yolov5-5.0

Original codes from tensorrtx. I modified the yololayer and integrated batchedNMSPlugin. A yolov5s.wts is provided for fast demo. How to generate .wts can refer to https://github.com/wang-xinyu/tensorrtx/tree/master/yolov5.

Run with docker

1. Run into docker, assume repo path is /data/YoLov5-TensorRT-NMS

sudo docker run --gpus all -v /data/YoLov5-TensorRT-NMS:/work -it registry.cn-guangzhou.aliyuncs.com/nvidia-images/tensorrt20.03-py3:v3 /bin/bash
cd work
mkdir build
cd build
cmake ..
make
sudo ./yolov5 -s             // serialize model to plan file i.e. 'yolov5s.engine'
sudo ./yolov5 -d  ../samples // deserialize plan file and run inference, the images in samples will be processed.

How to Run, yolov5s as example

1. build and run

mkdir build
cd build
cmake ..
make
sudo ./yolov5 -s             // serialize model to plan file i.e. 'yolov5s.engine'
sudo ./yolov5 -d  ../samples // deserialize plan file and run inference, the images in samples will be processed.

2. check the images generated, as follows. _zidane.jpg and _bus.jpg

3. run Python example, please install Python tensorrt and Pycuda and then

python yolov5_trt.py

More Information

See the readme in tensorrtx home page.

Known issues

None!