#stream processing

NNStreamer facilitates the integration of neural network models into GStreamer applications. It provides developers with robust plugins to manage neural network pipelines and filters efficiently. The project supports multi-modal intelligence and composite models, enabling multiple neural networks within a single stream. Compatible with platforms such as Tizen, Ubuntu, Android, and macOS, NNStreamer also supports hardware acceleration with Movidius-X, Edge-TPU, and Qualcomm SNPE, enhancing deployment and execution of AI systems.

Project Flogo provides a lightweight, open-source ecosystem using Golang for developing event-driven applications. By leveraging triggers and actions, it enhances event processing capabilities and supports features like application integration, stream processing, and TensorFlow-based machine learning. The ecosystem is designed for versatile deployment on serverless platforms, containers, and IoT edge environments. Its unified core ensures the reuse of event constructs, offering tools suitable for developers with varying coding preferences. Explore Project Flogo for efficient data pre-processing and real-time decision-making in various contexts.

This robust open-source stream processor seamlessly integrates into pipelines, offering reliable performance and flexibility. Supporting diverse data connectors and ensuring at-least-once delivery even during failures, it's easily deployable in various environments. The tool is compatible with AWS, Azure, GCP, and more, and supports advanced mapping and monitoring capabilities. Its open-source nature encourages continuous updates and customizable plugin development.