Search Results for "jpk data processing"
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Showing 305 open source projects for "jpk data processing"
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LAStools
efficient tools for LiDAR processing
LAStools is a collection of efficient, multi-core, scriptable tools for processing LiDAR data. It supports various formats, including LAS, LAZ, Terrasolid BIN, and ESRI Shapefiles, providing a comprehensive suite for LiDAR data management and analysis. -
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MeshLab
The open source mesh processing system
...VCG can be used as a stand-alone large-scale automated mesh processing pipeline, while MeshLab makes it easy to experiment with its algorithms interactively. The open source system for processing and editing 3D triangular meshes. It provides a set of tools for editing, cleaning, healing, inspecting, rendering, texturing and converting meshes. It offers features for processing raw data produced by 3D digitization tools/devices and for preparing models for 3D printing. -
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Serial Studio
Multi-purpose serial data visualization & processing
Serial Studio is a simple, multi-platform, and multi-purpose serial data visualization program that allows embedded developers to visualize, analyze, and present data generated from their projects and devices while avoiding the need to write project-specific visualization software. Over my many CanSat-based competitions, I found myself writing and maintaining several Ground Station software for each program. However, I decided that it would be easier and more sustainable to define one... -
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GLM
OpenGL Mathematics (GLM)
...This project isn't limited to GLSL features. An extension system, based on the GLSL extension conventions, provides extended capabilities: matrix transformations, quaternions, data packing, random numbers, noise, etc. This library works perfectly with OpenGL but it also ensures interoperability with other third party libraries and SDK. It is a good candidate for software rendering (raytracing / rasterisation), image processing, physics simulations and any development context that requires a simple and convenient mathematics library. ... -
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GridDB
GridDB is a next-generation open source database
...Multi-model architecture capable of supporting various data stores with time-series data-oriented and pluggable data stores for efficient real-time processing and management of huge amounts of time-series data at high frequency. Various architectural innovations, such as in-memory orientation with "memory as the main unit and disk as the secondary unit" and event-driven design with minimal overhead, have been incorporated to achieve processing capabilities that can handle petabyte-scale applications. -
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Open3D
A modern library for 3D data processing
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently... -
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and... -
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DALI
A GPU-accelerated library containing highly optimized building blocks
The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. -
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CGAL
The Computational Geometry Algorithms Library
...These algorithms are useful in a wide range of applications, including computer aided design, robotics, molecular biology, medical imaging, geographic information systems and more. 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. -
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Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
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ROOT
Analyzing, storing and visualizing big data, scientifically
...ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modeling, and minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis. -
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if... -
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Memgraph
Open-source graph database, tuned for dynamic analytics environments
A high-performance, in-memory graph database designed for real-time analytics and complex network data processing. -
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ClickHouse
A fast open-source OLAP database management system
...ClickHouse also has exceptional hardware efficiency and a host of other features, including a feature-rich SQL database, vectorized query execution, real-time query processing and data ingestion, and more. -
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StarRocks
StarRocks is a next-gen sub-second MPP database for full analytics
StarRocks is the next generation of real-time SQL engines for enterprise analytics. Real-time analytics is notoriously difficult. Complex data pipelines and de-normalized tables have always been a necessary evil. Processing any updates or deletes once data arrives has not been possible- until now. StarRocks solves these challenges and makes real-time analytics easy. Get amazing query performance on Star or Snowflake Schemas directly. From canceled orders to updated items, your analytics applications can easily handle them with StarRocks. ... -
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DuckDB
DuckDB is an in-process SQL OLAP Database Management System
...DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to the Why DuckDB page on our website. Processing and storing tabular datasets, e.g. from CSV or Parquet files. Interactive data analysis, e.g. Joining & aggregate multiple large tables. Concurrent large changes, to multiple large tables, e.g. appending rows, adding/removing/updating columns. Large result set transfer to client. For development, DuckDB requires CMake, Python3 and a C++11 compliant compiler. ... -
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KuzuDB
Embeddable property graph database management system
KuzuDB is a high-performance graph database optimized for analytical queries, built from the ground up with a columnar storage engine. It is designed to efficiently process large-scale graph workloads, making it ideal for data science, machine learning, and knowledge graph applications. -
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mediasoup
Cutting Edge WebRTC Video Conferencing
mediasoup is a Node.js library that provides a cutting-edge WebRTC server capable of handling real-time communications with efficient media routing and processing. -
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Neuroglancer
WebGL-based viewer for volumetric data
...The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. Extensively used in neuroscience research, Neuroglancer supports integration with tools. -
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Alibaba iLogtail
Fast and Lightweight Observability Data Collector
iLogtail was born for observable scenarios and has many production-level features such as lightweight, high performance, and automated configuration, which are widely used internally by Alibaba Group and tens of thousands of external Alibaba Cloud customers. You can deploy it in physical machines, Kubernetes and other environments to collect telemetry data, such as logs, traces and metrics. Supports a variety of Logs, Traces, and Metrics data collection, and is friendly to container and... -
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Apache Thrift
Language-independent stack for point-to-point RPC implementation
Apache Thrift is a software framework for scalable cross-language services development. Apache Thrift allows you to define data types and service interfaces in a simple definition file. Taking that file as input, the compiler generates code to be used to easily build RPC clients and servers that communicate seamlessly across programming languages. Thrift is a lightweight, language-independent software stack for point-to-point RPC implementation. Thrift provides clean abstractions and implementations for data transport, data serialization, and application level processing. ... -
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BrowserOS
Agentic browser; privacy-first alternative to ChatGPT Atlas
BrowserOS is an open-source, agentic web browser built on a Chromium base that integrates AI agents directly into the browsing experience. Rather than just doing standard browsing, it places AI intelligence at the core: you can connect your own API keys (for e.g., OpenAI, Anthropic, Google Gemini) or run local models (via e.g., Ollama) so that your browsing data and automation stay on your machine — privacy and control are emphasized throughout. The interface remains familiar to users of... -
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StringZilla
10x faster string search, split, sort, and shuffle for long strings
StringZilla is the Godzilla of string libraries, splitting, sorting, and shuffling large textual datasets. StringZilla uses a heuristic so simple it's almost stupid... but it works. It matches the first few letters of words with hyper-scalar code to achieve memcpy speeds. The implementation fits into a single C 99 header file and uses different SIMD flavors and SWAR on older platforms. The Str is designed to replace long Python str strings and wrap our C-level API. On the other hand, the... -
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Speech Note
Speech Note Linux app. Note taking, reading and translating
...It combines speech-to-text, text-to-speech, and machine translation in a single interface, allowing users to dictate notes, listen back to them, and translate them without ever sending data to the cloud. All processing is done locally, which means audio, text, and translations never leave the device, emphasizing strong privacy guarantees. The application supports multiple STT engines such as Coqui STT (DeepSpeech fork), Vosk, whisper.cpp, Faster Whisper, and april-asr, giving users flexibility in accuracy, speed, and hardware requirements. ... -
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Adafruit Unified Sensor Driver
Common sensor library
Many small embedded systems exist to collect data from sensors, analyze the data, and either take appropriate action or send that sensor data to another system for processing. One of the many challenges of embedded systems design is the fact that parts you used today may be out of production tomorrow, or system requirements may change and you may need to choose a different sensor down the road.
