The openspoor package is intended to allow easy transformation between different geographical and topological systems commonly used in Dutch Railway

Overview

Openspoor

alt text

The openspoor package is intended to allow easy transformation between different geographical and topological systems commonly used in Dutch Railway. Its goal is to be publicly available and function as an open source package.

Currently the openspoor package allows the following transformations:

Type of input:

  • Point data

These transformations can be performed between the following systems:

Geographical systems:

  • WGS84 coordinate system (commonly known as GPS coordinates)
  • EPSG:28992 coordinate system (commonly known in the Netherlands as Rijksdriehoek)

Topological systems:

  • Geocode and geocode kilometrering
  • Spoortak and spoortak kilometrering (unavailable on switches)

Getting Started

Installation

Installation using anaconda

  • Clone the "openspoor" repository
    • pip install openspoor
  • create an environment:
    • conda create -n openspoorenv python==3.6.12
  • activate the environment:
    • conda activate openspoorenv
  • If you are installing on Windows OS with Anaconda, first install rtree and geopandas through anaconda with the commands:
    • conda install rtree==0.8.3 -y
    • conda install geopandas==0.6.1 -y
  • In the root directory of the repository, execute the command:
    • pip install -r requirements.txt
  • In the root directory of the repository, execute the command:
    • pip install .
  • In the root directory of the repository, execute the command:
    • python -m pytest
  • If all the test succeed, the openspoor package is ready to use and you are on the right "track"!

Demonstration notebook

In the future a notebook will be added that demonstrates the use of the openspoor package. For now one can take the code in the acceptance tests as example of how to use the package.

Dependencies

The transformations available in the openspoor package rely completely on data and API's made available at https://mapservices.prorail.nl/. Be aware of this dependency and specifically of the following possible issues:

  • The use of API's on mapservices.prorail.nl is changed
  • The output data of the mapservices API's is changed (with added, removed or missing columns for instance)

Furthermore mapservices.prorail.nl only provides current information about the topological systems used in Dutch Railways. As the topological systems tend to change with time, due to changing infrastructure and naming conventions, the current topological system is not necessarily sufficient to provide transformations on historical data. In the future we hope to add historical topological systems as part of the functionality of this package in such a way that it is available publicly.

Structure

The structure of the openspoor package is largely split in two categories.

MapservicesData

The MapservicesData classes use mapservices.prorail.nl API's to retrieve the necessary data to perform transformations. The essentially function as an interface with the topological systems used by ProRail.

  • PUICMapservices provides general data about railway tracks (spoor) and switches (wissel and kruisingbenen). This contains information regarding Geocode, geocodekilometrering, but also Spoortak identificatie.
  • SpoortakMapservices provides information about railway tracks concerning Spoortak identificatie and lokale kilometrering.

Transformers

The various transformers use the geopandas dataframes obtained by MapservicesData objects to add additional geographical or topological systems to a given geopandas input dataframe. The current transformers only function for geopandas dataframes containing Point data. The available transformers are:

  • TransformerCoordinatesToSpoor: transforms WGS84 or EPSG:28992 coordinates to spoortak and lokale kilomtrering as well as geocode and geocode kilometrering.
  • TransformerGeocodeToCoordinates: transforms geocode and geocode kilometrering to WGS84 or EPSG:28992 coordinates.
  • TransformerSpoorToCoordinates: transforms spoortak and lokale kilometrering to WGS84 or EPSG:28992 coordinates.

Release History

  • 0.1.0
    • The first proper release
    • ADD: transform point data between geographical systems.
  • 0.0.1
    • Work in progress

Contributing

The openspoor package stimulates every other person the contribute to the package. To do so:

  • Fork it
  • Create your feature branch (git checkout -b feature/fooBar)
  • Commit your changes (git commit -am 'Add some fooBar')
  • Push to the branch (git push origin feature/fooBar)
  • Create a new Pull Request with 3 obligated reviewers from the developement team.

You could also contribute by thinking of possible new features. The current backlog is:

  • Make the package available for the "spoor" industry.
Data Augmentation with Variational Autoencoders

Documentation Pyraug This library provides a way to perform Data Augmentation using Variational Autoencoders in a reliable way even in challenging con

112 Nov 30, 2022
Generic ecosystem for feature extraction from aerial and satellite imagery

Note: Robosat is neither maintained not actively developed any longer by Mapbox. See this issue. The main developers (@daniel-j-h, @bkowshik) are no l

Mapbox 1.9k Jan 06, 2023
we propose a novel deep network, named feature aggregation and refinement network (FARNet), for the automatic detection of anatomical landmarks.

