Point cloud processing tool library.

Overview

Point Cloud ToolBox

This point cloud processing tool library can be used to process point clouds, 3d meshes, and voxels.

Environment

python 3.7.5

Dependent packages:
- openmesh==1.1.6
- open3d==0.13.0
- plyfile==0.7.4
- numpy==1.21.0
- vtk==8.2.0
- python-pcl==0.3.0rc1

How to install the environment:
# pip install requirements.txt

Todo

Point Cloud

  • format conversion (pointcloud->pointcloud)
    • pcd -> xyz | pts | txt | csv | ply
    • las -> pcd | xyz | pts | ply | txt | csv
    • ply -> pcd | xyz | pts | txt | csv
    • xyz -> pcd | pts | ply | txt | csv
    • pts -> pcd | xyz | ply | txt | csv
    • txt -> pcd | ply | xyz | pts
  • Calculate the surface area and volume of 3D Mesh
  • Point cloud voxelization
  • downsampling
    • farthest point sampling(FPS)
    • random sampling
    • uniform sampling
    • voxel sampling
  • upsampling
  • filtering
    • PassThrough Filter
    • VoxelGrid Filter
    • project_inliers Filter
    • remove_outliers Filter
    • statistical_removal Filter
  • registration
  • 3D reconstruction
  • visualization

3d Mesh

  • format conversion (mesh->mesh)
    • ply -> obj | stl | off
    • obj -> ply | off | stl
    • off -> ply | obj | stl
  • down sampling into point cloud
    • poisson disk sampling
    • uniform sampling
  • mesh filtering
    • Taubin filter
    • Laplacian smooth
    • simple neighbour average
  • mesh voxelization
  • mesh subdivision
  • 3d mesh visualization

voxel

  • visualization

Use

You can find command in run.sh.

To be continued...

Owner
ZhangXinyun
ZhangXinyun
Code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech Recognition"

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

ASAPP Research 67 Dec 01, 2022
[NeurIPS2021] Code Release of K-Net: Towards Unified Image Segmentation

K-Net: Towards Unified Image Segmentation Introduction This is an official release of the paper K-Net:Towards Unified Image Segmentation. K-Net will a

Wenwei Zhang 423 Jan 02, 2023
A data annotation pipeline to generate high-quality, large-scale speech datasets with machine pre-labeling and fully manual auditing.

About This repository provides data and code for the paper: Scalable Data Annotation Pipeline for High-Quality Large Speech Datasets Development (subm

Appen Repos 86 Dec 07, 2022
Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensors, CVPR 2021

Human POSEitioning System (HPS): 3D Human Pose Estimation and Self-localization in Large Scenes from Body-Mounted Sensors Human POSEitioning System (H

Aymen Mir 66 Dec 21, 2022
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

Phil Wang 383 Jan 02, 2023
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

DV Lab 116 Dec 20, 2022
QilingLab challenge writeup

qiling lab writeup shielder 在 2021/7/21 發布了 QilingLab 來幫助學習 qiling framwork 的用法,剛好最近有用到,順手解了一下並寫了一下 writeup。 前情提要 Qiling 是一款功能強大的模擬框架,和 qemu user mode

Yuan 17 Nov 17, 2022
Synthesizing and manipulating 2048x1024 images with conditional GANs

pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio

NVIDIA Corporation 6k Dec 27, 2022
A fast, dataset-agnostic, deep visual search engine for digital art history

imgs.ai imgs.ai is a fast, dataset-agnostic, deep visual search engine for digital art history based on neural network embeddings. It utilizes modern

Fabian Offert 5 Dec 14, 2022
This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effects in Video."

Omnimatte in PyTorch This repository contains a re-implementation of the code for the CVPR 2021 paper "Omnimatte: Associating Objects and Their Effect

Erika Lu 728 Dec 28, 2022
This code is part of the reproducibility package for the SANER 2022 paper "Generating Clarifying Questions for Query Refinement in Source Code Search".

Clarifying Questions for Query Refinement in Source Code Search This code is part of the reproducibility package for the SANER 2022 paper "Generating

Zachary Eberhart 0 Dec 04, 2021
Repo público onde postarei meus estudos de Python, buscando aprender por meio do compartilhamento do aprendizado!

Seja bem vindo à minha repo de Estudos em Python 3! Este é um repositório criado por um programador amador que estuda tópicos de finanças, estatística

32 Dec 24, 2022
git《Commonsense Knowledge Base Completion with Structural and Semantic Context》(AAAI 2020) GitHub: [fig1]

Commonsense Knowledge Base Completion with Structural and Semantic Context Code for the paper Commonsense Knowledge Base Completion with Structural an

AI2 96 Nov 05, 2022
Hyperparameters tuning and features selection are two common steps in every machine learning pipeline.

shap-hypetune A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models. Overview Hyperparameters t

Marco Cerliani 422 Jan 08, 2023
This is the pytorch implementation of the paper - Axiomatic Attribution for Deep Networks.

Integrated Gradients This is the pytorch implementation of "Axiomatic Attribution for Deep Networks". The original tensorflow version could be found h

Tianhong Dai 150 Dec 23, 2022
Time Delayed NN implemented in pytorch

Pytorch Time Delayed NN Time Delayed NN implemented in PyTorch. Usage kernels = [(1, 25), (2, 50), (3, 75), (4, 100), (5, 125), (6, 150)] tdnn = TDNN

Daniil Gavrilov 79 Aug 04, 2022
This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Koltun"

Learning to propose objects This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Ko

Philipp Krähenbühl 90 Sep 10, 2021
Council-GAN - Implementation for our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020)

Council-GAN Implementation of our paper Breaking the Cycle - Colleagues are all you need (CVPR 2020) Paper Ori Nizan , Ayellet Tal, Breaking the Cycle

ori nizan 260 Nov 16, 2022
Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided curriculum Learning Approach

Get Fooled for the Right Reason Official repository for the NeurIPS 2021 paper Get Fooled for the Right Reason: Improving Adversarial Robustness throu

Sowrya Gali 1 Apr 25, 2022
Cognate Detection Repository

Cognate Detection Repository Details This repository contains the data for two publications: Challenge Dataset of Cognates and False Friend Pairs from

Diptesh Kanojia 1 Apr 26, 2022