In this work, we evaluated the authenticity of drone in real time scenario using computer vision based deep tracker.
More information about this work is in this file
conda install pytorch torchvision -c pytorch
pip install opencv-python imutils pyyaml yacs tqdm colorama matplotlib cython tensorboardX
os.environ['KMP_DUPLICATE_LIB_OK']='True'
python drone_tracking.py --config experiments/siamrpn_alex_dwxcorr_otb/config.yaml --snapshot experiments/siamrpn_alex_dwxcorr_otb/model.pth
--config flag is for network configuration path
--snapshot flag is for network learned weights
Also, we utilized the code from pysot for SiamRPN. For, more information on SiamRPN, kindly refer to the below work.
@INPROCEEDINGS{8579033,
author={Li, Bo and Yan, Junjie and Wu, Wei and Zhu, Zheng and Hu, Xiaolin},
booktitle={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
title={High Performance Visual Tracking with Siamese Region Proposal Network},
year={2018},
pages={8971-8980},
doi={10.1109/CVPR.2018.00935}}