marcoslucianops/DeepStream-Yolo

Health v2 · maintenance only

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2054 stars · 462 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of configuration files, parsers, and conversion utilities for running YOLO-family object detection models on NVIDIA DeepStream SDK. It supports many model variants (YOLOv5 through YOLO26, RT-DETR, PPYOLOE, etc.) via ONNX or Darknet conversion with TensorRT engines and GPU post-processing.

Use cases

• deploy yolo models with nvidia deepstream
• convert yolov8 onnx to tensorrt engine
• run object detection on jetson with deepstream
• int8 calibration for yolo tensorrt
• use custom yolo weights in deepstream pipeline
• real-time object detection on gpu video streams

When to choose

• you need to run YOLO-family detectors inside NVIDIA DeepStream pipelines
• you want TensorRT optimization with INT8 calibration for detection models
• you target Jetson or dGPU hardware for real-time video analytics

When to avoid

• you need a framework-agnostic inference solution without DeepStream
• you run on non-NVIDIA hardware
• you need segmentation or pose models (use the companion DeepStream-Yolo-Seg/Pose repos)

Facets

library · maturity active

machine-learning computer-vision image-processing gpu-computing sdk computer-vision deep-learning machine-learning gpu-computing python cpp nvidia-deepstream yolo tensorrt object-detection onnx int8-calibration darknet ultralytics video-analytics video linux gpu docker

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