3D point cloud visualizer #101
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This pull request introduces an application called "3D Point Cloud Visualizer," designed for effective visualization and analysis of 3D point cloud data. The point cloud data utilized for development and testing of this application was sourced from a publicly available dataset on Kaggle, provided by Ahmad Kamal Nasir. The dataset can be accessed at this link. The key features include:
Visualization: Interactive 3D visualization using Open3D, providing users with a real-time, rotatable view of point cloud data loaded from
.plyfiles.Data Processing: Implementation of voxel downsampling to simplify point clouds for quicker rendering and analysis without compromising on the essential structure of the data.
Statistical Analysis: A feature that calculates the mean, standard deviation, and point density of the point cloud data, offering insights into the distribution and concentration of points.
Geometric Analysis: This feature computes the centroid and volume of the point cloud's axis-aligned bounding box, aiding in spatial orientation and size estimation of the dataset.
GUI Enhancements: The application's interface now includes checkboxes to select which statistics and geometric properties to calculate.
Documentation: A README, detailing installation instructions, feature descriptions, and usage examples
These enhancements serve to make the 3D Point Cloud Visualizer a more robust and user-friendly tool for both novice users and experienced practitioners in the field of 3D data analysis.
Files Added:
point_cloud_visualizer.py: The main application script with GUI and visualization features.README.txt: Documentation file providing setup and usage instructions.