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tensorrt for yolo series (YOLOv11,YOLOv10,YOLOv9,YOLOv8,YOLOv7,YOLOv6,YOLOX,YOLOv5), nms plugin support
| Date | Stars |
|---|---|
| 2026-07-24 | 1161 |
| 2026-07-25 | 1161 |
| 2026-07-28 | 1161 |
| 2026-07-30 | 1162 |
| 2026-08-06 | 1161 |
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# YOLO Series TensorRT Python/C++
## Support
[YOLOv11, YOLOV12](https://docs.ultralytics.com/)、[YOLOv10](https://github.com/THU-MIG/yolov10)、[YOLOv9](https://github.com/WongKinYiu/yolov9)、[YOLOv8](https://v8docs.ultralytics.com/)、[YOLOv7](https://github.com/WongKinYiu/yolov7)、[YOLOv6](https://github.com/meituan/YOLOv6)、 [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX)、 [YOLOV5](https://github.com/ultralytics/yolov5)、[YOLOv3](https://github.com/ultralytics/yolov3)
- [x] YOLOv12
- [x] YOLOv11
- [x] YOLOv10
- [x] YOLOv9
- [x] YOLOv8
- [x] YOLOv7
- [x] YOLOv6
- [x] YOLOX
- [x] YOLOv5
- [x] 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](https://github.com/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.py` get 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++`
[By Docker](https://github.com/NVIDIA/TensorRT/blob/main/docker/ubuntu-20.04.Dockerfile)
## YOLO12
### Export ONNX
```shell
pip install ultralytics
```
```Python
from ultralytics import YOLO
model = YOLO("yolo12n.pt")
model.export(format='onnx')
```
### Generate TRT File
```shell
python export.py -o yolo112n.onnx -e yolo12n.trt --end2end --v8 -p fp32
```
### Inference
```shell
python trt.py -e yolo12n.trt -i src/1.jpg -o yolo12-1.jpg --end2end
```
## YOLO11
### Export ONNX
```shell
pip install ultralytics
```
```Python
from ultralytics import YOLO
model = YOLO("yolo11n.pt")
model.export(format='onnx')
```
### Generate TRT File
```shell
python export.py -o yolo11n.onnx -e yolov11n.trt --end2end --v8 -p fp32
```
### Inference
```shell
python trt.py -e yolov11n.trt -i src/1.jpg -o yolov11-1.jpg --end2end
```
## YOLOv10
### Generate TRT File
```shell
python export.py -o yolov10n.onnx -e yolov10.trt --end2end --v10 -p fp32
```
### Inference
```shell
python trt.py -e yolov10.trt -i src/1.jpg -o yolov10-1.jpg --end2end
```
## YOLOv9
### Generate TRT File
```shell
python export.py -o yolov9-c.onnx -e yolov9.trt --end2end --v8 -p fp32
```
### Inference
```shell
python trt.py -e yolov9.trt -i src/1.jpg -o yolov9-1.jpg --end2end
```
## Python Demo
<details><summary> <b>Expand</b> </summary>
1. [YOLOv5](##YOLOv5)
2. [YOLOx](##YOLOX)
3. [YOLOv6](##YOLOV6)
4. [YOLOv7](##YOLOv7)
5. [YOLOv8](##YOLOv8)
## YOLOv8
### Install && Download [Weights](https://github.com/ultralytics/assets/)
```shell
pip install ultralytics
```
### Export ONNX
```Python
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
```shell
python export.py -o yolov8n.onnx -e yolov8n.trt --end2end --v8 --fp32
```
### Inference
```shell
python trt.py -e yolov8n.trt -i src/1.jpg -o yolov8n-1.jpg --end2end
```
## YOLOv5
```python
!git clone https://github.com/ultralytics/yolov5.git
```
```python
!wget https://github.com/ultralytics/yolov5/releases/download/v6.1/yolov5n.pt
```
```python
!python yolov5/export.py --weights yolov5n.pt --include onnx --simplify --inplace
```
### include NMS Plugin
```python
!python export.py -o yolov5n.onnx -e yolov5n.trt --end2end
```
```python
!python trt.py -e yolov5n.trt -i src/1.jpg -o yolov5n-1.jpg --end2end
```
### exclude NMS Plugin
```python
!python export.py -o yolov5n.onnx -e yExcerpt of 6,651 characters
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Jian Lin · Northwestern Polytechnical University
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:f272739c61a3d5d3, topic:tensorrt
matched fp:f272739c61a3d5d3, topic:yolo