How to use the open3d.camera function in open3d

def process_single_fragment(fragment_id, color_files, depth_files, n_files,
                            n_fragments, config):
    if config["path_intrinsic"]:
        intrinsic = o3d.io.read_pinhole_camera_intrinsic(
            config["path_intrinsic"])
    else:
        intrinsic = o3d.camera.PinholeCameraIntrinsic(
            o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault)
    sid = fragment_id * config['n_frames_per_fragment']
    eid = min(sid + config['n_frames_per_fragment'], n_files)

    make_posegraph_for_fragment(config["path_dataset"], sid, eid, color_files,
                                depth_files, fragment_id, n_fragments,
                                intrinsic, with_opencv, config)
    optimize_posegraph_for_fragment(config["path_dataset"], fragment_id, config)
    make_pointcloud_for_fragment(config["path_dataset"], color_files,
                                 depth_files, fragment_id, n_fragments,
                                 intrinsic, config)

args = parser.parse_args()

    with open(args.config) as json_file:
        config = json.load(json_file)
        initialize_config(config)

        with_opencv = initialize_opencv()
        if with_opencv:
            from opencv_pose_estimation import pose_estimation

        [color_files, depth_files] = get_rgbd_file_lists(config["path_dataset"])
        if args.path_intrinsic:
            intrinsic = o3d.io.read_pinhole_camera_intrinsic(
                args.path_intrinsic)
        else:
            intrinsic = o3d.camera.PinholeCameraIntrinsic(
                o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault)
        test_single_pair(args.source_id, args.target_id, color_files,
                         depth_files, intrinsic, with_opencv, config)

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)


    geometrie_added = False
    vis = o3d.visualization.Visualizer()
    #vis.create_window("Pointcloud",640,480)
    vis.create_window("Pointcloud")
    pointcloud = o3d.geometry.PointCloud()
    i = 0
    plane_flag = 0

voxel_length=4.0 / 512.0,
        sdf_trunc=0.04,
        color_type=o3d.integration.TSDFVolumeColorType.RGB8)

    for i in range(len(camera_poses)):
        print("Integrate {:d}-th image into the volume.".format(i))
        color = o3d.io.read_image(
            "../../TestData/RGBD/color/{:05d}.jpg".format(i))
        depth = o3d.io.read_image(
            "../../TestData/RGBD/depth/{:05d}.png".format(i))
        rgbd = o3d.geometry.RGBDImage.create_from_color_and_depth(
            color, depth, depth_trunc=4.0, convert_rgb_to_intensity=False)
        volume.integrate(
            rgbd,
            o3d.camera.PinholeCameraIntrinsic(
                o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault),
            np.linalg.inv(camera_poses[i].pose))

    print("Extract a triangle mesh from the volume and visualize it.")
    mesh = volume.extract_triangle_mesh()
    mesh.compute_vertex_normals()
    o3d.visualization.draw_geometries([mesh])

rgbd_images = []
    depth_image_path = get_file_list(os.path.join(path, "depth/"),
                                     extension=".png")
    color_image_path = get_file_list(os.path.join(path, "image/"),
                                     extension=".jpg")
    assert (len(depth_image_path) == len(color_image_path))
    for i in range(len(depth_image_path)):
        depth = o3d.io.read_image(os.path.join(depth_image_path[i]))
        color = o3d.io.read_image(os.path.join(color_image_path[i]))
        rgbd_image = o3d.geometry.RGBDImage.create_from_color_and_depth(
            color, depth, convert_rgb_to_intensity=False)
        if debug_mode:
            pcd = o3d.geometry.PointCloud.create_from_rgbd_image(
                rgbd_image,
                o3d.camera.PinholeCameraIntrinsic(
                    o3d.camera.PinholeCameraIntrinsicParameters.
                    PrimeSenseDefault))
            o3d.visualization.draw_geometries([pcd])
        rgbd_images.append(rgbd_image)

    # Read camera pose and mesh
    camera = o3d.io.read_pinhole_camera_trajectory(
        os.path.join(path, "scene/key.log"))
    mesh = o3d.io.read_triangle_mesh(
        os.path.join(path, "scene", "integrated.ply"))

    # Before full optimization, let's just visualize texture map
    # with given geometry, RGBD images, and camera poses.
    option = o3d.color_map.ColorMapOptimizationOption()
    option.maximum_iteration = 0
    o3d.color_map.color_map_optimization(mesh, rgbd_images, camera, option)
    o3d.visualization.draw_geometries([mesh])

