Depth Stream", cv2.WINDOW_AUTOSIZE)
    
    # Create colorizer object
    colorizer = rs.colorizer()

    number = 0
    timestamp_tmp = 0

    # Streaming loop
    while True:
        # Get frameset of depth
        frames = pipeline.wait_for_frames()

        number = number + 1
        print(number, ' ', frames.timestamp, frames.timestamp - timestamp_tmp)
        timestamp_tmp = frames.timestamp
        # Get depth frame
        depth_frame = frames.get_depth_frame()

        # Colorize depth frame to jet colormap
        depth_color_frame = colorizer.colorize(depth_frame)

        # Convert depth_frame to numpy array to render image in opencv
        depth_color_image = np.asanyarray(depth_color_frame.get_data())

        # Render image in opencv window
        cv2.imshow("Depth Stream", depth_color_image)
        key = cv2.waitKey(1)


        # if pressed escape exit program
        # if key == 27:
        #     cv2.destroyAllWindows()
        #     break
except RuntimeError:
    print(number)
    print("There are no more frames left in the .bag file!")
    cv2.destroyAllWindows()

finally:
    pass

参考文献：

（1）ROSBAG：用python按时间戳提取bag中的图像