GnnForPrivacyScan/data/purposeSplit/visualize/stray_visualize_1.py

def read_args():
    parser = ArgumentParser(description=description, usage=usage)
    parser.add_argument('path', type=str, help="Path to StrayScanner dataset to process.")
    parser.add_argument('--trajectory', '-t', action='store_true', help="Visualize the trajectory of the camera as a line.")
    parser.add_argument('--frames', '-f', action='store_true', help="Visualize camera coordinate frames from the odometry file.")
    parser.add_argument('--point-clouds', '-p', action='store_true', help="Show concatenated point clouds.")
    parser.add_argument('--integrate', '-i', action='store_true', help="Integrate point clouds using the Open3D RGB-D integration pipeline, and visualize it.")
    parser.add_argument('--mesh-filename', type=str, help='Mesh generated from point cloud integration will be stored in this file. open3d.io.write_triangle_mesh will be used.', default=None)
    parser.add_argument('--every', type=int, default=60, help="Show only every nth point cloud and coordinate frames. Only used for point cloud and odometry visualization.")
    parser.add_argument('--voxel-size', type=float, default=0.015, help="Voxel size in meters to use in RGB-D integration.")
    parser.add_argument('--confidence', '-c', type=int, default=1,
            help="Keep only depth estimates with confidence equal or higher to the given value. There are three different levels: 0, 1 and 2. Higher is more confident.")
    return parser.parse_args()