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A web application that renders an effect on an image uploaded by user using python image processing libraries.

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photo_effect

A web application that renders an effect on an image uploaded by user using python image processing libraries.

Techstack:

  1. Python
  2. Flask
  3. HTML
  4. CSS
  5. Bootstrap

Workflow:

  1. User uploads image
  2. Image processed using image processing libraries like OpenCV
  3. User downloads image

Steps to launch application

NOTE: It is vital that you install Python before moving on to subsequent steps.

  1. Go to https://www.python.org/ and install the latest version compatible with your system
  2. Fork and clone the repo
  3. Create a virtual environment through the following command
    virtualenv venv
    
  4. Activate the virtualenv
  • (Windows)
    venv\Scripts\activate
    
  • (Linux)
    source venv/bin/activate
    
    NOTE: After you are done working on the application you can deactivate environment by
    deactivate
    
  1. Move to the cloned directory
cd photo_effect
  1. Open up the terminal and intall the necessary dependencies by the following command
    pip install -r requirements.txt
    
  2. Now that we have the essential dependencies lets launch the application through the following commands.
  • (Windows)
    set FLASK_APP = start.py
    flask run
    
  • (Linux)
    export FLASK_APP = start.py
    flask run
    
  1. It is possible that while running the application you run into " pakage not found" error. In this case all you need to do to install the necessary package is
    pip install package_name
    
  2. Start contributing to the project, comment on an issue if you want to work on it, you can also suggest new issues that you would like to work on!

References:

  1. Flask documentation https://flask.palletsprojects.com/en/1.1.x/
  2. OpenCV documentation https://opencv.org/
  3. Flask & OpenCV session recordings:

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A web application that renders an effect on an image uploaded by user using python image processing libraries.

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  • Python 70.4%
  • HTML 29.6%