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.
Open source digital rocks software platform for micro-CT, CT, thin sections and borehole image analysis. Includes tools for: annotation, AI, HPC, porous media flow simulation, porosity analysis, permeability analysis and much more.
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.
ParaView plugins
Efficient analysis of large datasets of point clouds recorded over time
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.
This repo detect objects automatically for LiDAR data
Web-based 3D point cloud viewer & analysis tool. No install — just open your browser. Supports LAS, LAZ, PLY, PCD, XYZ, PTS.
LAS/LAZ library for C#
Listen, Attend and spell model for E2E ASR. Implementation in Pytorch
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