lafte1 / imageops

ImageOps is a comprehensive Python imaging API for image processing, designed for performance and simplicity of integration into Python projects

ImageOps

ImageOps is an open-source image processing API that provides a set of basic yet important functionalities to manipulate and transform images.

Table of Contents

• Project Overview
• Collaboration
• Usage
• Dependencies

Project Overview

ImageOps aims to simplify image processing tasks by offering a straightforward API for common operations. This project was initiated to address the need for a flexible, easy-to-use image-processing solution for developers working on diverse projects. It should be noted that the API is still under development and is yet to be hosted externally.

Collaboration

How to contribute:

1. Fork the repository: Start by forking the ImageOps repository to your GitHub account.
2. Clone the repository: clone the forked repository to your local machine

git clone https://github.com/your-username/ImageOps.git

3. Create a Branch: Create a new branch for your contribution

git checkout -b feature-or-fix-name

4. Make and commit changes: Implement your desired feature or fix in the code.
5. **Push changes: After committing the changes, push them to your forked repository

git push origin feature-or-fix-name

6. Open a Pull Request: Create a pull request from your forked repository to the main ImageOps repository.

Testing

1. In the repository folder, create a virtual environment(optional):

python -m venv venv

2. Activate the environment:

• On Windows:

venv\Scripts\activate

• On MacOS/Linux:

source venv/bin/activate

3. Install requirements:

pip install -r requirements.txt

The API can be tested locally by sending requests to 'http://127.0.0.1:5000/api/'. First, the server should be started:

python app/main.py

A test image is included, with a testing code:

python testing/testing.py

Usage

ImageOps offers several endpoints for image processing tasks. here is a quick overview:

• Grayscale Conversion:

  • Endpoint: '/api/grayscale'
  • Parameters:
    • image (.png -> bytes): image to be converted

• Negative Conversion:

  • Endpoint: '/api/negative'
  • Parameters:
    • image (.png -> bytes): image to be converted

• Half-toning transformation:

  • Endpoint: '/api/half'
  • Parameters:
    • image (.png -> bytes): image to be half-toned using Floyd Steinberg's algorithm

• Sobel Edge Detection:

  • Endpoint: '/api/sobel_edge'
  • Parameters:
    • image (.png -> bytes): input image file for edge detection.

Dependencies

ImageOps relies on the following dependencies (some might be added/deleted as the project progresses):

• Flask
• NumPy
• CV2
• Pillow

All dependencies are listed in the requirements.txt file.