In the old Tangent Prop paper (you don't need to know this paper), the tangent vector of the rotation transformation (think of this as a vector-valued function) at some input image is approximated by (1) rotating this input image by a very small amount, (2) subtracting this rotated image from the original image and (3) dividing the result of subtraction by the degree rotated.
However, I'm not understanding what it means to rotate an image (i.e., a matrix) by a very small amount (less than one degree).
Also, how can this be implemented in Python using libraries like Python / Scipy / Skimage?
In addition, how am I supposed to know that the image has actually been rotated, since the rotation is so small?
Note: I tried to do rotation with Skimage, but it seems like Skimage allows rotations of at least 1 degree.
Since I'm new to these concepts, I wouldn't mind if someone points me to some resources or references since it might be hard to provide a succinct answer.