| .. | ||
| CMakeLists.txt | ||
| gen_wts.py | ||
| holder.h | ||
| ibnnet.cpp | ||
| ibnnet.h | ||
| InferenceEngine.cpp | ||
| InferenceEngine.h | ||
| layers.cpp | ||
| layers.h | ||
| logging.h | ||
| main.cpp | ||
| README.md | ||
| utils.cpp | ||
| utils.h | ||
IBN-Net
An implementation of IBN-Net, proposed in "Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net", ECCV2018 by Xingang Pan, Ping Luo, Jianping Shi, Xiaoou Tang.
For the Pytorch implementation, you can refer to IBN-Net
Features
- InstanceNorm2d
- bottleneck_ibn
- Resnet50-IBNA
- Resnet50-IBNB
- Multi-thread inference
How to Run
-
- generate .wts
// for ibn-a
python gen_wts.py aa file 'resnet50-ibna.wts' will be generated.
// for ibn-b
python gen_wts.py ba file 'resnet50-ibnb.wts' will be generated.
-
- cmake and make
mkdir build cd build cmake .. make -
- build engine and run classification
// put resnet50-ibna.wts/resnet50-ibnb.wts into tensorrtx/ibnnet
// go to tensorrtx/ibnnet
./ibnnet -s // serialize model to plan file ./ibnnet -d // deserialize plan file and run inference