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Plugin package: Shot Type Classification

This package includes all methods to classify a given shot/or image sequence in one of the categories Extreme Long Shot (ELS), Long Shot (LS), Medium Shot (MS) or Close-Up Shot (CU).

Package Description

PDF format: vhh_stc_pdf

HTML format (only usable if repository is available in local storage): vhh_stc_html

Quick Setup

This package includes a setup.py script and a requirements.txt file which are needed to install this package for custom applications. The following instructions have to be done to used this library in your own application:

Requirements:

  • Ubuntu 18.04 LTS
  • CUDA 10.1 + cuDNN
  • python version 3.6.x

Create a virtual environment:

  • create a folder to a specified path (e.g. /xxx/vhh_stc/)
  • python3 -m venv /xxx/vhh_stc/

Activate the environment:

  • source /xxx/vhh_stc/bin/activate

Checkout vhh_stc repository to a specified folder:

Install the stc package and all dependencies:

  • Update pip and setuptools (tested using pip==20.2.3 and setuptools==50.3.0)
  • Install the Wheel package: pip install wheel
  • change to the root directory of the repository (includes setup.py)
  • python setup.py bdist_wheel
  • The aforementioned command should create a /dist directory containing a wheel. Install the package using python -m pip install dist/xxx.whl

NOTE: You can check the success of the installation by using the commend pip list. This command should give you a list with all installed python packages and it should include vhh-stc.

Install PyTorch :

Install a Version of PyTorch depending on your setup. Consult the PyTorch website for detailed instructions.

Setup environment variables:

  • source /data/dhelm/python_virtenv/vhh_sbd_env/bin/activate
  • export CUDA_VISIBLE_DEVICES=1
  • export PYTHONPATH=$PYTHONPATH:/XXX/vhh_stc/:/XXX/vhh_stc/Develop/:/XXX/vhh_stc/Demo/

Run demo script

  • change to root directory of the repository
  • python Demo/vhh_stc_run_on_single_video.py