Feature Aggregation and Refinement Network for 2D Anatomical Landmark Detection Overview Localization of anatomical landmarks is essential for clinica

aoyueyuan 0 Aug 28, 2022
GANTheftAuto is a fork of the Nvidia's GameGAN

Description GANTheftAuto is a fork of the Nvidia's GameGAN, which is research focused on emulating dynamic game environments. The early research done

Harrison 801 Dec 27, 2022
A project for developing transformer-based models for clinical relation extraction

Clinical Relation Extration with Transformers Aim This package is developed for researchers easily to use state-of-the-art transformers models for ext

uf-hobi-informatics-lab 101 Dec 19, 2022
DLFlow is a deep learning framework.

DLFlow是一套深度学习pipeline,它结合了Spark的大规模特征处理能力和Tensorflow模型构建能力。利用DLFlow可以快速处理原始特征、训练模型并进行大规模分布式预测,十分适合离线环境下的生产任务。利用DLFlow,用户只需专注于模型开发,而无需关心原始特征处理、pipeline构建、生产部署等工作。

DiDi 152 Oct 27, 2022
「PyTorch Implementation of AnimeGANv2」を用いて、生成した顔画像を元の画像に上書きするデモ

AnimeGANv2-Face-Overlay-Demo PyTorch Implementation of AnimeGANv2を用いて、生成した顔画像を元の画像に上書きするデモです。

KazuhitoTakahashi 21 Oct 18, 2022
optimization routines for hyperparameter tuning

Hyperopt: Distributed Hyperparameter Optimization Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which

Marc Claesen 398 Nov 09, 2022
A Python package for causal inference using Synthetic Controls

Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim

Oscar Engelbrektson 107 Dec 28, 2022
Masked regression code - Masked Regression

Masked Regression MR - Python Implementation This repositery provides a python implementation of MR (Masked Regression). MR can efficiently synthesize

Arbish Akram 1 Dec 23, 2021
Pytorch implementation of MaskGIT: Masked Generative Image Transformer

Pytorch implementation of MaskGIT: Masked Generative Image Transformer

Dominic Rampas 247 Dec 16, 2022
PlenOctrees: NeRF-SH Training & Conversion

PlenOctrees Official Repo: NeRF-SH training and conversion This repository contains code to train NeRF-SH and to extract the PlenOctree, constituting

Alex Yu 323 Dec 29, 2022
A project that uses optical flow and machine learning to detect aimhacking in video clips.

waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che

waldo.vision 542 Dec 03, 2022
Official PyTorch implemention of our paper "Learning to Rectify for Robust Learning with Noisy Labels".

WarPI The official PyTorch implemention of our paper "Learning to Rectify for Robust Learning with Noisy Labels". Run python main.py --corruption_type

Haoliang Sun 3 Sep 03, 2022
DeepCAD: A Deep Generative Network for Computer-Aided Design Models

DeepCAD This repository provides source code for our paper: DeepCAD: A Deep Generative Network for Computer-Aided Design Models Rundi Wu, Chang Xiao,

Rundi Wu 85 Dec 31, 2022
MTCNN face detection implementation for TensorFlow, as a PIP package.

MTCNN Implementation of the MTCNN face detector for Keras in Python3.4+. It is written from scratch, using as a reference the implementation of MTCNN

Iván de Paz Centeno 1.9k Dec 30, 2022
TrackFormer: Multi-Object Tracking with Transformers

TrackFormer: Multi-Object Tracking with Transformers This repository provides the official implementation of the TrackFormer: Multi-Object Tracking wi

Tim Meinhardt 321 Dec 29, 2022
This is a official repository of SimViT.

SimViT This is a official repository of SimViT. We will open our models and codes about object detection and semantic segmentation soon. Our code refe

ligang 57 Dec 15, 2022
Code and hyperparameters for the paper "Generative Adversarial Networks"

Generative Adversarial Networks This repository contains the code and hyperparameters for the paper: "Generative Adversarial Networks." Ian J. Goodfel

Ian Goodfellow 3.5k Jan 08, 2023
code for our paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

SHOT++ Code for our TPAMI submission "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer" that is ext

75 Dec 16, 2022