Light-Distribution-Analysis

🛡️ Badges

Overview

Light-Distribution-Analysis is a Python package designed for the analysis of light distribution in images. The package utilizes OpenCV, NumPy, and Matplotlib to enable in-depth yet simple analysis of the flux and power in images based on their wavelength and frequency representations.

Features

• Convert RGB images to wavelength and frequency representations
• Apply edge detection on images
• Calculate the flux and power of images
• Save processed images in various forms
• Calculate similarity scores based on flux and power
• Plot power images
• Export flux and power data to a CSV file (feature planned)

Installation

To install Light-Distribution-Analysis, run the following command in your terminal:

python3 -m pip install light-distribution-analysis

Functions

Validate File Type

from light_distribution_analysis import validate_file_type
is_valid = validate_file_type('path/to/image.jpg')

Checks if the file type of an image is valid (JPG or PNG).

Validate Image Dimensions

from light_distribution_analysis import validate_image_dimensions
is_valid = validate_image_dimensions(image_array)

Checks if an image has the correct dimensions (3-channel color image).

Load Image

from light_distribution_analysis import load_image
image_array = load_image('path/to/image.jpg')

Loads an image from a given path into a NumPy array.

Convert to RGB

from light_distribution_analysis import convert_to_rgb
image_rgb = convert_to_rgb(image_array)

Converts a given image to its RGB representation.

Save Image

from light_distribution_analysis import save_image
save_image(image_array, 'path/to/save/image.jpg')

Saves an image to the specified path.

Apply Edge Detection

from light_distribution_analysis import apply_edge_detection
edge_image = apply_edge_detection(image_array, method='Canny')

Applies edge detection to an image using either the 'Canny' or 'Sobel' method.

Calculate Flux

from light_distribution_analysis import calculate_flux
flux_value = calculate_flux(intensity_image, quantity_image)

Calculates the flux of an image given its intensity and quantity representations.

Calculate Power

from light_distribution_analysis import calculate_power
power_value = calculate_power(intensity_image)

Calculates the power of an image based on its intensity representation.

Plot Power Image

from light_distribution_analysis import plot_power_image
plot_power_image(intensity_image, 'path/to/save/power_image.jpg')

Generates and saves a power image based on the intensity of the original image.

Examples

Basic Image Processing

from light_distribution_analysis import process_single_image
process_single_image('path/to/image.jpg', 'output/directory/')

Flux Comparison

from light_distribution_analysis import compare_flux
similarity_score_flux = compare_flux('path/to/image1.jpg', 'path/to/image2.jpg')
print(f"Flux Similarity Score: {similarity_score_flux}")

Power Calculation and Comparison

from light_distribution_analysis import compare_power
similarity_score_power = compare_power('path/to/image1.jpg', 'path/to/image2.jpg')
print(f"Power Similarity Score: {similarity_score_power}")

Interpreting the Similarity Score

A similarity score close to 1 indicates that the images are highly similar in terms of their flux, whereas a score close to 0 suggests they are dissimilar.