点云可视化 open3D

好博客汇总

• Python点云数据处理(六)Open3d补充：点云基本处理 - 知乎 https://zhuanlan.zhihu.com/p/353971365?utm_id=0

• open3d绘制点云1–单帧点云 - 知乎 https://zhuanlan.zhihu.com/p/591249741

• (168条消息) open3D 的使用，pcd可视化，3D bbox可视化，web_visualizer使用等。_CV矿工的博客-CSDN博客 https://blog.csdn.net/ZauberC/article/details/127260203

• open3d.geometry.AxisAlignedBoundingBox — Open3D 0.17.0 documentation http://www.open3d.org/docs/release/python_api/open3d.geometry.AxisAlignedBoundingBox.html

• Open3D 可视化(1)——简单可视化_o3d.visualization.draw_geometries_Dove_1234的博客-CSDN博客 https://blog.csdn.net/baidu_39332177/article/details/127792817

• 爆肝5万字❤️Open3D 点云数据处理基础（Python版） - 小智博客 http://imyhq.com/design/312.html#23__191

点云语义分割可视化

测试文件Area_5_office_10.npy下载

用open3D可以弹出一个窗口，支持鼠标旋转和放缩，很方便

方案1：npy文件包含位置和颜色

#不显示天花板和天花板上的灯
#coding=utf-8
import open3d as o3d
import numpy as np

np.set_printoptions(suppress=True) # 取消默认科学计数法，open3d无法读取科学计数法表示
data = np.load("C:/Users/mi/Desktop/trash/Area_5_office_10.npy")# point_num, x、y、z、r、g、b、label

data = data[data[:,6]!=0] # 0 cell：去除天花板
data = data[data[:,6]!=12] # 12 ：去除天花板上的灯

b = np.array([1 , 1, 1,255, 255, 255]) # 每一列要除的数
np.savetxt('scene.txt', data[:,:6]/b)
# 读取点云并可视化
pcd =o3d.io.read_point_cloud("scene.txt", format='xyzrgb') # 原npy文件中的数据正好是按x y z r g b进行排列
# print(pcd)
o3d.visualization.draw_geometries([pcd], width=1200, height=600)

参考的博客

方案2：npy 文件 位置跟颜色分离

• 点跟颜色分离处理
• 点由原始的输入提供
• 颜色可自定义为，现实颜色、gt label颜色、pre label 颜色

import open3d as o3d
import numpy as np
from copy import deepcopy

if __name__ == '__main__':
    # point_num, x、y、z、r、g、b、label
    points = np.load('C:/Users/mi/Desktop/trash/Area_5_office_10.npy') 
    
	data = data[data[:,6]!=0] # 0 cell：去除天花板
	data = data[data[:,6]!=12] # 12 ：去除天花板上的灯

    preds = points[:,-1]
    print(preds.shape, points.shape)
    print(set(preds))

    # 随机生成13个类别的颜色
    colors_0 = np.random.randint(255, size=(13, 3)) / 255.
	
	# 获取场景的点
    pcd = o3d.geometry.PointCloud()
    pcd.points = o3d.utility.Vector3dVector(points[:, :3])

    # 为各个真实标签指定颜色
    colors = colors_0[points[:, -1].astype(np.uint8)]
    pcd.colors = o3d.utility.Vector3dVector(colors[:, :3])

    # 显示现实颜色
    pcd1 = deepcopy(pcd)
    pcd1.translate((0, 5, 0))  # 整体进行y轴方向平移5
    pcd1.colors = o3d.utility.Vector3dVector(points[:,3:6]/255)

    # 点云显示
    o3d.visualization.draw_geometries([pcd, pcd1], window_name="xxx语义分割结果",
                                      point_show_normal=False,
                                      width=800,  # 窗口宽度
                                      height=600)

参考的博客

方案3：同时显示现实颜色、gt、pre label

文件下载

import open3d as o3d
import numpy as np
from copy import deepcopy

if __name__ == '__main__':

