Shot Type Classification Package
Project description
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
0 Environment Setup (optional)
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
1A Install using Pip
The VHH Shot Boundary Detection package is available on PyPI and can be installed via pip
.
- Update pip and setuptools (tested using pip==20.2.3 and setuptools==50.3.0)
pip install vhh-stc
Alternatively, you can also build the package from source.
1B Install by building from Source
Checkout vhh_stc repository to a specified folder:
- git clone https://github.com/dahe-cvl/vhh_stc
Install the stc package and all dependencies:
- Update
pip
andsetuptools
(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.
2 Install PyTorch
Install a Version of PyTorch depending on your setup. Consult the PyTorch website for detailed instructions.
3 Setup environment variables (optional)
- 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/
4 Run demo script (optional)
- change to root directory of the repository
- python Demo/vhh_stc_run_on_single_video.py
Release Generation
- Create and checkout release branch: (e.g. v1.1.0):
git checkout -b v1.1.0
- Update version number in setup.py
- Update Sphinx documentation and release version
- Make sure that
pip
andsetuptools
are up to date - Install
wheel
andtwine
- Build Source Archive and Built Distribution using
python setup.py sdist bdist_wheel
- Upload package to PyPI using
twine upload dist/*
Project details
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