Open3d Python实现点云的显示与交互式点选

Open3d的中文资料相对不是很丰富，网上有些代码还有小bug。今天我这儿搬运一下，提供点云显示和交互式点选的代码。

以下代码采用open3d 0.12.0 应该可以直接运行。如果有bug欢迎提出。

1.点云显示
代码引自：https://zhuanlan.zhihu.com/p/57215172

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(points)
o3d.visualization.draw_geometries([point_cloud])

2.给点云统一绘制为绿色

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.paint_uniform_color([0, 1, 0])#给所有点云一个统一的颜色
o3d.visualization.draw_geometries([point_cloud])

3.给每个点云以不同的颜色
此处定义一个随机color矩阵，一个向量由一个 1*3的向量决定。此处可以使用RGB颜色，不过颜色的值都要归一化到0~1之间。例如上图[0, 1, 0]表示绿色，[1, 0, 0]则表示红色，[0, 0, 1]则表示蓝色。其他颜色可以依据RGB颜色值表归一后获得。代码如下：

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
color = np.random.rand(10000, 3)
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.colors = o3d.utility.Vector3dVector(color)
o3d.visualization.draw_geometries([point_cloud])

4.一个坐标系加入两组点云
如下代码第一块点云为绿色，第二块为红色。

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.paint_uniform_color([0, 1, 0])#给所有点云一个统一的颜色

points_2 = np.random.rand(100, 3)
point_cloud2 = o3d.geometry.PointCloud()
point_cloud2.points = o3d.utility.Vector3dVector(points_2)
point_cloud2.paint_uniform_color([1, 0, 0])#给所有点云一个统一的颜色
o3d.visualization.draw_geometries([point_cloud, point_cloud2])

采用o3d.visualization.draw绘制可以获得更加丰富的显示效果，可以旋转点的大小，设置光照等

5.同时绘制线和点云：

print("Let's draw a box using o3d.geometry.LineSet.")
points = [
[0, 0, 0],
[1, 0, 0],
[0, 1, 0],
[1, 1, 0],
[0, 0, 1],
[1, 0, 1],
[0, 1, 1],
[1, 1, 1],
]
lines = [#设置线条连接points中点的次序
[0, 1],
[0, 2],
[1, 3],
[2, 3],
[4, 5],
[4, 6],
[5, 7],
[6, 7],
[0, 4],
[1, 5],
[2, 6],
[3, 7],
]
colors = [[1, 0, 0] for i in range(len(lines))]
line_set = o3d.geometry.LineSet(
points=o3d.utility.Vector3dVector(points),
lines=o3d.utility.Vector2iVector(lines),
)
line_set.colors = o3d.utility.Vector3dVector(colors)
point_cloud2 = o3d.geometry.PointCloud()
point_cloud2.points = o3d.utility.Vector3dVector(points)
point_cloud2.paint_uniform_color([0, 1, 0])

o3d.visualization.draw_geometries([line_set, point_cloud2])

6.点云的坐标点选
点云坐标点选很简单，显示的函数稍微调整即可。以第二段代码为例进行修改，代码如下：

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
color = np.random.rand(10000, 3)
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.paint_uniform_color([0, 1, 0])#给所有点云一个统一的颜色
o3d.visualization.draw_geometries_with_editing([point_cloud])

图中小黄球和小蓝球就是按住shifit+鼠标左键点选得到的点，坐标在控制台中显示。按住shift+鼠标右键可以实现取消选择。

使用下面这段代码也可以实现上述功能，不过交互功能可以更加丰富。如按住q键就可以关闭Open3d的窗口，代码如下：

import numpy as np
import open3d as o3d

points = np.random.rand(10000, 3)
point_cloud = o3d.geometry.PointCloud()
color = np.random.rand(10000, 3)
point_cloud.points = o3d.utility.Vector3dVector(points)
point_cloud.paint_uniform_color([0, 1, 0])#给所有点云一个统一的颜色
vis = o3d.visualization.VisualizerWithEditing()
vis.create_window()
vis.add_geometry(point_cloud)
vis.run()  # user picks points
vis.destroy_window()

上述交互代码参考如下代码：（链接：http://www.open3d.org/docs/release/tutorial/visualization/interactive_visualization.html）

# examples/python/visualization/interactive_visualization.py

import numpy as np
import copy
import open3d as o3d


def demo_crop_geometry():
    print("Demo for manual geometry cropping")
    print(
        "1) Press 'Y' twice to align geometry with negative direction of y-axis"
    )
    print("2) Press 'K' to lock screen and to switch to selection mode")
    print("3) Drag for rectangle selection,")
    print("   or use ctrl + left click for polygon selection")
    print("4) Press 'C' to get a selected geometry and to save it")
    print("5) Press 'F' to switch to freeview mode")
    pcd = o3d.io.read_point_cloud("../../test_data/ICP/cloud_bin_0.pcd")
    o3d.visualization.draw_geometries_with_editing([pcd])


def draw_registration_result(source, target, transformation):
    source_temp = copy.deepcopy(source)
    target_temp = copy.deepcopy(target)
    source_temp.paint_uniform_color([1, 0.706, 0])
    target_temp.paint_uniform_color([0, 0.651, 0.929])
    source_temp.transform(transformation)
    o3d.visualization.draw_geometries([source_temp, target_temp])


def pick_points(pcd):
    print("")
    print(
        "1) Please pick at least three correspondences using [shift + left click]"
    )
    print("   Press [shift + right click] to undo point picking")
    print("2) After picking points, press 'Q' to close the window")
    vis = o3d.visualization.VisualizerWithEditing()
    vis.create_window()
    vis.add_geometry(pcd)
    vis.run()  # user picks points
    vis.destroy_window()
    print("")
    return vis.get_picked_points()


def demo_manual_registration():
    print("Demo for manual ICP")
    source = o3d.io.read_point_cloud("../../test_data/ICP/cloud_bin_0.pcd")
    target = o3d.io.read_point_cloud("../../test_data/ICP/cloud_bin_2.pcd")
    print("Visualization of two point clouds before manual alignment")
    draw_registration_result(source, target, np.identity(4))

    # pick points from two point clouds and builds correspondences
    picked_id_source = pick_points(source)
    picked_id_target = pick_points(target)
    assert (len(picked_id_source) >= 3 and len(picked_id_target) >= 3)
    assert (len(picked_id_source) == len(picked_id_target))
    corr = np.zeros((len(picked_id_source), 2))
    corr[:, 0] = picked_id_source
    corr[:, 1] = picked_id_target

    # estimate rough transformation using correspondences
    print("Compute a rough transform using the correspondences given by user")
    p2p = o3d.pipelines.registration.TransformationEstimationPointToPoint()
    trans_init = p2p.compute_transformation(source, target,
                                            o3d.utility.Vector2iVector(corr))

    # point-to-point ICP for refinement
    print("Perform point-to-point ICP refinement")
    threshold = 0.03  # 3cm distance threshold
    reg_p2p = o3d.pipelines.registration.registration_icp(
        source, target, threshold, trans_init,
        o3d.pipelines.registration.TransformationEstimationPointToPoint())
    draw_registration_result(source, target, reg_p2p.transformation)
    print("")


if __name__ == "__main__":
    demo_crop_geometry()
    demo_manual_registration()

欢迎大家一起搬运优质Open3d的资源，方便大家快速上手！