This code has been tested on windows 10, Python 3.7.9, Pytorch 1.7.0, CUDA 10.0. Please install related libraries before running this code:
pip install -r requirements.txt
Download the pretrained model and put them into tools/snapshot
directory.
From BaiduYun:
- SiamMSS extract code: k9vh
- our_train_baseline extract code: gcvw
- baseline
If you want to test the tracker on a new dataset, please refer to pysot-toolkit to set test_dataset.
The tracking result can be download from BaiduYun (extract code: 50fq) for comparision.
python testTracker.py \
--config ../experiments/siamsmm_googlenet/config.yaml \
--dataset LSOTB \ # dataset_name
--snapshot snapshot/siamsmm.pth # tracker_name
The testing result will be saved in the results/dataset_name/tracker_name
directory.
Download the datasets:
Note: training_dataset/dataset_name/readme.md
has listed detailed operations about how to generate training datasets.
Download pretrained backbones from link and put them into pretrained_models
directory.
To train the SiamSMM model, run train.py
with the desired configs:
cd tools
python train.py
The code is implemented based on pysot and SiamGAT. We would like to express our sincere thanks to the contributors.