Search Results for "aosp-project-mido"

To use precompiled wheels: 1) go to releases (Files) and download tarball needed; 2) install it with command: python3 -m pip install /path/to/wheel.whl Or simply use URL in pip: python3 -m pip install https://sourceforge.net/projects/gdal-wheels-for-linux/files/GDAL-3.1.4-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl/download URL may be found under "View details" button (i) To use GDAL in C/C++ project you need to link gdal lib AND all libs located at dir GDAL.libs (usually this folder resides inside python site-packages) To compile your own wheels see information given at forefather project: https://github.com/youngpm/gdalmanylinux Usually this is done via command `make wheels` GDAL wheels for Windows are provided by Christoph Gohlke at https://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal Built with PROJ (proj.db is included), GEOS, EXPAT. ...

The Geocanvas project aims to provide a very small and simple set of APIs to assist the developer in creating geographically referenced canvas applications within the GTK/Gnome environment.

openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.

Project created to develop customizations in OpenGeo, to contribute to the standardization of formats Brazilians. Tool-Kit aplication for system Geo Integrations, using java frameworks.

This software enables easy creation and sharing of district maps online.

QGIS Plugin to Read/Write xml metadata files associated with geospatial file formats.

This project aims to provide an open source fleet management system with special focus on modularity and integration.

TransimsGui and makeTransims allow users to automatically generate triptables, timetables and vehicle files, edit individual control files, create batch files for transims feedback processes, run exe-control file pairs and run batch files.

This is the worlds first and probably only FLOSS project aimed to create a lowbudget, based on availble technology, cruise missile. No this is not a Joke, its for real. Why? Since no one has tried to do this before and certainly not under the GPL.

easyDevice is a open source project for telit modules GM862 and GM863. Main software targets are vehicle location tracking, data history functionality and making sure there are no data losses when data is transfered to server.

AVPython embeds the Python programming language within ArcView GIS 3.x. This project will also encompass efforts to build a similar bridge between Python and ArcObjects. An integrated, redistributable Python / PyWin32 setup wizard is also published here.

A Open Source project with the main goal to make a simple way to display 3D objects from a Geodatabase (PostgreSQL/PostGIS) on the Web. This project was created by OpenGEO (www.opengeo.com.br).

The NHD Software Project is a collection of the utilities, scripts, APIs, standards, and application extensions used for the quality assurance of stream and river data, conflation/generalisation of hydrographic data, and other hydrologic data maintenance.

This project exists as a central meeting place for those wishing to share in-house developed applications and tools for local government (and related industries) in Australia.

The aim of this project is to translate the geostatistical BMELib Matlab Toolbox (http://www.unc.edu/depts/case/BMELIB/) into Python.

GrassView is a wxPython GUI for GRASS, the GNU Geographical Information System.

This project provides a library written in Python for reading and eventually writing ISO8211 files. ISO8211 is a format used for various GIS systems (geographic data), including SDTS, the format used by the US Geological Survey.

...There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.