pytracking

PyTracking

A general python library for visual tracking algorithms.

Running a tracker

The installation script will automatically generate a local configuration file "evaluation/local.py". In case the file was not generated, run evaluation.environment.create_default_local_file() to generate it. Next, set the paths to the datasets you want to use for evaluations. You can also change the path to the networks folder, and the path to the results folder, if you do not want to use the default paths. If all the dependencies have been correctly installed, you are set to run the trackers.

Run the tracker on some dataset sequence
This is done using the run_tracker script.

python run_tracker.py tracker_name parameter_name --dataset dataset --sequence sequence --debug debug --threads threads

Here, the dataset_name is the name of the dataset used for evaluation, e.g. otb. See evaluation.datasets.py for the list of datasets which are supported. The sequence can either be an integer denoting the index of the sequence in the dataset, or the name of the sequence, e.g. 'Soccer'. The debug parameter can be used to control the level of debug visualizations. threads parameter can be used to run on multiple threads.

Take CIA18 as an example.

python run_tracker.py CIA CIA18 --dataset lasot

Visdom

All trackers support Visdom for debug visualizations. To use visdom, start the visdom server from a seperate command line:

visdom

Run the tracker with the debug argument > 0. The debug output from the tracker can be accessed by going to http://localhost:8097 in your browser. Further, you can pause the execution of the tracker, or step through frames using keyboard inputs.