Perform the perspective transform on an image

perspective_transform.py

def get_mask_coord(imshape):
    vertices = np.array([[(0.09 * imshape[1], 0.99 * imshape[0]), 
                          (0.43 * imshape[1], 0.32 * imshape[0]), 
                          (0.56 * imshape[1], 0.32 * imshape[0]),
                          (0.85 * imshape[1], 0.99 * imshape[0])]], dtype = np.int32)
    return vertices

def get_perspective_matrices(X_img):
    offset = 15
    img_size = (X_img.shape[1], X_img.shape[0])

    # Estimate the coordinates of object of interest inside the image.
    src = np.float32(get_mask_coord(X_img.shape))
    dst = np.float32([[offset, img_size[1]], [offset, 0], [img_size[0] - offset, 0], 
                      [img_size[0] - offset, img_size[1]]])
    
    perspective_matrix = cv2.getPerspectiveTransform(src, dst)
    return perspective_matrix

def perspective_transform(X_img):
    # Doing only for one type of example
    perspective_matrix = get_perspective_matrices(X_img)
    warped_img = cv2.warpPerspective(X_img, perspective_matrix,
                                     (X_img.shape[1], X_img.shape[0]),
                                     flags = cv2.INTER_LINEAR)
    return warped_img
  
perspective_img = perspective_transform(X_img)