https://github.com/shaymorad/lightricks-home-assignment

My implementation of the home assignment given by the company Lightricks.
https://github.com/shaymorad/lightricks-home-assignment

cli-app home-assignment image-processing json jsonschema python3

Last synced: about 2 months ago
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My implementation of the home assignment given by the company Lightricks.

• Host: GitHub
• URL: https://github.com/shaymorad/lightricks-home-assignment
• Owner: ShayMorad
• License: mit
• Created: 2025-06-09T19:32:56.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-09T20:07:24.000Z (about 1 year ago)
• Last Synced: 2025-06-09T20:29:48.688Z (about 1 year ago)
• Topics: cli-app, home-assignment, image-processing, json, jsonschema, python3
• Language: Python
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          


  
Advanced Image Editing System


  


  This project was developed as part of the Lightricks Students Home Assignment.

  


  It showcases an image editing tool built from scratch in Python, using NumPy for core operations and implementing convolution-based filters and adjustments without any external image-processing libraries.

  


  The system is modular, extensible, and configurable via a JSON file, and supports both saving and displaying the final result.

  








  
Features

  


    


Modular Design - Each operation is cleanly separated to allow for easy extension and maintenance.

    


JSON-Based Configuration - Users can define image paths, filters, parameters, and save/display options using a structured input file.

    


Supported Filters:

      


        


Box Blur – Averages pixel values in an X×Y neighborhood to produce a softened effect.

        


Sobel Edge Detection – Highlights image edges using horizontal and vertical gradient kernels.

        


Sharpen – Enhances image details using the unsharp masking technique.

      

    

    


Supported Adjustments:

      


        


Brightness – Adjusts pixel intensity globally.

        


Contrast – Stretches or compresses pixel value distribution.

        


Saturation – Modifies color vibrancy (in RGB approximation).

      

    

    


Sequential Layering - Applies operations in the exact order specified by the user.

    


Validation & Error Handling - Provides clear messages for invalid configuration files.

    


Display or Save Output - Allows visualizing the result or saving it to a file based on user input.

    


CLI Integration - Run the tool via command line with a single command.

  








  
Media


  
Here are a few examples of images edited using the tool and the filters described above:


  


    
Original Image

    

    
Box Blur (5x5)

    

    
Sobel Edge Detection

    

    
Pipeline (multiple filters layered)

    

  








  
Running the Project


  
To try it out locally, follow these steps:

  


    
Clone the repository: git clone <url>



    
Open the folder in your preferred code editor

    


Optional: Set up a virtual environment using python3 -m venv venv



    
Install dependencies: pip install -r requirements.txt



    
Run the editor with: python3 edit_image.py --config path/to/config.json



  








  
Example JSON Configuration


```json

{

  "input": "image.png",

  "output": "output.png",

  "display": true,

  "operations": [

    {

      "type": "brightness",

      "value": 0.6

    },

    {

      "type": "box",

      "width": 5,

      "height": 3

    },

    {

      "type": "contrast",

      "value": -3

    }

  ]

}