Run RF-DETR in NVIDIA DeepStream on Jetson

Erik Kokalj's blog post from July 22, 2026, details the process of running RF-DETR within NVIDIA DeepStream on a Jetson Orin NX, explaining both DeepStream and RF-DETR functionalities. DeepStream is described as NVIDIA's video analytics SDK that uses GStreamer to provide hardware-accelerated video processing pipelines, while RF-DETR is a DETR-family detector developed by Roboflow. The post discusses building a TensorRT engine, creating a parser for model output interpretation, and running it on RTSP streams with customized box colors for different classes. The RF-DETR model is used to detect objects by transforming raw data into structured detection results, which involves converting ONNX files into TensorRT engines and configuring DeepStream with a parser function to interpret detection results. The author emphasizes the importance of correctly setting preprocessing parameters and describes how to implement custom per-class color coding using Python, enhancing the visualization of detected objects. Performance metrics indicate that a Jetson Orin NX can efficiently handle a four-stream setup at 30 fps per stream, leveraging the RF-DETR Nano model with FP16 precision on a 384x384 input resolution.

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