Search Results for "image processing in java"
Sort By:
Showing 112 open source projects for "image processing in java"
View related business solutions-
Gen AI apps are built with MongoDB AtlasMongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
-
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.
-
1
SageMaker Spark Container
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. -
2
MMDeploy
OpenMMLab Model Deployment Framework
...It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy. -
3
Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level... -
4
Spring Batch
Spring Batch is a framework for writing batch applications using Java
A lightweight, comprehensive batch framework designed to enable the development of robust batch applications vital for the daily operations of enterprise systems. Spring Batch provides reusable functions that are essential in processing large volumes of records, including logging/tracing, transaction management, job processing statistics, job restart, skip, and resource management. It also provides more advanced technical services and features that will enable extremely high-volume and high... -
Get the most trusted enterprise browserDefend against security incidents with Chrome Enterprise. Create customizable controls, manage extensions and set proactive alerts to keep your data and employees protected without slowing down productivity.
-
5
Apache Beam
Unified programming model for Batch and Streaming
Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs... -
6
Benthos
Fancy stream processing made operationally mundane
Benthos is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads. It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck. Delivery guarantees can be a dodgy subject. Benthos processes and... -
7
protoactor-go
Proto Actor - Ultra fast distributed actors for Go, C# and Java/Kotlin
Built on cloud-native technologies. Taking advantage of proven stability and performance. Asynchronous and Distributed by design. High-level abstractions like Actors and Virtual Grains. Capable of millions of messages per second cross-process communication. Write systems that self-heal using supervisor hierarchies. The Actor Model provides a higher level of abstraction for writing concurrent and distributed systems. It alleviates the developer from having to deal with explicit locking and... -
8
Apache Spark
A unified analytics engine for large-scale data processing
...With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. The built-in MLlib library provides scalable machine learning algorithms, while GraphX enables graph computations integrated with data pipelines. Spark supports multiple languages—Scala, Java, Python, R—and connects with many storage systems like HDFS, S3, Cassandra, and streaming platforms like Kafka, making it a versatile choice for big data workloads in analytics, ETL, and data science. -
9
Apache Sedona
Cluster computing framework for processing large-scale geospatial data
...According to our benchmark and third-party research papers, Sedona has 50% less peak memory consumption than other Spark-based geospatial data systems for large-scale in-memory query processing. Sedona offers Scala, Java, Spatial SQL, Python, and R APIs and integrates them into underlying system kernels with care. You can simply create spatial analytics and data mining applications and run them in any cloud environments. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
-
10
Besu Ethereum Client
An enterprise-grade Java-based, Apache 2.0 licensed Ethereum client
...Please also read the wiki for more details on how to submit a pull request (PR). Besu is an Apache 2.0 licensed, MainNet compatible, Ethereum client written in Java. Participation in private networks is typically restricted in some way, so the volume of traffic is much lower than on Mainnet, resulting in lower system requirements. Depending on your environment and network setup, the minimum Java Virtual Machine (JVM) memory requirement for private networks is 4 GB. -
11
Erupt Framework
Pure Java annotation, single class file, rapid development
Pure Java annotation, single class file, rapid development of Admin management background. Does not generate any code, zero front-end code, zero CURD, automatic table creation, annotated API, custom service logic, supports all mainstream databases, supports custom pages, supports multiple data sources, provides more than 20 types of business components, more than a dozen It supports logical deletion, dynamic timing tasks, front-end and back-end separation, etc. Core technologies: Spring... -
12
threeddonut
3D donut. Example of frojasg1.com libraries usage
The application shows a 3D donut, that can be rotated with two sliders in both axis. It is a simple example of what can be done with frojasg1.com platform libraries: - Zoom option for components - Multi language - Dark mode option - Automatic Undo-Redo for text components, with popup menu included - Text Search/Replace window prepared to be used. - Base components for auto-completion windows. - Automatic component relocation after redimensioning a... -
13
KotlinPoet
