History

BaofengZan 8bdbb47dfa 从wts文件中读取anhor信息，并传入yololayer plugin (#215 ) * 修改图片地址为URL * get Anchor values from wts * get anchor values form wts * get anchor values from wts * get anchor values from wts * 1 using space 2 release heap mem * 1 Using 4 space 2 Delete Chinese comment 3 Load all variables 4 Release heap mem * 1 Using 4 space 2 Delete Chinese comment 3 Load all variables 4 Release heap mem * 1. 函数模块化 2. 格式化代码 3. 同步为最新的yolov5代码		2020-11-06 23:27:30 +08:00
..
CMakeLists.txt	yolov5 hswish plugin replaced by x*hsigmoid	2020-11-06 22:54:15 +08:00
common.hpp	从wts文件中读取anhor信息，并传入yololayer plugin (#215 )	2020-11-06 23:27:30 +08:00
gen_wts.py	update yolov5 genwts	2020-11-06 21:35:02 +08:00
logging.h	implement yolov5s	2020-06-22 13:48:17 +08:00
README.md	fix register plugin and cmp	2020-11-06 22:24:28 +08:00
utils.h	implement yolov5s	2020-06-22 13:48:17 +08:00
yololayer.cu	从wts文件中读取anhor信息，并传入yololayer plugin (#215 )	2020-11-06 23:27:30 +08:00
yololayer.h	从wts文件中读取anhor信息，并传入yololayer plugin (#215 )	2020-11-06 23:27:30 +08:00
yolov5_trt.py	bug fix	2020-11-06 23:26:00 +08:00
yolov5.cpp	从wts文件中读取anhor信息，并传入yololayer plugin (#215 )	2020-11-06 23:27:30 +08:00

README.md

yolov5

The Pytorch implementation is ultralytics/yolov5.

Currently, we support yolov5 v1.0(yolov5s only), v2.0 and v3.0.

For yolov5 v3.0, please visit yolov5 release v3.0, and use the latest commit of this repo.
For yolov5 v2.0, please visit yolov5 release v2.0, and checkout commit '7cd092d' of this repo.
For yolov5 v1.0, please visit yolov5 release v1.0, and checkout commit '0504551' of this repo.

Config

Choose the model s/m/l/x by NET macro in yolov5.cpp
Input shape defined in yololayer.h
Number of classes defined in yololayer.h
FP16/FP32 can be selected by the macro in yolov5.cpp
GPU id can be selected by the macro in yolov5.cpp
NMS thresh in yolov5.cpp
BBox confidence thresh in yolov5.cpp
Batch size in yolov5.cpp

How to Run, yolov5s as example

1. generate yolov5s.wts from pytorch with yolov5s.pt

git clone https://github.com/wang-xinyu/tensorrtx.git
git clone https://github.com/ultralytics/yolov5.git
// download its weights 'yolov5s.pt'
// copy tensorrtx/yolov5/gen_wts.py into ultralytics/yolov5
// ensure the file name is yolov5s.pt and yolov5s.wts in gen_wts.py
// go to ultralytics/yolov5
python gen_wts.py
// a file 'yolov5s.wts' will be generated.

2. build tensorrtx/yolov5 and run

// put yolov5s.wts into tensorrtx/yolov5
// go to tensorrtx/yolov5
// ensure the macro NET in yolov5.cpp is s
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.

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

4. optional, load and run the tensorrt model in python

// install python-tensorrt, pycuda, etc.
// ensure the yolov5s.engine and libmyplugins.so have been built
python yolov5_trt.py

More Information

See the readme in home page.