yequanpara/siammaskcpp

C++ Implementation of SiamMask

SiamMaskCpp

• C++ Implementation of SiamMask
• Efficient network output post-processing using OpenCV's GPU matrix operations instead of numpy
• Faster than original implementation (speed increased from 22fps to 40fps when tested with a single NVIDIA GeForce GTX 1070)

Requirements

• OpenCV >= 3.4.0
• pytorch >= 1.3.0
• dlib >= 19.13

Convert a SiamMask model to Torch scripts

You can use the models (with the refine module) trained with the original repository foolwood/SiamMask for inference in C++. Just Follow the instruction in jiwoong-choi/SiamMask to convert your own models to Torch script files.

Download pretrained Torch scripts

Or you can download pretrained Torch scripts. These files are converted from the pretrained models (SiamMask_DAVIS.pth and SiamMask_VOT.pth) in the original repository.

git clone --recurse-submodules https://github.com/nearthlab/SiamMaskCpp
cd SiamMaskCpp
mkdir models
cd models
wget https://github.com/nearthlab/SiamMaskCpp/releases/download/v1.0/SiamMask_DAVIS.tar.gz
wget https://github.com/nearthlab/SiamMaskCpp/releases/download/v1.0/SiamMask_VOT.tar.gz
tar -xvzf SiamMask_DAVIS.tar.gz
tar -xvzf SiamMask_VOT.tar.gz

How to build demo

cd SiamMaskCpp
mkdir build
cd build
cmake -DCMAKE_PREFIX_PATH=/path/to/python3.x/site-packages/torch ..
make

How to run demo

cd SiamMaskCpp/build
./demo -c ../config_davis.cfg -m ../models/SiamMask_DAVIS ../tennis
./demo -c ../config_vot.cfg -m ../models/SiamMask_VOT ../tennis