{
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  "item": {
    "slug": "pangolin-utils",
    "name": "Pywayne Visualization Pangolin Utils",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/wangyendt/pangolin-utils",
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    "quickSetup": [
      "Download the package from Yavira.",
      "Extract the archive and review SKILL.md first.",
      "Import or place the package into your OpenClaw setup."
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      "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
      "steps": [
        "Download the package from Yavira.",
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        "Paste one of the prompts below and point your agent at the extracted folder."
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          "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
        },
        {
          "label": "Upgrade existing",
          "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
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      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/pangolin-utils"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
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    "downloadPageUrl": "https://openagent3.xyz/downloads/pangolin-utils",
    "agentPageUrl": "https://openagent3.xyz/skills/pangolin-utils/agent",
    "manifestUrl": "https://openagent3.xyz/skills/pangolin-utils/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/pangolin-utils/agent.md"
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  "agentAssist": {
    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
      "Download the package from Yavira.",
      "Extract it into a folder your agent can access.",
      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
    "prompts": [
      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
      }
    ]
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Pywayne Visualization Pangolin Utils",
        "body": "pywayne.visualization.pangolin_utils.PangolinViewer provides a Python interface to Pangolin 3D visualization library."
      },
      {
        "title": "Quick Start",
        "body": "from pywayne.visualization.pangolin_utils import PangolinViewer, Colors\nimport numpy as np\n\n# Create viewer\nviewer = PangolinViewer(800, 600)\nviewer.init()\n\n# Run visualization loop\nwhile viewer.should_not_quit():\n    # ... add/update visual elements ...\n    viewer.show(delay_time_in_s=0.03)\n\nviewer.join()  # Wait for window to close"
      },
      {
        "title": "Colors",
        "body": "Use Colors class for common colors:\n\nColors.RED      # [1.0, 0.0, 0.0]\nColors.GREEN    # [0.0, 1.0, 0.0]\nColors.BLUE     # [0.0, 0.0, 1.0]\nColors.YELLOW   # [1.0, 1.0, 0.0]\nColors.CYAN     # [0.0, 1.0, 1.0]\nColors.MAGENTA  # [1.0, 0.0, 1.0]\nColors.WHITE    # [1.0, 1.0, 1.0]\nColors.BLACK    # [0.0, 0.0, 0.0]\nColors.ORANGE   # [1.0, 0.5, 0.0]\nColors.PURPLE   # [0.5, 0.5, 0.5]\nColors.GRAY     # [0.5, 0.5, 0.5]\nColors.BROWN    # [0.6, 0.3, 0.1]\nColors.PINK     # [1.0, 0.75, 0.8]"
      },
      {
        "title": "Core Control",
        "body": "viewer.run()          # Start main loop (blocking)\nviewer.close()         # Close viewer\nviewer.join()         # Wait for process to end\nviewer.reset()         # Reset viewer state\nviewer.init()          # Initialize view (set initial camera)\nviewer.show(0.03)      # Render frame with delay (s)\nviewer.should_not_quit()  # Check if viewer should continue\nviewer.clear_all_visual_elements()  # Clear all elements"
