Alpha-Refine is the winner of the VOT Real-Time Challenge 2020, which has great ability to predict high-quality masks. In this work, we combine the STARK tracker with Alpha-Refine to test on the VOT2020 benchamark.
After the environment has been installed according to the README.md of STARK, you only need to install a few more packages as shown below.
- Install ninja-build for Precise ROI pooling
sudo apt-get install ninja-build
In case of issues, we refer to https://github.com/vacancy/PreciseRoIPooling.
- Install the Precise ROI pooling
cd ltr/external
git clone https://github.com/vacancy/PreciseRoIPooling.git
cd ../..
- Add the project path to environment variables
export PYTHONPATH=<absolute_path_of_AR>:$PYTHONPATH
- Setup the environment
Create the default environment setting files.
# Environment settings for pytracking. Saved at pytracking/evaluation/local.py
python -c "from pytracking.evaluation.environment import create_default_local_file; create_default_local_file()"
# Environment settings for ltr. Saved at ltr/admin/local.py
python -c "from ltr.admin.environment import create_default_local_file; create_default_local_file()"
You can modify these files to set the paths to datasets, results paths etc.
- Download the pre-trained Alpha-Refine network
Download the network for Alpha-Refine and put it under the ltr/checkpoints/ltr/ARcm_seg/ARcm_coco_seg_only_mask_384 dir.