🛠️ SLAMcore SLAM Utilities

Overview

slamcore_utils

PyPI version Code style: black

Description

This repo contains the slamcore-setup-dataset script. It can be used for installing a sample dataset for offline testing and evaluation of SLAMcore's Localization and Mapping capabilities.

Currently the following types of datasets are supported:

Usage

After installation the script should be available in your path. Executing it will guide you through a list of questions in order to properly setup a sample SLAM dataset.

Here is a sample execution of the said script to enable processing of the TUM-VI dataset-room4_1024_16

setup-dataset2

Here's the same execution for the OpenLORIS cafe1-1 dataset

setup-dataset1

And here's the execution guiding the user to the right download page, when the datasets are not available locally yet.

setup-dataset3

Installation

Install it directly from PyPI:

pip3 install --user --upgrade slamcore_utils[tqdm]

# Or if you don't want tqdm's polished progress bars
pip3 install --user --upgrade slamcore_utils
I don't want to have to install it

Make sure the project dependencies are installed:

pip3 install -r requirements.txt

Then adjust your PYTHONPATH variable and run accordingly:

git clone https://github.com/slamcore/slamcore_utils
cd slamcore_utils
export PYTHONPATH=$PYTHONPATH:$PWD
./slamcore_utils/scripts/setup_dataset.py
I don't want to install any of your dependencies in my user's install directory

Consider using either pipx or poetry to install this package and its dependencies isolated in a virtual environment:

git clone https://github.com/slamcore/slamcore_utils
poetry install
poetry shell

# the executables should now be available in your $PATH
setup-dataset

About SLAMcore

SLAMcore offers commercial-grade visual-inertial simultaneous localisation and mapping (SLAM) software for real-time autonomous navigation on robots and drones. Request access today to get started.

Owner
SLAMcore
SLAMcore
A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation.

Continuous Wasserstein-2 Benchmark This is the official Python implementation of the NeurIPS 2021 paper Do Neural Optimal Transport Solvers Work? A Co

Alexander 22 Dec 12, 2022
[ACMMM 2021, Oral] Code release for "Elastic Tactile Simulation Towards Tactile-Visual Perception"

EIP: Elastic Interaction of Particles Code release for "Elastic Tactile Simulation Towards Tactile-Visual Perception", in ACMMM (Oral) 2021. By Yikai

Yikai Wang 37 Dec 20, 2022
code for our BMVC 2021 paper "HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification"

HCV_IIRC code for our BMVC 2021 paper HCV: Hierarchy-Consistency Verification for Incremental Implicitly-Refined Classification by Kai Wang, Xialei Li

kai wang 13 Oct 03, 2022
Unofficial PyTorch implementation of Fastformer based on paper "Fastformer: Additive Attention Can Be All You Need"."

Fastformer-PyTorch Unofficial PyTorch implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Usage : import t

Hong-Jia Chen 126 Dec 06, 2022
Pytorch Implementation of rpautrat/SuperPoint

SuperPoint-Pytorch (A Pure Pytorch Implementation) SuperPoint: Self-Supervised Interest Point Detection and Description Thanks This work is based on:

76 Dec 27, 2022
Codebase for "Revisiting spatio-temporal layouts for compositional action recognition" (Oral at BMVC 2021).

Revisiting spatio-temporal layouts for compositional action recognition Codebase for "Revisiting spatio-temporal layouts for compositional action reco

Gorjan 20 Dec 15, 2022
Official PyTorch implementation and pretrained models of the paper Self-Supervised Classification Network

Self-Classifier: Self-Supervised Classification Network Official PyTorch implementation and pretrained models of the paper Self-Supervised Classificat

Elad Amrani 24 Dec 21, 2022
This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (ICLR 2022)

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

Beatrice Bevilacqua 59 Dec 13, 2022
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack

FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack Case study of the FCA. The code can be find in FCA. Cas

IDRL 21 Dec 15, 2022
Implementation for the paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR2021).

Invertible Image Denoising This is the PyTorch implementation of paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR 20

157 Dec 25, 2022
How Effective is Incongruity? Implications for Code-mix Sarcasm Detection.

Code for the paper: How Effective is Incongruity? Implications for Code-mix Sarcasm Detection - ICON ACL 2021

2 Jun 05, 2022
Reinforcement Learning for Portfolio Management

qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive

Angelos Filos 406 Jan 01, 2023
Event-forecasting - Event Forecasting Algorithms With Python

event-forecasting Event Forecasting Algorithms Theory Correlating events in comp

Intellia ICT 4 Feb 15, 2022
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)

This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the offi

789 Jan 04, 2023
Framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample resolution

Sample-specific Bayesian Networks A framework for estimating the structures and parameters of Bayesian networks (DAGs) at per-sample or per-patient re

Caleb Ellington 1 Sep 23, 2022
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)

nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom

Qiujie (Jay) Dong 2 Oct 31, 2022
An example project demonstrating how the Autonomous Learning Library can be used to build new reinforcement learning agents.

About This repository shows how Autonomous Learning Library can be used to build new reinforcement learning agents. In particular, it contains a model

Chris Nota 5 Aug 30, 2022
A script helps the user to update Linux and Mac systems through the terminal

Description This script helps the user to update Linux and Mac systems through the terminal. All the user has to install some requirements and then ru

Roxcoder 2 Jan 23, 2022
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne

MALL Lab (IISc) 56 Dec 03, 2022
Notepy is a full-featured Notepad Python app

Notepy A full featured python text-editor Notable features Autocompletion for parenthesis and quote Auto identation Syntax highlighting Compile and ru

Mirko Rovere 11 Sep 28, 2022