To computationally process the image-based labels in the Pascal VOC2012 dataset, the RGB color values of each pixel must be mapped to distinct integer class indices. This is accomplished by defining a colormap that lists the RGB values for all predefined categories (e.g., background is [0, 0, 0], aeroplane is [128, 0, 0]). A mapping array of size $256^3$ can then be constructed to serve as a fast lookup table, instantly translating any given RGB combination in a label image to its corresponding integer class index for neural network training.