How to use the pyrealsense2.config function in pyrealsense2

# 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()

        align = rs.align(rs.stream.color)
        pipeline = rs.pipeline()
        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, 640, 480, rs.format.z16, 30)
        config.enable_stream(rs.stream.color, 640, 480, rs.format.rgb8, 30)

        # Start streaming from file
        profile = pipeline.start(config)

        intr = profile.get_stream(rs.stream.color).as_video_stream_profile().get_intrinsics()
        # print( 'camera_intrinsic', intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)

        # Create opencv window to render image in
        cv2.namedWindow("Depth Stream", cv2.WINDOW_AUTOSIZE)
        cv2.namedWindow("Color Stream", cv2.WINDOW_AUTOSIZE)
        pinhole_camera_intrinsic = PinholeCameraIntrinsic(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)

if not args.input:
        print("No input paramater have been given.")
        print("For help type --help")
        exit()

    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()

    align = rs.align(rs.stream.color)
    pipeline = rs.pipeline()
    config = rs.config()

    rs.config.enable_device_from_file(config, args.input)

    config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
    config.enable_stream(rs.stream.color, 640, 480, rs.format.rgb8, 30)


    profile = pipeline.start(config)

    intr = profile.get_stream(rs.stream.color).as_video_stream_profile().get_intrinsics()

    cv2.namedWindow("Depth Stream", cv2.WINDOW_AUTOSIZE)
    cv2.namedWindow("Color Stream", cv2.WINDOW_AUTOSIZE)
    pinhole_camera_intrinsic = o3d.camera.PinholeCameraIntrinsic(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)

    geometrie_added = False
    vis = o3d.visualization.VisualizerWithKeyCallback()

# 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
    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:

import pyrealsense2 as rs
import numpy as np
import cv2
import time
from open3d import *
import os

if __name__=="__main__":
    align = rs.align(rs.stream.color)

    config = rs.config()
    config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
    config.enable_stream(rs.stream.color, 640, 480, rs.format.rgb8, 30)

    config.enable_record_to_file('object_detection2.bag') 

    pipeline = rs.pipeline()
    profile = pipeline.start(config)

    # get camera intrinsics
    intr = profile.get_stream(rs.stream.color).as_video_stream_profile().get_intrinsics()
    print(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    pinhole_camera_intrinsic = PinholeCameraIntrinsic(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    # print(type(pinhole_camera_intrinsic))
    
    cv2.namedWindow('Color Stream', cv2.WINDOW_AUTOSIZE)
    cv2.namedWindow('Depth Stream', cv2.WINDOW_AUTOSIZE)

obj_list = ['box','polar bear','duck','turtle','whale','dog','elephant','horse']
    obj_list = ['盒子','北极熊','小黄鸭','小海龟','独角鲸','灰狗','大象','马']
    color_list = [[96/255,96/255,96/255],[1,97/255,0],[227/255,207/255,87/255],[176/255,224/255,230/255],
                [106/255,90/255,205/255],[56/255,94/255,15/255],[61/255,89/255,171/255],[51/255,161/255,201/255],
                [178/255,34/255,34/255],[138/255,43/255,226/255]]
    


    s = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
    s.connect(('titanxp.sure-to.win',8899))
    print(s.recv(1024).decode('utf-8'))

    align = rs.align(rs.stream.color)
    #align = rs.align(rs.stream.depth)

    config = rs.config()
    config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 15)
    config.enable_stream(rs.stream.color, 640, 480, rs.format.rgb8, 15)
    pipeline = rs.pipeline()
    profile = pipeline.start(config)

    # get camera intrinsics
    intr = profile.get_stream(rs.stream.color).as_video_stream_profile().get_intrinsics()
    # print(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    pinhole_camera_intrinsic = o3d.camera.PinholeCameraIntrinsic(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    # print(type(pinhole_camera_intrinsic))
    
    cv2.namedWindow('Color Stream', cv2.WINDOW_AUTOSIZE)
    cv2.namedWindow('Depth Stream', cv2.WINDOW_AUTOSIZE)

    cam = rgbdTools.Camera(616.8676147460938,617.0631103515625,319.57012939453125,233.06488037109375)

##              Align Depth to Color               ##
#####################################################

# First import the library
import pyrealsense2 as rs
# Import Numpy for easy array manipulation
import numpy as np
# Import OpenCV for easy image rendering
import cv2

# Create a pipeline
pipeline = rs.pipeline()

#Create a config and configure the pipeline to stream
#  different resolutions of color and depth streams
config = rs.config()
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)

# Start streaming
profile = pipeline.start(config)

# Getting the depth sensor's depth scale (see rs-align example for explanation)
depth_sensor = profile.get_device().first_depth_sensor()
depth_scale = depth_sensor.get_depth_scale()
print("Depth Scale is: " , depth_scale)

