Use RGB images and depth maps to generate a point cloud image

def create_pcd_from_rgbd(rgb_img, depth_img):
    """
    *Compute point cloud from depth*
    """
    #depth_img  单位um
    t1 = time.time()
    depth = depth_img
    rgb = rgb_img#[:, :, ::-1]
    h,w,ch=rgb_img.shape
    xmap = np.arange(w)
    ymap = np.arange(h)
    xmap, ymap = np.meshgrid(xmap, ymap)
    points_z = depth*1000
    points_x = xmap*10
    points_y = ymap*10
    pcd = np.stack([points_x, points_y, points_z], axis=-1)
    pcd.shape = (h*w,3)
    point_cloud = o3.geometry.PointCloud()
    pcd_rgb=rgb_img.copy()
    pcd_rgb.shape= (h*w,3)
    point_cloud.points = o3.utility.Vector3dVector(pcd)
    point_cloud.colors = o3.utility.Vector3dVector(pcd_rgb)
    t2 = time.time()
    print('create_pcd_from_rgbd time: {}'.format(t2 - t1))
    return point_cloud

One thing to note,

rgb_img needs to be a floating point number, between 0 and 1

depth_img is also a floating point number, and its size is consistent with rgb_img.

The final point cloud image can be displayed through o3.visualization.draw_geometry([point_cloud]).