Transforming images into matrix or tensor objects of various libraries

In most cases, images are represented in computer memory in an interleaved format, which means that pixel values are placed one by one in linear order. Each pixel value consists of several numbers representing a color. For example, for the RGB format, it will be three values placed together. So, in the memory, we will see the following layout for a 4 x 4 image:

rgb rgb rgb rgb
rgb rgb rgb rgb
rgb rgb rgb rgb
rgb rgb rgb rgb

For image processing libraries, such a value layout is not a problem, but many machine learning algorithms require different ordering. For example, it's a common approach for neural networks to take image channels separately ordered, one by one. The following example shows how such a layout is usually placed in memory:

r r r r   g g g g   b b b b
r r r r   g g g g   b b b b
r r r r   g g...