cv_tools.py

import numpy as np
import cv2

# Order the points so that the coords stay consistent 
def order_points(pts):
    rect = np.zeros((4,2), dtype= "float32")

    s = pts.sum(axis=1)
    rect[0] = pts[np.argmin(s)]
    rect[2] = pts[np.argmax(s)]

    diff = np.diff(pts, axis=1)
    rect[1] = pts[np.argmin(diff)]
    rect[3] = pts[np.argmax(diff)]

    return rect

# Perform a matrix transformation to make corners to the corners of a new image
def four_point_transform(image,pts):

    rect = order_points(pts)
    (tl,tr,br,bl) = rect
    
    # Find widest part of detected object
    widthA = np.sqrt(((br[0] - bl[0]) ** 2) + (br[1] - bl[1]) ** 2)
    widthB = np.sqrt(((tr[0] - tl[0]) ** 2) + (tr[1] - tl[1]) ** 2)

    maxWidth = max(int(widthA), int(widthB))
    
    # Find tallest part of detected object
    heightA = np.sqrt(((tr[0] - br[0]) ** 2) + (tr[1] - br[1]) ** 2)
    heightB = np.sqrt(((tl[0] - bl[0]) ** 2) + (tl[1] - bl[1]) ** 2)

    maxHeight = max(int(heightA), int(heightB))
    
    # Calculate and perform the perspective transformation
    dst = np.array([
        [0,0],[maxWidth-1, 0], [maxWidth-1, maxHeight-1], 
        [0, maxHeight-1]], dtype = "float32")

    M = cv2.getPerspectiveTransform(rect,dst)
    warp = cv2.warpPerspective(image, M, (maxWidth,maxHeight))

    return warp