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Commit 6a16491f authored by Petteri Laitinen's avatar Petteri Laitinen
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Readme updated, and some unnecessary files removed

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......@@ -5,15 +5,15 @@ before_script:
- pip install -r requirements.txt
stages:
- Pelkn luokan ajo
- Pelkan luokan ajo
- Testi
kokeilutesti:
stage: Pelkn luokan ajo
muodollisuustesti:
stage: Pelkan luokan ajo
script:
- python bayesian_adapted_gmm_for_background_extraction.py
laajatesti:
toimivuustesti:
stage: Testi
script:
- python test.py
\ No newline at end of file
This repo tries to develop an easy version of background elimination.
This repository contains a basic applied version of background elimination to a video.
It was developed in Python, using Visual Studio.
### General thoughts
My ambition was to code a version of the background elimination algorithm that takes into account the
Bayesian prior probability of background in the video frame. This was a bit more cumbersome than I thought,
so I ended up setting up the scale. Today (April 2020), the solution is naive and works, but prior probability is not yet implemented!
### Key files:
* bayesian_adapted_gmm_for_background_extraction.py
* contains class for background extraction
* this is the main development area
* you can (after importing the module as bayes!) create a subtractor by MySubtractor=bayes.BackgroundSubtractorBayes(priorProbability, windowLength, NumberOfGaussians)_
* you can apply the subtractor to an OpenCV frame by calling for method _apply(frame,IntegerIndex)_
* koeajo.py
* applies the class on a video in the same folder
* test.py
* test file for gitlab's CI/CD purpose
* gitlab-ci.yml
* defines the CI test in gitlab
* README.md
* this file
* test_video_1.MP4
* a video for testing purposes
* test_video_1b.wmv
* same video in another format for testing purposes
* test_video_2.MP4
* another video for testing purposes
* bayesian_adapted_gmm_for_background_extraction.sln
* Visual Studio solution "wrapper"
* bayesian_adatped_gmm_for_background_extraction.pyproj
* File for Visual Studio to know it is a Python project
We test it with a short video.
# Current status (23 april 2020)
Only one python code file (bayesian_adapted_gmm_for_background_extraction.py) including classes and main program.
It should be split.
The CI test belt is built so that the python code file is run.
Once the code is split into several files, also the tests should be splitted.
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