      },
      {
        "title": "Point Cloud",
        "body": "# Clear all points\nviewer.clear_all_points()\n\n# Add single-color points (default: red)\nviewer.add_points(points, point_size=4.0)\n\n# Add points with custom colors\nviewer.add_points_with_colors(points, colors, point_size=4.0)\n\n# Add points with named color\nviewer.add_points_with_color_name(points, color_name=\"red\", point_size=4.0)\n\n# Data format: points (N, 3), colors (N, 3)"
      },
      {
        "title": "Trajectory",
        "body": "# Clear all trajectories\nviewer.clear_all_trajectories()\n\n# Add trajectory with quaternions (positions + orientations)\nviewer.add_trajectory_quat(\n    positions,           # (N, 3)\n    orientations,        # (N, 4) or (N, 7) depending on quat_format\n    color=Colors.GREEN,\n    quat_format=\"wxyz\",   # \"wxyz\" or \"xyzw\"\n    line_width=2.0,\n    show_cameras=True,    # Show camera models along trajectory\n    camera_size=0.05\n)\n\n# Add trajectory with SE3 poses\nviewer.add_trajectory_se3(\n    poses_se3,           # (N, 4) or (N, 7)\n    color=Colors.GREEN,\n    line_width=2.0,\n    show_cameras=False\n)"
      },
      {
        "title": "Camera",
        "body": "# Clear all cameras\nviewer.clear_all_cameras()\n\n# Set main camera (view follows this camera)\nviewer.set_main_camera(camera_id)\n\n# Add camera with quaternion\ncam_id = viewer.add_camera_quat(\n    position,           # (3,)\n    orientation,         # (4,) or (7) depending on quat_format\n    color=Colors.YELLOW,\n    quat_format=\"wxyz\",\n    scale=0.1,\n    line_width=1.0\n)\n\n# Add camera with SE3 pose\ncam_id = viewer.add_camera_se3(\n    pose_se3,            # (4,) or (7)\n    color=Colors.YELLOW,\n    scale=0.1,\n    line_width=1.0\n)"
      },
      {
        "title": "Plane",
        "body": "# Clear all planes\nviewer.clear_all_planes()\n\n# Add plane by vertices\nviewer.add_plane(\n    vertices,        # (>=3, 3)\n    color=Colors.GRAY,\n    alpha=0.5,       # Transparency 0-1\n    label=\"plane\"\n)\n\n# Add plane by normal + center\nviewer.add_plane_normal_center(\n    normal,          # (3,) - direction of plane normal\n    center,          # (3,) - center point\n    size,            # half-size (distance from center to edge)\n    color=Colors.GRAY,\n    alpha=0.5,\n    label=\"plane\"\n)\n\n# Add plane from SE3 transformation\nviewer.add_plane_from_Twp(\n    Twp,             # (4, 4) - world pose matrix\n    size=1.0,\n    color=Colors.GREEN,\n    alpha=0.5,\n    label=\"plane\"\n)"
      },
      {
        "title": "Chessboard",
        "body": "Useful for camera calibration and spatial reference:\n\n# Add chessboard on XY plane\nviewer.add_chessboard(rows=8, cols=8, cell_size=0.1)\n\n# Add chessboard on custom plane with normal\nviewer.add_chessboard(\n    rows=9, cols=6, cell_size=0.025,\n    origin=np.array([0, 0, 0]),\n    normal=np.array([1, 0, 0]),  # YZ plane\n    color1=Colors.RED,\n    color2=Colors.YELLOW,\n    alpha=0.8\n)\n\n# Add chessboard from SE3 transformation\nviewer.add_chessboard_from_Twp(\n    rows=9, cols=6, cell_size=0.025,\n    Twp=pose_matrix,\n    color1=Colors.BLACK,\n    color2=Colors.WHITE,\n    alpha=0.8,\n    label=\"calib\"\n)"
      },
      {
        "title": "Line",
        "body": "viewer.clear_all_lines()\n\nviewer.add_line(\n    start_point,      # (3,)\n    end_point,        # (3,)\n    color=Colors.WHITE,\n    line_width=1.0\n)"
      },
      {
        "title": "Image Display",
