Normalise face landmark data using python
Actually I think I have figured it out, pretty simple maths actually, here is what i am going to do

Take every point and take away the first box point values - this will give me the points as if the box starts at [ 0,0 ]
Apply the box/normalised size ratio to every point
I am currently learning python and playing around with tensorflow.
I have a bunch of images where I have obtained the landmarks (pixel points) of a person's facial features such as ears and eyes. In addition, it also provides me with a box (4 coordinates) where the face exists.
My goal is to normalise all the data from different images into a standard sized rectangle / square and calculate the position of the landmarks relative to the normalised size.
Is there an API that allows me to do this already or should I get cracking and calculate the points myself?
Thanks in advance.