Playback the.bag file to extract the sequence of depth frames. Why do the frames look the same?

• Alexandra Ciuriuc

  • October 29, 2019 09:38

  Hello 1106569356,

   

  Thank you for your interest in the Intel RealSense products. 

  Can you please run the code below and see if you still get the wrong results? 

  Also, we need more details on how you determine that the frames are all the same.

  #####################################################
  ##               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 resolution, 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()
  # 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 filem to be used by the pipeline through playback.
      rs.config.enable_device_from_file(config, args.input)
      # Configure the pipeline to stream the depth stream
      config.enable_stream(rs.stream.depth, 1280, 720, rs.format.z16, 30)
  
      # Start streaming from file
      profile = pipeline.start(config)
  
      # Create opencv window to render image in
      cv2.namedWindow("Depth Stream", cv2.WINDOW_AUTOSIZE)
   
      # Create colorizer object
      colorizer = rs.colorizer();
  
      # Streaming loop
     # while True:
      playback = profile.get_device().as_playback()
      playback.set_real_time(False)
      start_num = 100
      end_num = 150
      n = 0
      while (playback.current_status() == rs.playback_status.playing) and (n<(end_num+1)):
          n += 1
          # Get frameset of depth
          frames = pipeline.wait_for_frames()
          if (n > start_num-1) and (n < (end_num+1)):
              print(n)
              # 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
  
  finally:
      pass

   

  Regards,

  Alexandra

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• 1106569356

  • October 30, 2019 01:54

  Hi Alexandra,

  I will try your suggestions, which will be very helpful to me. Thank you very much for your reply.

  Best Regards,

  Nevyn

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