How to tell if the lowest point in the output of BoxPoints(rect) is the bottom right or bottom left point of the bounding box?

Question

In answer to another question, Sushanth stated:

The lowest point of the rectangle(does not matter left or right) will always be the first sub-list of the "box" ndarray. So in the example I have given, the first sub-list [169 144] represents the "bottom right of this rectangle". Now this point will be the reference point to decide what the next sub-list represents. Meaning, the next sub-list will always represent the point that you first get when you move in the clockwise direction. (as shown in the second image of the for loop)

I don't understand how to tell if the lowest point is the bottom-left or bottom-right point on the bases of the "first sub-list".

I need to create a generalized code that can tell them apart so that I can reliably apply warpAffine transformation to a dataset of images (as shown here).

Answer 1

I learned later on that I actually didn't need that information for performing warpAffine transformation as the angle information is returned by minAreaRect

def warp_contour(img,cnt):
    rows, cols = img.shape
    
    rect = cv2.minAreaRect(cnt)
    center,_,angle = rect
    
    box = cv2.boxPoints(rect)
    box = np.int0(box)
    
    rot = cv2.getRotationMatrix2D(center, angle, 1)
    img = cv2.warpAffine(img, rot, (rows,cols))
    
    return img

_{But I won't be accepting this answer as I still want to know how to tell them apart.}

Answer 2

This is Sushanth's answer to my question:

To determine whether it is a bottom-left or right in a scenario when the two bottom points have the same y-coordinate: i. First, have a conditional statement to see whether the two bottom points have the same y-coordinate. ii. If the condition is True, then check which coordinate has the lowest x-value(or the highest). The coordinate with the lowest x-value will be bottom-left of course! "How did you determine this just by looking at the sub-list?" -- I did not determine it by just looking at it! I could not! This is exactly why I wrote the above for-loop in my answer!

_{with minor spelling corrections from my side}