Usage Documentation

This document provides an overview and description of the functions available in the ArtSnake library. The focus of this guide is on functions for calculating differences and similarities between images.

Watermark Insertion Functions

insert_watermark

Description:

The insert_watermark function inserts a watermark into an image. This is the main function and uses multiple sub-functions to detect, remove, and insert watermarks. You can create your custom functions and pass them as arguments to this function, but the standard versions of each function are listed below.

Function Signature:

insert_watermark(img, watermark, n, measure_diff=measure_diff_padrao, watermark_remover=watermark_remover_padrao, watermark_detector=watermark_detector_padrao)

Arguments:

  • img (numpy.ndarray): The image to insert the watermark into.

  • watermark (numpy.ndarray): The watermark image.

  • n (int): The number of iterations to perform the watermark random insertion process.

  • measure_diff (function, optional): The function to use for measuring differences between images. Defaults to measure_diff_padrao.

  • watermark_remover (function, optional): The function to use for removing watermarks from images. Defaults to watermark_remover_padrao.

  • watermark_detector (function, optional): The function to use for detecting watermarks in images. Defaults to watermark_detector_padrao.

Returns:

  • img (numpy.ndarray): The image with the watermark inserted.

  • score (float): The score of the quality of the inserted watermark.

Example Usage:

import cv2
from ArtSnake import *

imagem1_path = "../image.jpeg"
imagem2_path = "../praia.jpg"

img1 = cv2.imread(imagem1_path)
img2 = cv2.imread(imagem2_path)

result, score = insert_watermark(img2, img1, 10)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

Image Comparison Functions

The following functions are designed to compare images by calculating differences and similarities.

measure_diff_simple

Description:

The measure_diff_simple function calculates the simple pixel-wise difference between two images.

Function Signature:

measure_diff_simple(img1, img2, show_diff=False)

Arguments:

  • img1 (numpy.ndarray): The first image.

  • img2 (numpy.ndarray): The second image.

  • show_diff (bool, optional): Whether to display the difference image. Defaults to False.

Returns:

  • diff (float): The calculated difference value.

Example Usage:

from ArtSnake import measure_diff_simple

diff = measure_diff_simple(image1, image2, show_diff=True)

measure_similarity_psnr

Description:

The measure_similarity_psnr function calculates the Peak Signal-to-Noise Ratio (PSNR) between two images.

Function Signature:

measure_similarity_psnr(img1, img2, show_diff=False)

Arguments:

  • img1 (numpy.ndarray): The first image.

  • img2 (numpy.ndarray): The second image.

  • show_diff (bool, optional): Whether to display the difference image. Defaults to False.

Returns:

  • psnr (float): The calculated PSNR value.

Example Usage:

from ArtSnake import measure_similarity_psnr

psnr = measure_similarity_psnr(image1, image2, show_diff=True)

measure_similarity_ssim

Description:

The measure_similarity_ssim function calculates the Structural Similarity Index (SSIM) between two images.

Function Signature:

measure_similarity_ssim(img1, img2, show_similarity=False)

Arguments:

  • img1 (numpy.ndarray): The first image.

  • img2 (numpy.ndarray): The second image.

  • show_similarity (bool, optional): Whether to print the SSIM value. Defaults to False.

Returns:

  • ssim_value (float): The calculated SSIM value.

Example Usage:

from ArtSnake import measure_similarity_ssim

ssim_value = measure_similarity_ssim(image1, image2, show_similarity=True)

Watermark Detection Functions

watermark_proba_prebuilt_from_opencv

Description:

The watermark_proba_prebuilt_from_opencv function calculates the probability that an image contains a watermark using a prebuilt model.

Function Signature:

watermark_proba_prebuilt_from_opencv(img_path)

Arguments:

  • img_path (str): The path to the image file.

Returns:

  • proba (float): The probability that the image contains a watermark.

Example Usage:

from ArtSnake import watermark_proba_prebuilt_from_opencv

proba = watermark_proba_prebuilt_from_opencv('path/to/image.jpg')

Watermark Removal Functions

remove_watermark_from_opencv

Description:

The remove_watermark_prebuilt_from_path function removes a watermark from an image file.

Function Signature:

remove_watermark_from_opencv(img_path)

Arguments:

  • img_path (str): The path to the image file.

Returns:

  • img (numpy.ndarray): The image with the watermark removed.

Example Usage:

from ArtSnake import remove_watermark_from_opencv

img = remove_watermark_from_opencv('path/to/image.jpg')