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NVIDIA DeepStream

NVIDIA's SDK for analyzing dozens of video streams in real time on a GPU.

DeepStream assembles video analytics pipelines as GStreamer graphs where every stage stays on the GPU: NVDEC hardware decoding, multi-stream batching, TensorRT or Triton inference, object tracking, on-screen display and metadata publishing to Kafka, MQTT or AMQP. The same pipeline, written in C++ or Python, runs on a Jetson at the edge or on a data-center GPU, with primary and secondary inference to detect and then classify. It's our choice when several cameras have to be analyzed continuously on site, without needless CPU copies.

[ Why NVIDIA DeepStream ]

What NVIDIA DeepStream brings to your project.

Typical use cases: People and vehicle counting, industrial site security, in-line quality control, retail analytics.

  1. 01

    Zero-copy GStreamer pipeline: NVDEC decoding, inference, tracking and encoding on the GPU.

  2. 02

    nvstreammux multi-stream batching: dozens of RTSP cameras on a single card.

  3. 03

    Built-in trackers (NvDCF, NvSORT, NvDeepSORT) and cascaded detect-then-classify inference.

  4. 04

    Metadata published to Kafka, MQTT, AMQP or Azure IoT through nvmsgbroker.

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