# We will be removing the background of objects more than
#  clipping_distance_in_meters meters away
clipping_distance_in_meters = 1 #1 meter
clipping_distance = clipping_distance_in_meters / depth_scale

from lib import rgbdTools,keyPoints,registration,template
import cv2
import numpy as np 
from scipy import optimize
import open3d as o3d 
import copy
import sys
import os 
import time


if __name__=="__main__":
    align = rs.align(rs.stream.color)
    #align = rs.align(rs.stream.depth)

    config = rs.config()
    config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 6)
    config.enable_stream(rs.stream.color, 640, 480, rs.format.rgb8, 6)
    pipeline = rs.pipeline()
    profile = pipeline.start(config)

    # get camera intrinsics
    intr = profile.get_stream(rs.stream.color).as_video_stream_profile().get_intrinsics()
    # print(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    pinhole_camera_intrinsic = o3d.camera.PinholeCameraIntrinsic(intr.width, intr.height, intr.fx, intr.fy, intr.ppx, intr.ppy)
    RealSense = rgbdTools.Camera(fx = intr.fx, fy = intr.fy, cx =  intr.ppx, cy = intr.ppy)
    TablePlane = keyPoints.Plane()
    # print(type(pinhole_camera_intrinsic))
    
    cv2.namedWindow('Color Stream', cv2.WINDOW_AUTOSIZE)
    # cv2.namedWindow('Depth Stream', cv2.WINDOW_AUTOSIZE)

def run_demo():
	
	# Define some constants 
	resolution_width = 1280 # pixels
	resolution_height = 720 # pixels
	frame_rate = 15  # fps
	dispose_frames_for_stablisation = 30  # frames
	
	chessboard_width = 6 # squares
	chessboard_height = 9 	# squares
	square_size = 0.0253 # meters

	try:
		# Enable the streams from all the intel realsense devices
		rs_config = rs.config()
		rs_config.enable_stream(rs.stream.depth, resolution_width, resolution_height, rs.format.z16, frame_rate)
		rs_config.enable_stream(rs.stream.infrared, 1, resolution_width, resolution_height, rs.format.y8, frame_rate)
		rs_config.enable_stream(rs.stream.color, resolution_width, resolution_height, rs.format.bgr8, frame_rate)

		# Use the device manager class to enable the devices and get the frames
		device_manager = DeviceManager(rs.context(), rs_config)
		device_manager.enable_all_devices()
		
		# Allow some frames for the auto-exposure controller to stablise
		for frame in range(dispose_frames_for_stablisation):
			frames = device_manager.poll_frames()

		assert( len(device_manager._available_devices) > 0 )
		"""
		1: Calibration
		Calibrate all the available devices to the world co-ordinates.

#############################################

scoresDecisionTree= cross_val_score(decisionTreeCLF, xTrainR, lTrainR, cv=5)

print(scoresDecisionTree)

print("Accuracy Decision Tree: %0.2f (+/- %0.2f)" % (scoresDecisionTree.mean(), scoresDecisionTree.std() * 2))
############################################


# Create a pipeline
pipeline = rs.pipeline()

# Create a config and configure the pipeline to stream
#  different resolutions of color and depth streams
config = rs.config()

config.enable_stream(rs.stream.depth, 640, 360, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)

# Start streaming
profile = pipeline.start(config)

# Getting the depth sensor's depth scale (see rs-align example for explanation)
depth_sensor = profile.get_device().first_depth_sensor()
depth_scale = depth_sensor.get_depth_scale()
print("Depth Scale is: ", depth_scale)

# We will be removing the background of objects more than
#  clipping_distance_in_meters meters away
clipping_distance_in_meters = 10  # 1 meter
clipping_distance = clipping_distance_in_meters / depth_scale

    @property
    def rotation(self):
        Rx, _ = cv2.Rodrigues((self.pitch, 0, 0))
        Ry, _ = cv2.Rodrigues((0, self.yaw, 0))
        return np.dot(Ry, Rx).astype(np.float32)

    @property
    def pivot(self):
        return self.translation + np.array((0, 0, self.distance), dtype=np.float32)


state = AppState()

# Configure depth and color streams
pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)

# Start streaming
pipeline.start(config)

# Get stream profile and camera intrinsics
profile = pipeline.get_active_profile()
depth_profile = rs.video_stream_profile(profile.get_stream(rs.stream.depth))
depth_intrinsics = depth_profile.get_intrinsics()
w, h = depth_intrinsics.width, depth_intrinsics.height

# Processing blocks
pc = rs.pointcloud()
decimate = rs.decimation_filter()
decimate.set_option(rs.option.filter_magnitude, 2 ** state.decimate)