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A simple Python package used by me and a friend at the university in the course 'Advanced Image, Video and Motion Analysis'

Project description

ZAOWR Package


This is a ZAOWR (Zaawansowana Analiza Obrazu, Wideo i Ruchu, eng. Advanced Image, Video, and Motion Analysis) Python package used by me and a friend at the university.

PyPI link to the package: MAIN PyPI, TEST PyPI.



Table of contents

  1. Windows tutorial

  2. Installing the package on Linux using pip

  3. Removing the package on Linux using pip

  4. Creating virtual environment and installing the package

  5. Testing the installation

  6. Automation: building and uploading with Makefile - DEV Tutorial

  7. Building package - DEV Tutorial based on official DOCS

  8. TODO for tracking issues / backlog / progress

  9. Code requirements

  10. Sources



Windows tutorial

The Windows tutorial can be found here



Installing the package on Linux using pip

  1. PyPI MAIN

    python3 -m pip install --upgrade zaowr-polsl-kisiel
    

  2. TestPyPI

    python3 -m pip install --index-url https://test.pypi.org/simple/ --upgrade zaowr-polsl-kisiel
    


Removing the package on Linux using pip


python3 -m pip uninstall zaowr-polsl-kisiel


Creating virtual environment and installing the package


[!NOTE]

Complete instructions on managing Python virtual environments

can be found here.


  1. Create project directory and open it (directory where you will create your files and where the venv will be created). Below is an example of how to do it through Bash - you can also do it through file explorer

    testDir=/home/user/test
    
    mkdir -p $testDir
    
    cd $testDir
    

  2. Create venv

    python -m venv ENV_NAME
    

  3. [!NOTE]

    ENV_NAME is the name of your venv, so you can change it however you like


  4. Activate the venv (while in the project directory)

    source ENV_NAME/bin/activate
    

    or

    . ENV_NAME/bin/activate
    

  5. Install the package from PyPI

    python3 -m pip install --upgrade zaowr-polsl-kisiel
    

  6. (ADDITIONAL COMMAND) If you want to deactivate the currently active venv

    deactivate
    

  7. (ADDITIONAL COMMAND) To reactivate the venv, navigate to the path where you created the venv and source it again (command shown above in section number 3)


Testing the installation


  • Activate the venv (while in the project directory) - Skip this step if you are not using a virtual environment

    source ENV_NAME/bin/activate
    

    or

    . ENV_NAME/bin/activate
    

  • Launch python

    python3
    

  • Import the package

    from zaowr_polsl_kisiel import load_calibration
    

  • Locate the file with calibration params or create new file with structure shown below

    {
        "mse": 5.984166144997382,
        "rms": 0.5399844606283781,
        "objPoints": [
            [1272.011234078766, 0.0, 1058.4537673810164],
            [0.0, 1266.8726860857762, 617.7592332273604],
            [0.0, 0.0, 1.0]
        ],
        "imgPoints": [
            [1272.011234078766, 0.0, 1058.4537673810164],
            [0.0, 1266.8726860857762, 617.7592332273604],
            [0.0, 0.0, 1.0]
        ],
        "cameraMatrix": [
            [1272.011234078766, 0.0, 1058.4537673810164],
            [0.0, 1266.8726860857762, 617.7592332273604],
            [0.0, 0.0, 1.0]
        ],
        "distortionCoefficients": [
            [-0.39935647747478337, 0.18200290247627665, 0.0020154085712910707, -0.012190829753206725, -0.04648398598417859]
        ],
        "rotationVectors": [
            [[0.014376302442723948], [0.1667778841470017], [0.018832348485715023]],
            [[-0.3405035725192283], [0.526867552280327], [-0.13373157952652456]]
        ],
        "translationVectors": [
            [[71.27846898868391], [50.76036240921024], [1400.9402673825555]],
            [[-476.2081267995082], [-120.35757569213392], [803.862414335442]]
        ]
    }
    

  • Try reading the params from file

    # remember to provide appropriate path to the calibration params
    # you can simply create a json file with structure shown above
    calibrationParams = load_calibration("../../tests/calibration_params/calibration_params.json")
    

  • Display the MSE value to test if the load succeeded

    print(calibrationParams["mse"])
    


Code requirements

The code fulfills all the requirements necessary to pass the course. Detailed descriptions of the requirements for each lab are provided in the ./docs/code_requirements directory in the form of images (in Polish).



Sources

This package has been prepared following this tutorial.

The publishing to PyPI was created with this tutorial

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