Why are the images flattened column wise?

The image dataset undergoes some pre-processing to become a column vector so that it can be inputted. Why are they not processed into a row vector and inputted instead?

Either row or column vectors may be used. There is little standardization in how the data set is organized.


Sometimes while using the lib we have to follow its way of using and accepting things, ways in which a particular lib expects the data to be, so its better to make it a habit from the start to deal with the data in that format.

For example, TensorFlow typically uses channel-last format (height, width, channels), while PyTorch often uses channel-first format (channels, height, width).
When flattening, these conventions can influence whether you choose row-wise or column-wise flattening.

like h x w x c is 4 x 4x 3 becomes 16 x 3 (column wise)
and c x h x w is 3 x 4 x 4 becomes 3 x 16 (row wise)