Python Image Processing Cookbook

Getting ready

First, download the skin segmentation dataset from the UCI Machine Learning Repository at https://archive.ics.uci.edu/ml/datasets/skin+segmentation. This dataset has the dimensions of 245057 x 4 and the first three columns are B, G, R values (corresponding to the variables x1, x2, and x3, respectively) and the fourth column is the class label (decision variable y, where y = 1 is a positive (that is, a skin example) and y = 2 is a nonskin example). Let's start by importing all the required libraries:

import numpy as npimport matplotlib as mplimport matplotlib.pyplot as pltfrom sklearn.mixture import GaussianMixtureimport pandas as pdimport seaborn as snsfrom skimage.io import imreadfrom skimage.color import rgb2ycbcr, gray2rgb ...