image-processing-ajs 0.1.0

A package for image processing using Python

Image Processing AJS

Description

"image_processing_ajs" is an image processing package developed in Python that offers a variety of functionalities for image manipulation and analysis. This package utilizes popular libraries such as scikit-image and matplotlib, making it easy to perform common image processing tasks.

Package Structure

image_processing_ajs/  
├── processing/                        # Main package directory  
│   ├── __init__.py                    # Marks this directory as a Python package  
│   ├── io.py                          # Loads and saves images  
│   ├── measure.py                     # Labels and measures connected components  
│   ├── exposure.py                    # Adjusts intensity and gamma correction  
│   ├── color.py                       # Converts colored images to grayscale  
│   └── plot.py                        # Functions for visualizing results  
├── tests/                             # Directory for tests  
│   ├── __init__.py                    # Marks this directory as a Python package  
│   ├── test_io.py                     # Tests for loads and saves images  
│   ├── test_measure.py                # Tests for labels and measures connected components  
│   ├── test_exposure.py               # Tests for adjusts intensity and gamma correction  
│   ├── test_color.py                  # Tests for converts colored images to grayscale  
│   └── test_plot.py                   # Tests for functions for visualizing results  
├── README.md                          # Basic documentation  
├── setup.py                           # Setup script for setuptools  
└── requirements.txt                   # Dependencies file  

Package Modules

“io.py”:
Uses the functions “skimage.io.imread()” and “skimage.io.imsave()” to load and save images in various formats such as JPG, PNG, TIFF, etc.

“measure.py”:
Uses “skimage.measure.label()” to label connected components in a binary image.
Uses “skimage.measure.regionprops()” to calculate properties of labeled objects, such as area, perimeter, etc.
Uses “skimage.feature.canny()” to perform edge detection using the Canny algorithm.

“exposure.py”:
Uses “skimage.exposure.adjust_gamma()” to adjust the gamma correction of an image.
Uses “skimage.exposure.rescale_intensity()” to rescale the intensity of pixel values.

“color.py”:
Uses “skimage.color.rgb2gray()” to convert colored images (RGB) to grayscale.

“plot.py”:
Uses functions “show_image()” and “show_images_side_by_side()” from the “matplotlib” library to display the results from the “io”, “measure”, “exposure”, and “color” modules.

Installation

Use the package manager pip to install image_processing_ajs:

pip install image_processing_ajs

If you are developing the package locally, clone the repository and install the dependencies:

git clone https://github.com/soaresaj/image-processing-ajs-package
cd image_processing_ajs
pip install -r requirements.txt

Usage

An example of how to use the package:

from image_processing_ajs import io, measure, exposure, color, plot

# Load an image
image = io.imread('path/to/image.jpg')

# Adjust the image gamma correction
adjusted_image = exposure.adjust_gamma(image, gamma=1.5)

# Convert the image to grayscale
gray_image = color.rgb2gray(image)

# Label connected components
labels = measure.label(gray_image)

# Display the results
plot.show_image(image)

Tests

The package contains a test directory where you can find test cases to ensure the proper functionality of the features.

Contributions

Contributions are welcome! Feel free to open issues or submit pull requests.

Author

Antonio José Soares

License

This project is licensed under the MIT License.