        "body": "# Set image resolution\nviewer.set_img_resolution(width, height)\n\n# Add left image\nviewer.add_image_1(img_array)           # Use numpy array\nviewer.add_image_1(image_path=\"path.jpg\")  # Use file path\n\n# Add right image\nviewer.add_image_2(img_array)\nviewer.add_image_2(image_path=\"path.jpg\")"
      },
      {
        "title": "Step Mode (Debugging)",
        "body": "viewer.is_step_mode_active()   # Check if step mode is active\nviewer.wait_for_step()         # Wait for step trigger"
      },
      {
        "title": "Important Notes",
        "body": "Dependencies: Requires Pangolin library (auto-downloaded via gettool)\nData types: All position/point inputs must be float32\nQuaternion formats: Support wxyz and xyzw formats\nSE3 poses: Support (4, 4) or (4, 7) matrix formats\nAutomatic cleaning: clear_all_visual_elements() clears points, trajectories, cameras, planes, lines\nCamera following: Use set_main_camera() with camera ID from add_camera_*() return"
      }
    ],
    "body": "Pywayne Visualization Pangolin Utils\n\npywayne.visualization.pangolin_utils.PangolinViewer provides a Python interface to Pangolin 3D visualization library.\n\nQuick Start\nfrom pywayne.visualization.pangolin_utils import PangolinViewer, Colors\nimport numpy as np\n\n# Create viewer\nviewer = PangolinViewer(800, 600)\nviewer.init()\n\n# Run visualization loop\nwhile viewer.should_not_quit():\n    # ... add/update visual elements ...\n    viewer.show(delay_time_in_s=0.03)\n\nviewer.join()  # Wait for window to close\n\nColors\n\nUse Colors class for common colors:\n\nColors.RED      # [1.0, 0.0, 0.0]\nColors.GREEN    # [0.0, 1.0, 0.0]\nColors.BLUE     # [0.0, 0.0, 1.0]\nColors.YELLOW   # [1.0, 1.0, 0.0]\nColors.CYAN     # [0.0, 1.0, 1.0]\nColors.MAGENTA  # [1.0, 0.0, 1.0]\nColors.WHITE    # [1.0, 1.0, 1.0]\nColors.BLACK    # [0.0, 0.0, 0.0]\nColors.ORANGE   # [1.0, 0.5, 0.0]\nColors.PURPLE   # [0.5, 0.5, 0.5]\nColors.GRAY     # [0.5, 0.5, 0.5]\nColors.BROWN    # [0.6, 0.3, 0.1]\nColors.PINK     # [1.0, 0.75, 0.8]\n\nCore Control\nviewer.run()          # Start main loop (blocking)\nviewer.close()         # Close viewer\nviewer.join()         # Wait for process to end\nviewer.reset()         # Reset viewer state\nviewer.init()          # Initialize view (set initial camera)\nviewer.show(0.03)      # Render frame with delay (s)\nviewer.should_not_quit()  # Check if viewer should continue\nviewer.clear_all_visual_elements()  # Clear all elements\n\nPoint Cloud\n# Clear all points\nviewer.clear_all_points()\n\n# Add single-color points (default: red)\nviewer.add_points(points, point_size=4.0)\n\n# Add points with custom colors\nviewer.add_points_with_colors(points, colors, point_size=4.0)\n\n# Add points with named color\nviewer.add_points_with_color_name(points, color_name=\"red\", point_size=4.0)\n\n# Data format: points (N, 3), colors (N, 3)\n\nTrajectory\n# Clear all trajectories\nviewer.clear_all_trajectories()\n\n# Add trajectory with quaternions (positions + orientations)\nviewer.add_trajectory_quat(\n    positions,           # (N, 3)\n    orientations,        # (N, 4) or (N, 7) depending on quat_format\n    color=Colors.GREEN,\n    quat_format=\"wxyz\",   # \"wxyz\" or \"xyzw\"\n    line_width=2.0,\n    show_cameras=True,    # Show camera models along trajectory\n    camera_size=0.05\n)\n\n# Add trajectory with SE3 poses\nviewer.add_trajectory_se3(\n    poses_se3,           # (N, 4) or (N, 7)\n    color=Colors.GREEN,\n    line_width=2.0,\n    show_cameras=False\n)\n\nCamera\n# Clear all cameras\nviewer.clear_all_cameras()\n\n# Set main camera (view follows this