Loaders for big data visualization. Website:

Airborne LiDAR data manipulation and visualisation for forestry application

Open-Source Toolkit for End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.

Drag-n-drop In-browser LAS/LAZ point cloud viewer. http://plas.io

Laspy is a pythonic interface for reading/modifying/creating .LAS LIDAR files matching specification 1.0-1.4.

A pytorch based end2end speech recognition system.

Tools for analyzing aerial point clouds of forest data.

Read and write ASPRS las files, Rust edition.

激光点云处理工具，集成Cesium与Potree实现在线点云查看和处理

ParaView plugins

Visualization, processing and analysis of Lidar point clouds, mainly focused on forest environment. New version of 3D Forest. Process files with terabytes of data. Edit new point attributes. Simple addition of new features by plugins.

Convert various AEC model formats for efficient viewing in the browser with xeokit.

This repo detect objects automatically for LiDAR data

Listen, Attend and spell model for E2E ASR. Implementation in Pytorch

LAS Explorer is a Streamlit web app that allows you to understand the contents of a LAS file. Also includes the ability to identify missing data intervals.

copc-lib provides an easy-to-use reader and writer interface for creating and reading Cloud Optimized Point Clouds, with bindings for Python and C++

LAS/LAZ library for C#

PyTorch implementation of automatic speech recognition models.

R package to read and write las and laz files used to store LiDAR data

JavaScript for converting well-log standard .las file format to json format