效果图：

代码：

import cv2
import os

img_path = "./outdir/180m_norm_depth.png"
depth_img = cv2.imread(img_path, cv2.IMREAD_ANYDEPTH)
filename = os.path.basename(img_path)
img_hig, img_wid = depth_img.shape  # (1080, 1920)
print(depth_img.shape)

point_color = (0, 0, 255) # BGR
thickness = 5 
lineType = 4

grid_size = 80

for i in range(img_wid // grid_size):  # 40 为正方向网格的宽
    for j in range(img_hig // grid_size):
        p1 = ((i + 1) * grid_size, (j + 1) * grid_size)
        p2 = (i * grid_size, (j + 1) * grid_size)
        p3 = ((i + 1) * grid_size, j * grid_size)
        cv2.line(depth_img, p1, p2, point_color, thickness, lineType)
        cv2.line(depth_img, p1, p3, point_color, thickness, lineType)
        depth_pos = ((i + 1) * grid_size - grid_size // 2, (j + 1) * grid_size - grid_size // 2)
        depth_value = depth_img[depth_pos[1], depth_pos[0]]
        cv2.putText(depth_img, str(depth_value), (depth_pos[0] - 20, depth_pos[1]), cv2.FONT_HERSHEY_COMPLEX, 0.8, (100, 200, 200), 1)
        # depth_img[i][j] = depth_img[i][j] / 1000
cv2.imwrite(os.path.join("./outdir/", filename[:filename.rfind('.')] + '_grid.png'), depth_img)