camera)\nviewer.set_main_camera(camera_id)\n\n# Add camera with quaternion\ncam_id = viewer.add_camera_quat(\n    position,           # (3,)\n    orientation,         # (4,) or (7) depending on quat_format\n    color=Colors.YELLOW,\n    quat_format=\"wxyz\",\n    scale=0.1,\n    line_width=1.0\n)\n\n# Add camera with SE3 pose\ncam_id = viewer.add_camera_se3(\n    pose_se3,            # (4,) or (7)\n    color=Colors.YELLOW,\n    scale=0.1,\n    line_width=1.0\n)\n\nPlane\n# Clear all planes\nviewer.clear_all_planes()\n\n# Add plane by vertices\nviewer.add_plane(\n    vertices,        # (>=3, 3)\n    color=Colors.GRAY,\n    alpha=0.5,       # Transparency 0-1\n    label=\"plane\"\n)\n\n# Add plane by normal + center\nviewer.add_plane_normal_center(\n    normal,          # (3,) - direction of plane normal\n    center,          # (3,) - center point\n    size,            # half-size (distance from center to edge)\n    color=Colors.GRAY,\n    alpha=0.5,\n    label=\"plane\"\n)\n\n# Add plane from SE3 transformation\nviewer.add_plane_from_Twp(\n    Twp,             # (4, 4) - world pose matrix\n    size=1.0,\n    color=Colors.GREEN,\n    alpha=0.5,\n    label=\"plane\"\n)\n\nChessboard\n\nUseful for camera calibration and spatial reference:\n\n# Add chessboard on XY plane\nviewer.add_chessboard(rows=8, cols=8, cell_size=0.1)\n\n# Add chessboard on custom plane with normal\nviewer.add_chessboard(\n    rows=9, cols=6, cell_size=0.025,\n    origin=np.array([0, 0, 0]),\n    normal=np.array([1, 0, 0]),  # YZ plane\n    color1=Colors.RED,\n    color2=Colors.YELLOW,\n    alpha=0.8\n)\n\n# Add chessboard from SE3 transformation\nviewer.add_chessboard_from_Twp(\n    rows=9, cols=6, cell_size=0.025,\n    Twp=pose_matrix,\n    color1=Colors.BLACK,\n    color2=Colors.WHITE,\n    alpha=0.8,\n    label=\"calib\"\n)\n\nLine\nviewer.clear_all_lines()\n\nviewer.add_line(\n    start_point,      # (3,)\n    end_point,        # (3,)\n    color=Colors.WHITE,\n    line_width=1.0\n)\n\nImage Display\n# Set image resolution\nviewer.set_img_resolution(width, height)\n\n# Add left image\nviewer.add_image_1(img_array)           # Use numpy array\nviewer.add_image_1(image_path=\"path.jpg\")  # Use file path\n\n# Add right image\nviewer.add_image_2(img_array)\nviewer.add_image_2(image_path=\"path.jpg\")\n\nStep Mode (Debugging)\nviewer.is_step_mode_active()   # Check if step mode is active\nviewer.wait_for_step()         # Wait for step trigger\n\nImportant Notes\nDependencies: Requires Pangolin library (auto-downloaded via gettool)\nData types: All position/point inputs must be float32\nQuaternion formats: Support wxyz and xyzw formats\nSE3 poses: Support (4, 4) or (4, 7) matrix formats\nAutomatic cleaning: clear_all_visual_elements() clears points, trajectories, cameras, planes, lines\nCamera following: Use set_main_camera() with camera ID from add_camera_*() return"
  },
  "trust": {
    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/wangyendt/pangolin-utils",
    "publisherUrl": "https://clawhub.ai/wangyendt/pangolin-utils",
    "owner": "wangyendt",
    "version": "0.1.0",
    "license": null,
    "verificationStatus": "Indexed source record"
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/pangolin-utils",
    "downloadUrl": "https://openagent3.xyz/downloads/pangolin-utils",
    "agentUrl": "https://openagent3.xyz/skills/pangolin-utils/agent",
    "manifestUrl": "https://openagent3.xyz/skills/pangolin-utils/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/pangolin-utils/agent.md"
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}