This repository if for classifying videos/sequences containing actions, and classifying them. This is written in Python 3.
Currently we utilize the KTH dataset, which can be found here: http://www.nada.kth.se/cvap/actions/along with that, for the interest points we utilize the Spatio-Temporal Interest Points as defined by Laptev et al., which can be found here: https://www.di.ens.fr/~laptev/download/stip-2.0-linux.zip
Note: Regarding STIP, to work correctly with the current OpenCV, a workaround has to be made to link the correct libs.
This module uses scikit-learn, which can be installed by either the
pip install -r requirements.txt
or
pip install sklearn
For now, to execute
python3 classify.py
The main dataset working, and preprocessing of the descriptors to form a vocabulary is done by KTH.py
. The classify.py
calls it for accessing the processed dataset.
The KTH.pkl
contains the processed descriptors along with the classifiers and the rest. The sequences.txt
and sequences.pkl
contains the sequences of the actions to be classified.