Introduction

Yolov13 model supports TensorRT-8.

Detection training code link

Environment

• cuda 11.6
• cudnn 8.9.1.23
• tensorrt 8.6.1.6
• opencv 4.8.0
• ultralytics 8.3.63

Support

• YOLOV13-det support FP32/FP16/INT8 and C++ API

Config

• Choose the YOLOV13 sub-model n/s/l/x from command line arguments.
• Other configs please check src/config.h

Build and Run (Detection)

1. generate .wts from pytorch with .pt, or download .wts from model zoo

# Download ultralytics
wget https://github.com/iMoonLab/yolov13/releases/tag/yolov13 -O ultralytics-8.3.63.zip
# Unzip ultralytics
unzip ultralytics-8.3.63.zip
cd ultralytics-8.3.63
# Training your ownself models
to download other models, replace 'yolov13n.pt' with 'yolov13s.pt', 'yolov13l.pt', or 'yolov13x.pt'
# Generate .wts
cp [PATH-TO-TENSORRTX]/yolov13/gen_wts.py .
python gen_wts.py -w yolov13n.pt -t detect -o yolov13n.wts 
# A file 'yolov13n.wts' will be generated.

2. build tensorrtx/yolov13 and run

cd [PATH-TO-TENSORRTX]/yolov13
mkdir build
cd build
cmake ..
make

Detection

cp [PATH-TO-ultralytics]/yolov13n.wts .
# Build and serialize TensorRT engine
./yolov13-det -s yolov13n.wts yolo13n.engine [n/s/l/x]
# Run inference
./yolov13-det -d yolo13n.engine ../images [c/g]
# results saved in build directory

INT8 Quantization

========================================= 个人3050Ti 失败 =====================================================================

1. Prepare calibration images, you can randomly select 1000s images from your train set. For coco, you can also download my calibration images coco_calib from GoogleDrive or BaiduPan pwd: a9wh
2. unzip it in yolo11/build
3. set the macro USE_INT8 in src/config.h and make again
4. serialize the model and test

....... but I meet a mistake when I try to use the int8 ...... activation_8(47): error: identifier "inff" is undefined

1 error detected in the compilation of "activation_8".

[06/28/2025-10:42:42] [E] [TRT] 1: Unexpected exception NVRTC error: NVRTC_ERROR_COMPILATION Build engine successfully! Assertion failed: serialized_engine, file E:\tensorrtx-master\yolov13\yolov13_det.cpp, line 23

========================================= 个人4060成功 =====================================================================

input->['images-2/img_17.jpg'], time->106.42ms, saving into output/ input->['images-2/4.jpg'], time->4.15ms, saving into output/ input->['images-2/1.jpg'], time->4.89ms, saving into output/ input->['images-2/img_52.jpg'], time->4.11ms, saving into output/ input->['images-2/bus.jpg'], time->4.14ms, saving into output/ input->['images-2/zidane.jpg'], time->4.77ms, saving into output/ input->['images-2/2.jpg'], time->4.13ms, saving into output/ input->['images-2/3.jpg'], time->4.75ms, saving into output/

More Information

See the readme in home page.