OpenCV Python HoughLines Transformation get the rectangle points to crop the original image

Is there anyway to get the rectangle points from the HoughLines Transformation results and apply the crop point to original image to get the cropped image. I have copied the code form the documentation. The idea is to extract the document from an image. Below is the result from the HoughLines Transformation and I required the intersection point to crop the image.

"""
@file hough_lines.py
@brief This program demonstrates line finding with the Hough transform
"""
import sys
import math
import cv2 as cv
import numpy as np
import matplotlib.pyplot as plt

def main(argv=[]):
    
    default_file = "/Users/apple/Downloads/Unknown-4"
    filename = argv[0] if len(argv) > 0 else default_file
    # Loads an image
    src = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
    # Check if image is loaded fine
    if src is None:
        print ('Error opening image!')
        print ('Usage: hough_lines.py [image_name -- default ' + default_file + '] \n')
        return -1
    
    
    dst = cv.Canny(src, 50, 200, None, 3)
    
    # Copy edges to the images that will display the results in BGR
    cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
    cdstP = np.copy(cdst)
    
    lines = cv.HoughLines(dst, 1, np.pi / 180, 150, None, 0, 0)
    
                   
    
    if lines is not None:
        for i in range(0, len(lines)):
            rho = lines[i][0][0]
            theta = lines[i][0][1]
            a = math.cos(theta)
            b = math.sin(theta)
            x0 = a * rho
            y0 = b * rho
            pt1 = (int(x0 + 1000*(-b)), int(y0 + 1000*(a)))
            pt2 = (int(x0 - 1000*(-b)), int(y0 - 1000*(a)))
            cv.line(cdst, pt1, pt2, (0,0,255), 3, cv.LINE_AA)
    
    
    linesP = cv.HoughLinesP(dst, 1, np.pi / 180, 50, None, 50, 10)
    
    if linesP is not None:
        for i in range(0, len(linesP)):
            l = linesP[i][0]
            cv.line(cdstP, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3, cv.LINE_AA)
    
    #cv.imshow("Source", src)
    #plt.imshow(src)

    plt.imshow(cdstP)
    #plt.imshow(cdstP)
    
    


    
if __name__ == "__main__":
    main()