jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput.
The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory.
The codebase covers a broad surface of capabilities, including real-time video analytics, object detection and tracking, and image segmentation. It also integrates hardware-accelerated decoding and TensorRT-based inference to optimize model execution on embedded platforms.
The project provides a TensorRT inference wrapper and an embedded vision SDK to facilitate the deployment of neural network primitives.
