# enazoe/yolo-tensorrt

TensorRT8.Support Yolov5n,s,m,l,x .darknet -> tensorrt.  Yolov4  Yolov3 use raw darknet *.weights and *.cfg fils.  If the wrapper is useful to you,please Star it.

Repository: https://github.com/enazoe/yolo-tensorrt
Canonical: https://ross.abutalabs.com/products/yolo-tensorrt
Language: C++
License: MIT
License Family: permissive
Topics: yolov4-tiny, yolov5s, yolov5m, yolov5l, yolov5x, yolov3, yolov3-tiny, darknet, jetson-xavier-nx, jetson, yolov4, yolov5, l4t, weights, yolo-tensorrt
Last push: 2026-04-12T09:10:07+00:00

## Health v2 (maintenance only)
Score: 57/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 77, release rhythm 8, longevity 100
- inputs: {"age_days": 2437, "days_push": 143, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1202, forks 312 (observed 2026-08-28T04:03:58.499006+00:00)

## What it is
A C++ wrapper around NVIDIA TensorRT for running YOLO object detection models (YOLOv3, YOLOv4, YOLOv5) with support for FP32, FP16, and INT8 precision. It converts Darknet weights and PyTorch YOLOv5 models into optimized TensorRT engines for x86 GPUs and Jetson embedded platforms.

## Use cases
- deploy yolo models with tensorrt
- run yolov5 inference on jetson xavier nx
- convert darknet weights to tensorrt engine
- int8 quantized object detection on gpu
- batch inference for yolo models in c++
- fast object detection on embedded nvidia devices

## When to choose
- you need high-performance YOLO inference via TensorRT in C++
- you are deploying on NVIDIA Jetson (L4T) hardware
- you want FP16/INT8 optimized YOLOv3/v4/v5 detection

## When to avoid
- you need a Python-first inference pipeline
- you use YOLO versions beyond v5 or dynamic input sizes
- you want a maintained framework with frequent updates

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, computer-vision, image-processing, gpu-computing
- domain: computer-vision, deep-learning, gpu-computing, embedded-systems
- platform: windows, cpp
- tags: yolo, tensorrt, object-detection, darknet, inference, jetson, fp16, int8-quantization, linux, gpu, nvidia-jetson

## Member repositories
- enazoe/yolo-tensorrt (main) score 57

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:58.499006+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:20:35.591551+00:00, confidence not recorded.
  - readme: https://github.com/enazoe/yolo-tensorrt (fetched 2026-08-28T04:03:58.499006+00:00, sha aedd7a1ded72)
- Data as of 2026-08-30T08:39:29.467469+00:00.