Search Results for "spatial"
Sort By:
Showing 406 open source projects for "spatial"
View related business solutions-
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
GeoStats.jl
An extensible framework for geospatial data science
...Visualization is supported via integration with Makie.jl to produce spatial renderings, mesh visualizations, and variable overlays. -
2
Seurat
R toolkit for single cell genomics
Seurat is a comprehensive R toolkit for single-cell genomics analysis, introduced by the Satija Lab at NYGC. It supports quality control, normalization, clustering, integration of multimodal data (e.g., scRNA‑seq, spatial, CITE‑seq), and visualization. Seurat v5 introduces scalable workflows and spatial transcriptomics support, commonly used in academic and industry research for single-cell studies. -
3
GeoLibre
A lightweight, cloud-native GIS platform
...The platform keeps data local and private while still supporting cloud-native geospatial workflows. It uses technologies such as Tauri, React, TypeScript, MapLibre GL JS, DuckDB-WASM Spatial, and deck.gl. Users can load many local and remote geospatial formats, style map layers, inspect attributes, and run spatial analysis. It also includes advanced tools such as multi-map comparison, SQL workspaces, story maps, field collection, plugins, Python automation, and an AI GIS assistant. -
4
Apache Sedona
Cluster computing framework for processing large-scale geospatial data
Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ... -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
...By learning the RF signature of each environment over time, RuView adapts automatically to different spaces and improves its sensing accuracy. Designed for applications ranging from healthcare monitoring to disaster response, it enables spaces to gain spatial awareness using the radio signals already present in the environment. -
6
PHP-CRUD-API
Single file PHP script that adds a REST API to a SQL database
Single file PHP script that adds a REST API to a MySQL/MariaDB, PostgreSQL, SQL Server or SQLite database. Howto: Upload "api.php" to your webserver, configure it to connect to your database, have an instant full-featured REST API. This is the TreeQL reference implementation in PHP. This is a single file application! Upload "api.php" somewhere and enjoy! For local development you may run PHP's built-in web server. All configuration options are also available as environment variables. Write... -
7
Flatbush
A very fast static spatial index for 2D points and rectangles in JS
A really fast static spatial index for 2D points and rectangles in JavaScript. An efficient implementation of the packed Hilbert R-tree algorithm. Enables fast spatial queries on a very large number of objects (e.g. millions), which is very useful in maps, data visualizations and computational geometry algorithms. -
8
Manyfold
A self-hosted digital asset manager for 3d print files
...The platform emphasizes accessibility and flexibility, making 3D collaboration as easy as sharing a document link while still providing spatial audio, synchronized interactions, and physics-aware environments that feel alive and responsive. -
9
TorchIO
Medical imaging toolkit for deep learning
TorchIO is an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of 3D medical images in deep learning, following the design of PyTorch. It includes multiple intensity and spatial transforms for data augmentation and preprocessing. These transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity (bias) or k-space motion artifacts. TorchIO is a Python package containing a set of tools to efficiently read, preprocess, sample, augment, and write 3D medical images in deep learning applications written in PyTorch, including intensity and spatial transforms for data augmentation and preprocessing. ... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
10
Autonomous Agents
Autonomous Agents (LLMs) research papers. Updated Daily
...The project explores how multiple agents can cooperate and interact with complex environments through machine learning, imitation learning, and multimodal sensing. It includes frameworks that integrate visual perception, tactile sensing, and spatial reasoning to guide the actions of robotic agents during manipulation or collaborative tasks. One of the central concepts explored in the repository is the integration of different sensory modalities using advanced machine learning techniques such as Feature-wise Linear Modulation and graph-based attention mechanisms. These methods allow agents to combine visual and geometric information while maintaining awareness of the spatial relationships between agents and objects. -
11
GemGIS
Spatial data processing for geomodeling
GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. Postprocessing of model results will allow export from GemPy to geoinformation systems such as QGIS and ArcGIS or to Google Earth for further use. -
12
ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
...The core idea is a hybrid region representation that mixes discrete coordinates with continuous visual features, so the model can fluidly handle “any-form” referring while maintaining precise spatial localization. The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning. -
13
CGAL
The Computational Geometry Algorithms Library
...CGAL features a great range of data structures and algorithms, including Voronoi diagrams, cell complexes and polyhedra, triangulations, arrangements of curves, surface and volume mesh generation, spatial searching, alpha shapes, geometry processing, and many more. The use of these result in beautiful, visually complex and accurate representations. -
14
L7
Large-scale WebGL-powered geospatial data visualization analysis
