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

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.

ParaView plugins

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.

PyTorch implementation of automatic speech recognition models.

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.

Plugin to generate a three light exposure hillshade (shaded relief by combining three light exposures)

Python library for checking conformity of Log ASCII Standard (LAS) files to standards

A set of Python modules which makes it easy to write lidar processing code in Python

PyTorch implementation of Listen, Attend and Spell (LAS) speech recognition paper

Python library for parsing standard well log files (Geophysical well logs)

End-to-End Korean Automatic Speech Recognition leveraging PyTorch and Hydra.

A simple python library for reading lidar point clouds from .las files

Convert lidar .las/.laz file coordinates between various ITRF realizations and NAD83 CSRS

Thin wrapper around pylas to make reading and writing las files as simple as possible

다양한 feature를 이용한 음성인식 LAS model입니다. (한국어는 개발예정)