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Deep Upstream : Hardware Agnostic GStreamer Analytics | GStreamer Conference 2023

With the growing power of machine-learning, the time has come for GStreamer to support complex, platform-independent analytic pipelines for tracking, super-resolution, noise filtering, speech recognition and more general analysis of timed data streams. We discuss a new flexible and efficient design to address these problems, without vendor or framework lock-in, which can easily interoperate with existing downstream approaches. To achieve this goal, we have designed new framework-independent graph-based infrastructure using the existing GstMeta structure to store complex metadata and their relationships. We have also generalized the existing ONNX-based object detector to easily support many new inference models targeting a variety of hardware backends, and have built a new OSD to visualize the generated analytics metadata. Care has been taken to ensure efficient pipelines with support for batch processing and zero-copy. Finally, we have built a bridge to non-GStreamer land with a new cloud metadata sink that can send analytics results to cloud servers. We will also present a demo at the end of the talk showcasing a complex two-phase video analysis pipeline. Presented by Daniel Morin. #GStreamer #DataAnalytics #MachineLearning