q3dviewer 1.3.4

q3dviewer is a library designed for quickly deploying a 3D viewer. It is based on Qt and provides efficient OpenGL items for displaying 3D objects (e.g., point clouds, cameras, and 3D Gaussians). You can use it to visualize your 3D data or set up an efficient viewer application. It is inspired by PyQtGraph but focuses more on efficient 3D rendering.

To show how to use q3dviewer as a library, we also provide some very useful tools.

Installation

For library usage:

pip install q3dviewer

For additional GUI tools (q3d.film_maker, etc.):

pip install "q3dviewer[tools]"

Note for Linux Users

If you encounter an error related to loading the shared library libxcb-cursor.so.0 on Ubuntu 20.04 or 22.04, please install libxcb-cursor0:

sudo apt-get install libxcb-cursor0

Tools

Once installed, you can directly use the following tools:

1. Cloud Viewer

A tool for visualizing point cloud files (LAS, PCD, PLY, E57). Launch it by executing the following command in your terminal:

q3d.cloud_viewer

Alternatively, if the path is not set (though it's not recommended):

python3 -m q3dviewer.tools.cloud_viewer

Basic Operations

📁 Load Files - Drag and drop files into the viewer

• Point clouds: .pcd, .ply, .las, .e57
• Mesh files: .stl

📏 Measure Distance - Interactive point measurement

• Ctrl + Left Click: Add measurement point
• Ctrl + Right Click: Remove last point
• Total distance displayed automatically

🎥 Camera Controls - Navigate the 3D scene

• Double Click: Set camera center to point
• Right Drag: Rotate view
• Left Drag: Pan view
• Mouse Wheel: Zoom in/out

⚙️ Settings - Press M to open settings window

• Manual adjustment of visualization properties
• Ctrl + S: Save all settings
• Ctrl + L: Load all settings

🔄 Depth Sorting - Press R to force one depth sort

🎯 Center Point - Shown while the camera view is changing

For example, you can download and view point clouds of Tokyo in LAS format from the following link:

Tokyo Point Clouds

Mesh Support - Starting from version 1.2.4, mesh files (.stl) are now supported.

2. Cloud Editor

A simple tool for editing point clouds. It supports PCD, PLY, LAS, and E57 files, point deletion, measurement, undo, and saving.

q3d.cloud_editor

3. ROS Viewer

A high-performance SLAM viewer compatible with ROS, serving as an alternative to RVIZ.

roscore &
q3d.ros_viewer

4. Film Maker

Would you like to create a video from point cloud data? With Film Maker, you can easily create videos with simple operations. Just edit keyframes using the user-friendly GUI, and the software will automatically interpolate the keyframes to generate the video.

q3d.film_maker

Basic Operations

• File loading, camera controls, and settings: Same as Cloud Viewer
• Space: Add a keyframe
• Delete: Remove the selected keyframe
• Play: Play or stop the camera motion
• Record: Record the camera motion during playback
• Save Camera Motion / Load Camera Motion: Save or restore keyframes

Film Maker GUI:

The demo video demonstrating how to use Film Maker utilizes the cloud data of Kyobashi Station Area located in Osaka, Japan.

5. Gaussian Viewer

A simple viewer for 3D Gaussians. See EasyGaussianSplatting for more information.

q3d.gaussian_viewer  # Drag and drop your Gaussian file onto the window

Using as a Library

Using the examples above, you can easily customize and develop your own 3D viewer with q3dviewer. Below is a coding example.

Custom 3D Viewer

#!/usr/bin/env python3

import q3dviewer as q3d  # Import q3dviewer

def main():
    # Create a Qt application
    app = q3d.QApplication([])

    # Create various 3D items
    axis_item = q3d.AxisItem(size=0.5, width=5)
    grid_item = q3d.GridItem(size=10, spacing=1)

    # Create a viewer
    viewer = q3d.Viewer(name='example')
    
    # Add items to the viewer
    viewer.add_items({
        'grid': grid_item,
        'axis': axis_item,
    })

    # Show the viewer & run the Qt application
    viewer.show()
    app.exec()

if __name__ == '__main__':
    main()

q3dviewer provides the following 3D items:

• AxisItem: Displays coordinate axes or the origin position.
• CenterItem: Displays a shaded center marker while the camera is moving.
• CloudItem: Displays point clouds.
• CloudIOItem: Displays point clouds with input/output capabilities.
• CloudSortItem: Displays point clouds with depth sorting support.
• FrameItem: Displays camera or coordinate frames.
• GaussianItem: Displays 3D Gaussians.
• GridItem: Displays grids.
• ImageItem: Displays 2D images.
• LineItem: Displays lines or trajectories.
• MeshItem: Displays dynamic quadrilateral meshes.
• SatelliteMapItem: Displays satellite map tiles.
• StaticMeshItem: Displays static triangular meshes.
• Text2DItem: Displays 2D text.
• Text3DItem: Displays 3D text and markers.

Developing Custom Items

In addition to the standard 3D items provided, you can visualize custom 3D items with simple coding. Below is a sample:

from OpenGL.GL import *
import numpy as np
import q3dviewer as q3d
from q3dviewer.Qt.QtWidgets import QLabel, QSpinBox

class YourItem(q3d.BaseItem):
    def __init__(self):
        super(YourItem, self).__init__()
        # Necessary initialization

    def add_setting(self, layout):
        # Initialize the settings screen
        label = QLabel("Add your setting:")
        layout.addWidget(label)
        box = QSpinBox()
        layout.addWidget(box)

    def set_data(self, data):
        # Obtain the data you want to visualize
        # Update the item state, then notify the viewer to repaint.
        self.data = data
        self.notify_changed()
        pass

    def set_color(self, color):
        # Any visual setting change must also notify the viewer.
        self.color = color
        self.notify_changed()

    def initialize_gl(self):
        # OpenGL initialization settings (if needed)
        pass

    def paint(self):
        # Visualize 3D objects using OpenGL
        pass

Enjoy using q3dviewer!