A general python framework for training and running visual object trackers, based on PyTorch.
News: Upgraded to latest version of PyTorch (v1.x).
Official implementation of the ATOM tracker (CVPR 2019), including complete training code and trained models.
Libraries for implementing and evaluating visual trackers. Including:
- All common tracking datasets.
- General building blocks, including optimization, feature extraction and utilities for correlation filter tracking.
General framework for training networks for visual tracking.
- All common training datasets for visual tracking.
- Functions for data sampling, processing etc.
- Integration of ATOM models
- More to come ... ;)
git clone https://github.com/visionml/pytracking.gitIn the repository directory, run the commands:
git submodule update --init Run the installation script to install all the dependencies. You need to provide the conda install path (e.g. ~/anaconda3) and the name for the created conda environment (here pytracking).
bash install.sh conda_install_path pytrackingThis script will also download the default networks and set-up the environment.
Note: The install script has been tested on an Ubuntu 18.04 system. In case of issues, check the detailed installation instructions.
Activate the conda environment and run the script pytracking/run_webcam.py to run ATOM using the webcam input.
conda activate pytracking
cd pytracking
python run_webcam.py atom default