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pangolin-utils穿山甲工具

Agent Skill

pangolin-utils 用于辅助部署、云资源、容器和基础设施运维,适合在 OpenClaw 中需要检查配置、整理部署步骤或排查环境问题时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pangolin-utils(穿山甲工具)
来源仓库:https://github.com/wangyendt/pangolin-utils
安装命令:
openclaw skills install pangolin-utils
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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openclaw skills install pangolin-utils

简介

pangolin-utils 提供 3D 可视化工具包,包含点云、轨迹与相机数据的实时查看器。

  • 适用于计算机视觉与机器人领域的数据调试与可视化分析。
  • 支持多种传感器数据格式导入与交互式渲染操作。
  • 需具备图形界面运行环境,注意 GPU 资源占用情况。
  • 安装前建议确认系统是否支持 OpenGL 或 Vulkan 渲染后端。

SKILL.md

name
pywayne-visualization-pangolin-utils
description
3D visualization toolkit wrapping Pangolin viewer for real-time display of point clouds, trajectories, cameras, planes, chessboards, and images. Use when visualizing sensor data (IMU, SLAM, tracking), robot states, or any 3D data with camera poses and trajectories. Supports dual-image display, step mode for debugging, and main camera following.

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

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