# Open3D: www.open3d.org
# The MIT License (MIT)
# See license file or visit www.open3d.org for details

import open3d as o3d
from trajectory_io import read_trajectory
import numpy as np

if __name__ == "__main__":
    camera_poses = read_trajectory("../../TestData/RGBD/odometry.log")
    camera_intrinsics = o3d.camera.PinholeCameraIntrinsic(
        o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault)
    volume = o3d.integration.UniformTSDFVolume(
        length=4.0,
        resolution=512,
        sdf_trunc=0.04,
        color_type=o3d.integration.TSDFVolumeColorType.RGB8,
    )

    for i in range(len(camera_poses)):
        print("Integrate {:d}-th image into the volume.".format(i))
        color = o3d.io.read_image(
            "../../TestData/RGBD/color/{:05d}.jpg".format(i))
        depth = o3d.io.read_image(
            "../../TestData/RGBD/depth/{:05d}.png".format(i))
        rgbd = o3d.geometry.RGBDImage.create_from_color_and_depth(
            color, depth, depth_trunc=4.0, convert_rgb_to_intensity=False)

"../../TestData/RGBD/other_formats/SUN_color.jpg")
    depth_raw = o3d.io.read_image(
        "../../TestData/RGBD/other_formats/SUN_depth.png")
    rgbd_image = o3d.geometry.RGBDImage.create_from_sun_format(
        color_raw, depth_raw)
    print(rgbd_image)
    plt.subplot(1, 2, 1)
    plt.title('SUN grayscale image')
    plt.imshow(rgbd_image.color)
    plt.subplot(1, 2, 2)
    plt.title('SUN depth image')
    plt.imshow(rgbd_image.depth)
    plt.show()
    pcd = o3d.geometry.PointCloud.create_from_rgbd_image(
        rgbd_image,
        o3d.camera.PinholeCameraIntrinsic(
            o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault))
    # Flip it, otherwise the pointcloud will be upside down
    pcd.transform([[1, 0, 0, 0], [0, -1, 0, 0], [0, 0, -1, 0], [0, 0, 0, 1]])
    o3d.visualization.draw_geometries([pcd])

def process_single_fragment(fragment_id, color_files, depth_files, n_files,
                            n_fragments, config):
    if config["path_intrinsic"]:
        intrinsic = o3d.io.read_pinhole_camera_intrinsic(
            config["path_intrinsic"])
    else:
        intrinsic = o3d.camera.PinholeCameraIntrinsic(
            o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault)
    sid = fragment_id * config['n_frames_per_fragment']
    eid = min(sid + config['n_frames_per_fragment'], n_files)

    make_posegraph_for_fragment(config["path_dataset"], sid, eid, color_files,
                                depth_files, fragment_id, n_fragments,
                                intrinsic, with_opencv, config)
    optimize_posegraph_for_fragment(config["path_dataset"], fragment_id, config)
    make_pointcloud_for_fragment(config["path_dataset"], color_files,
                                 depth_files, fragment_id, n_fragments,
                                 intrinsic, config)

volume = o3d.integration.ScalableTSDFVolume(
        voxel_length=4.0 / 512.0,
        sdf_trunc=0.04,
        color_type=o3d.integration.TSDFVolumeColorType.RGB8)

    for i in range(len(camera_poses)):
        print("Integrate {:d}-th image into the volume.".format(i))
        color = o3d.io.read_image(
            "../../TestData/RGBD/color/{:05d}.jpg".format(i))
        depth = o3d.io.read_image(
            "../../TestData/RGBD/depth/{:05d}.png".format(i))
        rgbd = o3d.geometry.RGBDImage.create_from_color_and_depth(
            color, depth, depth_trunc=4.0, convert_rgb_to_intensity=False)
        volume.integrate(
            rgbd,
            o3d.camera.PinholeCameraIntrinsic(
                o3d.camera.PinholeCameraIntrinsicParameters.PrimeSenseDefault),
            np.linalg.inv(camera_poses[i].pose))

    print("Extract a triangle mesh from the volume and visualize it.")
    mesh = volume.extract_triangle_mesh()
    mesh.compute_vertex_normals()
    o3d.visualization.draw_geometries([mesh])