【Open3d】使用open3d可视化

可视化点云

# 使用open3d可视化点云
# 使用open3d可视化点云,返回pointcloud类型示例
def visualize(pointcloud):
    from open3d.open3d.geometry import PointCloud
    from open3d.open3d.utility import Vector3dVector
    from open3d.open3d.visualization import draw_geometries

    # from open3d_study import *


    # points = np.random.rand(10000, 3)
    point_cloud = PointCloud()
    point_cloud.points = Vector3dVector(pointcloud[:,0:3].reshape(-1,3))
    draw_geometries([point_cloud],width=800,height=600)
    return point_cloud

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使用knn搜索点云，并指定颜色

#创建点云对象
pcd=o3d.geometry.PointCloud()
pcd.points=o3d.utility.Vector3dVector(pt[:,0:3])
pcd.paint_uniform_color([0.5, 0.5, 0.5])  # 给全部点云上色，灰色
pcd_tree=o3d.geometry.KDTreeFlann(pcd)  # 创建一个实例 pcd_tree以使用KDTree
[k, index, _] = pcd_tree.search_knn_vector_3d(pcd.points[K], 50)
np.asarray(pcd.colors)[index[1:], :] = [0, 1, 0]   # 给50以内的点设置颜色为green

ps:colors和points是PointCloud中的两个矩阵

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可视化点云+label

可视化点云，并根据标签赋值颜色

def vis(data,label):
    '''
    :param data: n*3的矩阵
    :param label: n*1的矩阵
    :return: 可视化
    '''
    data=data[:,:3]
    labels=np.asarray(label)
    max_label=labels.max()

    # 颜色
    colors = plt.get_cmap("tab20")(labels / (max_label if max_label > 0 else 1))

    pt1 = o3d.geometry.PointCloud()
    pt1.points = o3d.utility.Vector3dVector(data.reshape(-1, 3))
    pt1.colors=o3d.utility.Vector3dVector(colors[:, :3])

    o3d.visualization.draw_geometries([pt1],'part of cloud',width=500,height=500)

可视化两个点云

可视化两个点云并赋予不同的颜色

def vis_cloud(a,b):
	# a:n*3的矩阵
	# b:n*3的矩阵
    pt1=o3d.geometry.PointCloud()
    pt1.points=o3d.utility.Vector3dVector(a.reshape(-1,3))
    pt1.paint_uniform_color([1,0,0])

    pt2=o3d.geometry.PointCloud()
    pt2.points=o3d.utility.Vector3dVector(b.reshape(-1,3))
    pt2.paint_uniform_color([0,1,0])

    o3d.visualization.draw_geometries([pt1,pt2],window_name='cloud[0] and corr',width=800,height=600)