Pywayne Visualization Pangolin Utils

Pywayne Visualization Pangolin Utils

pywayne.visualization.pangolin_utils.PangolinViewer provides a Python interface to Pangolin 3D visualization library.

Quick Start

from pywayne.visualization.pangolin_utils import PangolinViewer, Colors
import numpy as np

# Create viewer
viewer = PangolinViewer(800, 600)
viewer.init()

# Run visualization loop
while viewer.should_not_quit():
    # ... add/update visual elements ...
    viewer.show(delay_time_in_s=0.03)

viewer.join()  # Wait for window to close

Colors

Use Colors class for common colors:

Colors.RED      # [1.0, 0.0, 0.0]
Colors.GREEN    # [0.0, 1.0, 0.0]
Colors.BLUE     # [0.0, 0.0, 1.0]
Colors.YELLOW   # [1.0, 1.0, 0.0]
Colors.CYAN     # [0.0, 1.0, 1.0]
Colors.MAGENTA  # [1.0, 0.0, 1.0]
Colors.WHITE    # [1.0, 1.0, 1.0]
Colors.BLACK    # [0.0, 0.0, 0.0]
Colors.ORANGE   # [1.0, 0.5, 0.0]
Colors.PURPLE   # [0.5, 0.5, 0.5]
Colors.GRAY     # [0.5, 0.5, 0.5]
Colors.BROWN    # [0.6, 0.3, 0.1]
Colors.PINK     # [1.0, 0.75, 0.8]

Core Control

viewer.run()          # Start main loop (blocking)
viewer.close()         # Close viewer
viewer.join()         # Wait for process to end
viewer.reset()         # Reset viewer state
viewer.init()          # Initialize view (set initial camera)
viewer.show(0.03)      # Render frame with delay (s)
viewer.should_not_quit()  # Check if viewer should continue
viewer.clear_all_visual_elements()  # Clear all elements

Point Cloud

# Clear all points
viewer.clear_all_points()

# Add single-color points (default: red)
viewer.add_points(points, point_size=4.0)

# Add points with custom colors
viewer.add_points_with_colors(points, colors, point_size=4.0)

# Add points with named color
viewer.add_points_with_color_name(points, color_name="red", point_size=4.0)

# Data format: points (N, 3), colors (N, 3)

Trajectory

# Clear all trajectories
viewer.clear_all_trajectories()

# Add trajectory with quaternions (positions + orientations)
viewer.add_trajectory_quat(
    positions,           # (N, 3)
    orientations,        # (N, 4) or (N, 7) depending on quat_format
    color=Colors.GREEN,
    quat_format="wxyz",   # "wxyz" or "xyzw"
    line_width=2.0,
    show_cameras=True,    # Show camera models along trajectory
    camera_size=0.05
)

# Add trajectory with SE3 poses
viewer.add_trajectory_se3(
    poses_se3,           # (N, 4) or (N, 7)
    color=Colors.GREEN,
    line_width=2.0,
    show_cameras=False
)

Camera

# Clear all cameras
viewer.clear_all_cameras()

# Set main camera (view follows this camera)
viewer.set_main_camera(camera_id)

# Add camera with quaternion
cam_id = viewer.add_camera_quat(
    position,           # (3,)
    orientation,         # (4,) or (7) depending on quat_format
    color=Colors.YELLOW,
    quat_format="wxyz",
    scale=0.1,
    line_width=1.0
)

# Add camera with SE3 pose
cam_id = viewer.add_camera_se3(
    pose_se3,            # (4,) or (7)
    color=Colors.YELLOW,
    scale=0.1,
    line_width=1.0
)

Plane

# Clear all planes
viewer.clear_all_planes()

# Add plane by vertices
viewer.add_plane(
    vertices,        # (>=3, 3)
    color=Colors.GRAY,
    alpha=0.5,       # Transparency 0-1
    label="plane"
)

# Add plane by normal + center
viewer.add_plane_normal_center(
    normal,          # (3,) - direction of plane normal
    center,          # (3,) - center point
    size,            # half-size (distance from center to edge)
    color=Colors.GRAY,
    alpha=0.5,
    label="plane"
)

# Add plane from SE3 transformation
viewer.add_plane_from_Twp(
    Twp,             # (4, 4) - world pose matrix
    size=1.0,
    color=Colors.GREEN,
    alpha=0.5,
    label="plane"
)

Chessboard

Useful for camera calibration and spatial reference:

# Add chessboard on XY plane
viewer.add_chessboard(rows=8, cols=8, cell_size=0.1)

# Add chessboard on custom plane with normal
viewer.add_chessboard(
    rows=9, cols=6, cell_size=0.025,
    origin=np.array([0, 0, 0]),
    normal=np.array([1, 0, 0]),  # YZ plane
    color1=Colors.RED,
    color2=Colors.YELLOW,
    alpha=0.8
)

# Add chessboard from SE3 transformation
viewer.add_chessboard_from_Twp(
    rows=9, cols=6, cell_size=0.025,
    Twp=pose_matrix,
    color1=Colors.BLACK,
    color2=Colors.WHITE,
    alpha=0.8,
    label="calib"
)

Line

viewer.clear_all_lines()

viewer.add_line(
    start_point,      # (3,)
    end_point,        # (3,)
    color=Colors.WHITE,
    line_width=1.0
)

Image Display

# Set image resolution
viewer.set_img_resolution(width, height)

# Add left image
viewer.add_image_1(img_array)           # Use numpy array
viewer.add_image_1(image_path="path.jpg")  # Use file path

# Add right image
viewer.add_image_2(img_array)
viewer.add_image_2(image_path="path.jpg")

Step Mode (Debugging)

viewer.is_step_mode_active()   # Check if step mode is active
viewer.wait_for_step()         # Wait for step trigger

Important Notes

• Dependencies: Requires Pangolin library (auto-downloaded via gettool)
• Data types: All position/point inputs must be float32
• Quaternion formats: Support wxyz and xyzw formats
• SE3 poses: Support (4, 4) or (4, 7) matrix formats
• Automatic cleaning: clear_all_visual_elements() clears points, trajectories, cameras, planes, lines
• Camera following: Use set_main_camera() with camera ID from add_camera_*() return