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Linaom1214/TensorRT-For-YOLO-Series
Pythontensorrt for yolo series (YOLOv11,YOLOv10,YOLOv9,YOLOv8,YOLOv7,YOLOv6,YOLOX,YOLOv5), nms plugin support
tensorrtyolov7yolov6yoloxyolov3yolov5yolov8yolov10yolov9yolo11yoloyolo12
Métricas clave
Crecimiento de estrellas
Estrellas
1.2k
Forks
191
Crecimiento semanal
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Issues
50
5001k
abr 2022dic 2022sept 2023may 2024feb 2025oct 2025jul 2026
ArtefactosPyPI
pip install tensorrt-for-yolo-seriesREADME
YOLO Series TensorRT Python/C++
Support
YOLOv11, YOLOV12、YOLOv10、YOLOv9、YOLOv8、YOLOv7、YOLOv6、 YOLOX、 YOLOV5、YOLOv3
- YOLOv12
- YOLOv11
- YOLOv10
- YOLOv9
- YOLOv8
- YOLOv7
- YOLOv6
- YOLOX
- YOLOv5
- YOLOv3
Update
- 2025.3.14 Support YOLOv12
- 2024.11.24 Support YOLOv11, fix the bug causing YOLOv8 accuracy misalignment
- 2024.6.16 Support YOLOv9, YOLOv10, changing the TensorRT version to 10.0
- 2023.8.15 Support cuda-python
- 2023.5.12 Update
- 2023.1.7 support YOLOv8
- 2022.11.29 fix some bug thanks @JiaPai12138
- 2022.8.13 rename reop、 public new version、 C++ for end2end
- 2022.8.11 nms plugin support ==> Now you can set --end2end flag while use
export.pyget a engine file - 2022.7.8 support YOLOv7
- 2022.7.3 support TRT int8 post-training quantization
Prepare TRT Env
Install via Python
pip install tensorrt
pip install cuda-python
Install via C++
YOLO12
Export ONNX
pip install ultralytics
from ultralytics import YOLO
model = YOLO("yolo12n.pt")
model.export(format='onnx')
Generate TRT File
python export.py -o yolo112n.onnx -e yolo12n.trt --end2end --v8 -p fp32
Inference
python trt.py -e yolo12n.trt -i src/1.jpg -o yolo12-1.jpg --end2end
YOLO11
Export ONNX
pip install ultralytics
from ultralytics import YOLO
model = YOLO("yolo11n.pt")
model.export(format='onnx')
Generate TRT File
python export.py -o yolo11n.onnx -e yolov11n.trt --end2end --v8 -p fp32
Inference
python trt.py -e yolov11n.trt -i src/1.jpg -o yolov11-1.jpg --end2end
YOLOv10
Generate TRT File
python export.py -o yolov10n.onnx -e yolov10.trt --end2end --v10 -p fp32
Inference
python trt.py -e yolov10.trt -i src/1.jpg -o yolov10-1.jpg --end2end
YOLOv9
Generate TRT File
python export.py -o yolov9-c.onnx -e yolov9.trt --end2end --v8 -p fp32
Inference
python trt.py -e yolov9.trt -i src/1.jpg -o yolov9-1.jpg --end2end
Python Demo
Expand
YOLOv8
Install && Download Weights
pip install ultralytics
Export ONNX
from ultralytics import YOLO
model = YOLO("yolov8s.pt")
model.fuse()
model.info(verbose=False) # Print model information
model.export(format='onnx') # TODO:
Generate TRT File
python export.py -o yolov8n.onnx -e yolov8n.trt --end2end --v8 --fp32
Inference
python trt.py -e yolov8n.trt -i src/1.jpg -o yolov8n-1.jpg --end2end
YOLOv5
!git clone https://github.com/ultralytics/yolov5.git
!wget https://github.com/ultralytics/yolov5/releases/download/v6.1/yolov5n.pt
!python yolov5/export.py --weights yolov5n.pt --include onnx --simplify --inplace
include NMS Plugin
!python export.py -o yolov5n.onnx -e yolov5n.trt --end2end
!python trt.py -e yolov5n.trt -i src/1.jpg -o yolov5n-1.jpg --end2end
exclude NMS Plugin
!python export.py -o yolov5n.onnx -e yolov5n.trt
!python trt.py -e yolov5n.trt -i src/1.jpg -o yolov5n-1.jpg
YOLOX
!git clone https://github.com/Megvii-BaseDetection/YOLOX.git
!wget https://github.com/Megvii-BaseDetection/YOLOX/releases/download/0.1.1rc0/yolox_s.pth
!cd YOLOX && pip3 install -v -e . --user
!cd YOLOX && python tools/export_onnx.py --output-name ../yolox_s.onnx -n yolox-s -c ../yolox_s.pth --decode_in_inference
include NMS Plugin
!python export.py -o yolox_s.onnx -e yolox_s.trt --end2end
!python trt.py -e yolox_s.trt -i src/1.jpg -o yolox-1.jpg --end2end
exclude NMS Plugin
!python export.py -o yolox_s.onnx -e yolox_s.trt
!python trt.py -e yolox_s.trt -i src/1.jpg -o yolox-1.jpg
YOLOv6
!wget https://github.com/meituan/YOLOv6/releases/download/0.1.0/yolov6s.onnx
include NMS Plugin
!python export.py -o yolov6s.onnx -e yolov6s.trt --end2end
!python trt.py -e yolov6s.trt -i src/1.jpg -o yolov6s-1.jpg --end2end
exclude NMS Plugin
!python export.py -o yolov6s.onnx -e yolov6s.trt
!python trt.py -e yolov6s.trt -i src/1.jpg -o yolov6s-1.jpg
YOLOv7
!git clone https://github.com/WongKinYiu/yolov7.git
!wget https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-tiny.pt
!pip install -r yolov7/requirements.txt
!python yolov7/export.py --weights yolov7-tiny.pt --grid --simplify
include NMS Plugin
!python export.py -o yolov7-tiny.onnx -e yolov7-tiny.trt --end2end
!python trt.py -e yolov7-tiny.trt -i src/1.jpg -o yolov7-tiny-1.jpg --end2end
exclude NMS Plugin
!python export.py -o yolov7-tiny.onnx -e yolov7-tiny-norm.trt
!python trt.py -e yolov7-tiny-norm.trt -i src/1.jpg -o yolov7-tiny-norm-1.jpg
C++ Demo
support NMS plugin show in C++ Demo
Citing
If you use this repo in your publication, please cite it by using the following BibTeX entry.
@Misc{yolotrt2022,
author = {Jian Lin},
title = {YOLOTRT: tensorrt for yolo series},
howpublished = {\url{[https://github.com/Linaom1214/TensorRT-For-YOLO-Series]}},
year = {2022}
}
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