    # pc_num, 6.  
    #6: xyzrgb
    points = np.load('C:/Users/mi/Desktop/trash/pc.npy')
    
    # pc_num
    gt = np.load('C:/Users/mi/Desktop/trash/gt_l.npy')
    # pc_num, 1
    gt = gt.reshape(-1,1)
    
    # pc_num
    pre = np.load('C:/Users/mi/Desktop/trash/pre_l.npy')
    # pc_num, 1
    pre = pre.reshape(-1,1)
    points = np.concatenate([points, gt, pre], axis=-1)
    # concatenate((a, b, c), axis=0)
    points = points[points[:, 6] != 0]
    points = points[points[:, 6] != 12]

    gt = points[:,6]
    pre = points[:,7]

    # 随机生成13个类别的颜色
    colors_0 = np.random.randint(255, size=(13, 3)) / 255.
    pcd = o3d.geometry.PointCloud()
    pcd.points = o3d.utility.Vector3dVector(points[:, :3])

    # 为各个真实标签指定颜色
    colors = colors_0[gt.astype(np.uint8)]
    pcd.colors = o3d.utility.Vector3dVector(colors[:, :3])

    # 显示现实颜色
    pcd1 = deepcopy(pcd)
    pcd1.translate((0, 9, 0))  # 整体进行y轴方向平移5
    # 为各个预测标签指定颜色
    # colors = colors_0[preds.astype(np.uint8)]
    pcd1.colors = o3d.utility.Vector3dVector(points[:,3:6]/255)

    #  pre 颜色
    pcd2 = deepcopy(pcd1)
    pcd2.translate((0, 9, 0))  # 整体进行y轴方向平移5
    # 为各个预测标签指定颜色
    colors = colors_0[pre.astype(np.uint8)]
    pcd2.colors = o3d.utility.Vector3dVector(colors[:, :3])

    # 点云显示
    o3d.visualization.draw_geometries([pcd, pcd1, pcd2], window_name="PointNet++语义分割结果",
                                      point_show_normal=False,
                                      width=800,  # 窗口宽度
                                      height=600)

目标检测可视化

每个检测的Box,可由

• box_center: box中心的位置，xyz
• box_size:每个Box 长宽高的一半， lwh
• Box_angle：默认box 绕z轴旋转，r

文件下载

import open3d as o3d
import numpy as np
from copy import deepcopy

i =9

# pc_num, xyz
points = np.load('C:/Users/mi/Desktop/trash/box/npy/gt_pc_'+str(i)+'_.npy')
# pc_num, rgb
color = np.load('C:/Users/mi/Desktop/trash/box/npy/color_'+str(i)+'_.npy')

# gt
# box_num,xyz
gt_box_center = np.load('C:/Users/mi/Desktop/trash/box/npy/gt_box_center_'+str(i)+'_.npy')
#box_num,angle
gt_box_angles = np.load('C:/Users/mi/Desktop/trash/box/npy/gt_box_angle_'+str(i)+'_.npy').reshape(-1,1)
# box_num,lwh
gt_box_size = np.load('C:/Users/mi/Desktop/trash/box/npy/gt_box_size_'+str(i)+'_.npy')


point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(points[:, :3])
point_cloud.colors = o3d.utility.Vector3dVector(color/255)

vis = o3d.visualization.Visualizer()
vis.create_window()
vis.add_geometry(point_cloud)


gt_boxes = np.concatenate([gt_box_center, gt_box_size, gt_box_angles], axis=-1)
for i, box in enumerate(gt_boxes):
    b = o3d.geometry.OrientedBoundingBox()
    b.center = box[:3]
    b.extent = box[3:6]
    # with heading
    R = o3d.geometry.OrientedBoundingBox.get_rotation_matrix_from_xyz((0, 0, box[6]))
    b.rotate(R, b.center)
    b.color = (1,1,0)
    vis.add_geometry(b)

# vis.get_render_option().background_color = np.asarray([0, 0, 0]) # 设置一些渲染属性
vis.run()
vis.destroy_window()

展示图局部放大

一些大型场景的图片，放大后可以比较gt和pre
https://www.yingsoo.com/news/devops/37918.html