NVIDIA DeepStream offers a robust platform for multi-stream video analytics, integrating hardware acceleration and streamlined processing through GStreamer. However, limitations arise with standard detection models, particularly in scenarios requiring custom post-processing or real-time model swapping. This article discusses developing a custom GStreamer plugin using Python, enabling users to leverage an existing PyTorch inference stack without reconfiguration. By correctly writing to DeepStream’s metadata structure, the plugin facilitates seamless integration with downstream elements, allowing for effective detection metadata handling while maintaining throughput. Key insights include the shared data contract within GStreamer and the constraints imposed by DeepStream's architecture regarding metadata object instantiation.
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Creating a Custom GStreamer Plugin for Enhanced NVIDIA DeepStream Performance
Towards Data Science· David Redó Nieto· Saturday, June 20, 2026
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EU's Tech Chief Henna Virkkunen Discusses AI Regulation and Technological Sovereignty
Henna Virkkunen, the European Union's top technology official and Executive Vice President, engaged with Bloomberg's Tom Mackenzie during the VivaTech event in Paris to explore crucial topics including EU AI regulation, the risks associated with cybersecurity, and the importance of Europe's technological sovereignty. The discussion emphasized the need to minimize dependence on non-European technology suppliers in essential sectors, highlighting strategic initiatives for enhancing local capabilities in technology.