GDAL is an MIT-licensed open source translator library that provides a unified abstract data model for reading and writing geospatial raster and vector data across hundreds of file formats. It serves as a foundational geospatial data translation library, enabling access to diverse geospatial data formats through a single, consistent interface. The library exposes its core functionality through command-line utilities that allow users to translate, convert, and process geospatial data between formats. A coordinate transformation engine handles conversions between spatial reference systems, whil
This project is a utility library for the Google Maps SDK for Android, providing a suite of specialized tools for rendering geospatial data, calculating spherical geometry, and visualizing map markers and heatmaps. It serves as a helper collection to handle complex geospatial tasks within Android applications. The library features a marker clustering tool to group nearby markers into single icons and a map data visualizer for generating heatmaps based on the intensity and distribution of geographic points. It also includes a polyline encoding tool for compressing coordinate sequences into com
This project is an AWS pandas integration library and data pipeline framework designed to simplify the movement and transformation of data between local memory and AWS storage and analytics services. It functions as a cloud data lake toolkit and storage file manager, allowing users to read, write, and transform structured data across various cloud environments. The library distinguishes itself as a distributed compute orchestrator capable of managing clusters in environments such as EMR to process datasets that exceed the memory limits of a single machine. It also provides specialized capabil
Deep learning docker files and docker images for geospatial anaysis. It contains the most popular deep learning frameworks(PyTorch and Tensorflow) with CPU and GPU support (CUDA and cuDNN included). And some other commonly used packages in machine learning and geospatial anaysis.
Las características principales de sshuair/dl-satellite-docker son: Geospatial Data Tools, Cloud Infrastructure, Geospatial Data Infrastructure.
Las alternativas de código abierto para sshuair/dl-satellite-docker incluyen: osgeo/gdal — GDAL is an MIT-licensed open source translator library that provides a unified abstract data model for reading and… googlemaps/android-maps-utils — This project is a utility library for the Google Maps SDK for Android, providing a suite of specialized tools for… aws/aws-sdk-ruby — The official AWS SDK for Ruby. azavea/loam — A wrapper for running GDAL in the browser using gdal-js. c6fc/npk. awslabs/aws-data-wrangler — This project is an AWS pandas integration library and data pipeline framework designed to simplify the movement and…