...L7 focuses on the visual expression of data, and realizes clear and effective expression from data to information through the setting of visual variables such as color, size, texture, direction, and volume. L7 can meet common map charts, visual analysis of BI systems, and application system development needs such as spatial information management and analysis in the fields of GIS, transportation, electricity, land, agriculture, and cities. Supports many base map, many rendering engines, and layer free customization, extension, combination. Supports multiple base maps, rendering engines, layers can be customized, expanded, and combined freely. -
15
RBush
High-performance JavaScript R-tree-based 2D spatial index
RBush is a high-performance JavaScript library for 2D spatial indexing of points and rectangles. It's based on an optimized R-tree data structure with bulk insertion support. Spatial index is a special data structure for points and rectangles that allows you to perform queries like "all items within this bounding box" very efficiently (e.g. hundreds of times faster than looping over all items). -
16
Qwen3-VL
Qwen3-VL, the multimodal large language model series by Alibaba Cloud
...Qwen3-VL is built for complex tasks such as GUI automation, multimodal coding (converting images or videos into HTML, CSS, JS, or Draw.io diagrams), long-context reasoning with support up to 1M tokens, and comprehensive video understanding. It also brings advanced perception capabilities, including spatial grounding, object recognition, OCR across 32 languages, and robust handling of challenging inputs like low-light or distorted text. -
17
rayshader
R Package for 2D and 3D mapping and data visualization
...It supports outputting high-quality renders via path tracing (using a companion package) and also offers depth-of-field (“cinematic blur”) effects to bring visual focus into scenes. It allows layering relational data (roads, points, polygons) on top of the shaded terrain, so you can combine spatial data overlays with the 3D model. The package can export models to 3D formats like STL or OBJ for 3D printing or external rendering. -
18
Lyra 2
Project Lyra: Open Generative 3D World Models
...It enables the creation of fully explorable 3D environments from minimal inputs such as a single image or video, leveraging self-distillation methods to generate consistent spatial representations. The system evolves across versions, with newer iterations introducing long-horizon generation and improved 3D consistency across frames. It combines elements of computer vision, generative modeling, and spatial intelligence to produce dynamic and navigable virtual worlds. The architecture is designed to handle both 3D and 4D scene generation, making it suitable for applications such as simulation, gaming, and virtual environments. ... -
19
Arnis
Generate any location from the real world in Minecraft
Arnis is a free and open-source desktop application that generates playable Minecraft worlds from real-world geographic data. The project processes large datasets from sources such as OpenStreetMap and elevation data to recreate terrain, buildings, roads, and landmarks with impressive spatial accuracy inside Minecraft. By converting geographic information into Minecraft blocks and structures, Arnis allows users to explore real cities, neighborhoods, and landscapes in a virtual environment that mirrors the real world. The tool handles large-scale geospatial processing and transforms raw mapping data into a format compatible with Minecraft world generation. ... -
20
QGIS
Cross platform (lin/win/mac) geographical information system (GIS)
Create, edit, visualize, analyze and publish geospatial information on Windows, Mac, Linux, BSD and mobile devices. For your desktop, server, in your web browser and as developer libraries. QGIS is a user-friendly open-source Geographic Information System (GIS) licensed under the GNU General Public License. QGIS is an official project of the Open Source Geospatial Foundation (OSGeo). It runs on Linux, Unix, Mac OSX, Windows and Android and supports numerous vector, raster, and database... -
21
NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
...The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of pickups/dropoffs). It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities. -
22
TURF
A modular geospatial engine written in JavaScript
Turf is a JavaScript library for spatial analysis. It includes traditional spatial operations, helper functions for creating GeoJSON data, and data classification and statistics tools. Turf can be added to your website as a client-side plugin, or you can run Turf server-side with Node.js. Modular, simple-to-understand JavaScript functions that speak GeoJSON. Turf is a collection of small modules, you only need to take what you want to use. -
23
S2 Geometry
Computational geometry and spatial indexing on the sphere
s2geometry is Google’s open source geometry library designed for representing, analyzing, and manipulating geometric shapes on a sphere rather than a flat plane. This makes it particularly suited for applications involving geospatial data, such as mapping, spatial indexing, and geographic information systems (GIS). The library provides a robust mathematical framework for spherical geometry, allowing developers to work with polygons, points, and regions on the Earth’s surface using consistent and precise algorithms. Unlike traditional 2D geometry libraries, S2 ensures accuracy over large scales by modeling the globe directly, avoiding distortions caused by map projections. ... -
24
Tile38
Ultra Fast Geospatial Database & Geofencing Server
When you need the best performance for your location-based applications, you can rely on Tile38. Tile38 is an ultra-fast, open source geospatial database and geofencing server capable of real-time geofencing, fast spatial indexing and more. It supports a variety of object types including lat/lon, Geohash, bbox, GeoJSON, QuadKey, and XYZ tile; and is capable of operations like Nearby, Within, and Intersects. There’s also built-in support for many popular tools. Tile38 is made up of 3 main components: the server, command line interface tool and server benchmark tool. ... -
25
Clustering.jl
A Julia package for data clustering
Methods for data clustering and evaluation of clustering quality.