A Kotlin API for generating .kt source files
KotlinPoet is a Kotlin and Java API for generating .kt source files. Source file generation can be useful when doing things such as annotation processing or interacting with metadata files (e.g., database schemas, protocol formats). By generating code, you eliminate the need to write boilerplate while also keeping a single source of truth for the metadata. -
14
KubeEdge
Kubernetes Native Edge Computing Framework (project under CNCF)
...It consists of a cloud part and an edge part, and provides core infrastructure support for networking, application deployment, and metadata synchronization between the cloud and edge. It also supports MQTT which enables edge devices to access through edge nodes. With KubeEdge it is easy to get and deploy existing complicated machine learning, image recognition, event processing, and other high-level applications to the Edge. With business logic running at the Edge, much larger volumes of data can be secured & processed locally where the data is produced. With data processed at the Edge, the responsiveness is increased dramatically and data privacy is protected. -
15
Apache InLong
Apache InLong - a one-stop integration framework for massive data
Apache InLong is a one-stop integration framework for massive data that provides automatic, secure and reliable data transmission capabilities. InLong supports both batch and stream data processing at the same time, which offers great power to build data analysis, modeling and other real-time applications based on streaming data. InLong (应龙) is a divine beast in Chinese mythology who guides the river into the sea, and it is regarded as a metaphor of the InLong system for reporting data... -
16
MegEngine
Easy-to-use deep learning framework with 3 key features
MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. ... -
17
ElasticJob
Distributed scheduled job framework
ElasticJob is a distributed scheduling solution consisting of two separate projects, ElasticJob-Lite and ElasticJob-Cloud. ElasticJob-Lite is a lightweight, decentralized solution that provides distributed task sharding services. ElasticJob-Cloud uses Mesos to manage and isolate resources. It uses a unified job API for each project. Developers only need code one time and can deploy at will. Support job sharding and high availability in distributed system. Scale out for throughput and... -
18
IM is a toolkit for Digital Imaging. IM is based on 4 concepts: Image Representation, Storage, Processing and Capture. The main goal of the library is to provide a simple API and abstraction of images for scientific applications.
-
19
Emgu CV
Emgu CV is a cross platform .Net wrapper for OpenCV
Emgu CV is a cross platform .Net wrapper to the OpenCV image processing library. Allowing OpenCV functions to be called from .NET compatible languages such as C#, VB, VC++, IronPython etc. The wrapper can be compiled in Mono and run on Windows, Linux, Mac OS X, iPhone, iPad and Android devices. -
20
NOTE THAT THE SOURCE CODE AND ISSUE TRACKER HAVE NOW MOVED TO GITHUB. FIND US AT https://github.com/GateNLP/ GATE (General Architecture for Text Engineering) is an architecture, framework and development environment for developing, evaluating and embedding Human Language Technology. See http://gate.ac.uk for full details.
-
21
libCIGI
C++ Library for the Common Image Generator Interface
libCIGI (library for Common Image Generator Interface) is a lightweight header only library that provides interfaces for communication between CIGI hosts and image generators. Currently versions 3.0, 3.2 and 3.3 are supported as well as support for the *draft* V4.0 CIGI standard. Additional functionality to the base packet interfaces is provided through external classes so that to the packet headers have no further dependencies. -
22
Web data extraction (web data mining, web scraping) tool. It leverages well proved XML and text processing techologies in order to easely extract useful data from arbitrary web pages.
-
23
The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.
-
24
MetalPetal
A GPU accelerated image and video processing framework built on Metal
MetalPetal is an image processing framework based on Metal designed to provide real-time processing for still images and video with easy-to-use programming interfaces. This chapter covers the key concepts of MetalPetal, and will help you to get a better understanding of its design, implementation, performance implications, and best practices. A MTIImage object is a representation of an image to be processed or produced. -
25
SpringAll
Step by step, learn Spring Boot, Spring Boot & Shiro, Spring Batch
SpringAll is a comprehensive learning project that gathers a wide range of Spring, Spring Boot, and Spring Cloud demos in one repository. It is designed for developers who want to deepen their understanding of the Spring ecosystem by exploring concrete, runnable code samples. Each module focuses on a specific technology or integration—covering web applications, ORM frameworks, microservices, caching, messaging, security, distributed systems, and monitoring. The repository emphasizes both...
