网络中同一视角显示点云

import numpy as np
from numpy.core.fromnumeric import reshape
import open3d as o3d
from torch import tensor, TensorCOLOR_MAP = {0: (0., 0., 0.),1: (174., 199., 232.),2: (152., 223., 138.),3: (31., 119., 180.),4: (255., 187., 120.),5: (188., 189., 34.),6: (140., 86., 75.),7: (255., 152., 150.),8: (214., 39., 40.),9: (197., 176., 213.),10: (148., 103., 189.),11: (196., 156., 148.),12: (23., 190., 207.),13: (100., 85., 144.),14: (247., 182., 210.),15: (66., 188., 102.),16: (219., 219., 141.),17: (140., 57., 197.),18: (202., 185., 52.),19: (51., 176., 203.),20: (200., 54., 131.),21: (92., 193., 61.),22: (78., 71., 183.),23: (172., 114., 82.),24: (255., 127., 14.),25: (91., 163., 138.),26: (153., 98., 156.),27: (140., 153., 101.),28: (158., 218., 229.),29: (100., 125., 154.),30: (178., 127., 135.),32: (146., 111., 194.),33: (44., 160., 44.),34: (112., 128., 144.),35: (96., 207., 209.),36: (227., 119., 194.),37: (213., 92., 176.),38: (94., 106., 211.),39: (82., 84., 163.),40: (100., 85., 144.),
}def visualize_with_label(cloud, label, window_name="open3d"):assert cloud.shape[0] == label.shape[0]pt = o3d.geometry.PointCloud()pt.points = o3d.utility.Vector3dVector(cloud)colors = [COLOR_MAP[i] for i in list(label)]pt.colors = o3d.utility.Vector3dVector(colors)# o3d.visualization.draw_geometries([pt], window_name ,width=500, height=500)def visualize_without_label(cloud, window_name="open3d"):# assert cloud.shape[0] == label.shape[0]if isinstance(cloud, Tensor):cloud = cloud.cpu().numpy().reshape((-1,3))pt = o3d.geometry.PointCloud()pt.points = o3d.utility.Vector3dVector(cloud)# colors = [COLOR_MAP[i] for i in list(label)]# pt.colors = o3d.utility.Vector3dVector(colors)o3d.visualization.draw_geometries([pt], window_name ,width=500, height=500)def ptGenerator(cloud):if isinstance(cloud, Tensor):cloud = cloud.cpu().numpy().reshape((-1,3))pt = o3d.geometry.PointCloud()pt.points = o3d.utility.Vector3dVector(cloud)return ptdef save_view_point(pcd, filename):vis = o3d.visualization.Visualizer()vis.create_window()vis.add_geometry(pcd)vis.run()  # user changes the view and press "q" to terminateparam = vis.get_view_control().convert_to_pinhole_camera_parameters()o3d.io.write_pinhole_camera_parameters(filename, param)vis.destroy_window()def load_view_point(pcd, filename):vis = o3d.visualization.Visualizer()vis.create_window()ctr = vis.get_view_control()param = o3d.io.read_pinhole_camera_parameters(filename)vis.add_geometry(pcd)ctr.convert_from_pinhole_camera_parameters(param)vis.run()vis.destroy_window()def vis_by_one_viewpoint(load_view_point_flag:bool, window_name:str, pcd):# if load_view_point is False:# save_view_point = Trueif load_view_point_flag is False:save_view_point(pcd = pcd, filename = './view.json')print("===> save viewpoint to {}".format("./view.json"))elif load_view_point_flag  :print("===> load viewpoint from {}".format("./view.json"))load_view_point(pcd = pcd, filename = './view.json')else:raise NotImplementedError

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 PointCloudfrom open3d.open3d.utility import Vector3dVectorfrom 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

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

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)

保存与读取view point

参考

# Open3D: www.open3d.org
# The MIT License (MIT)
# See license file or visit www.open3d.org for details# examples/python/visualization/load_save_viewpoint.pyimport numpy as np
import open3d as o3ddef save_view_point(pcd, filename):vis = o3d.visualization.Visualizer()vis.create_window()vis.add_geometry(pcd)vis.run()  # user changes the view and press "q" to terminateparam = vis.get_view_control().convert_to_pinhole_camera_parameters()o3d.io.write_pinhole_camera_parameters(filename, param)vis.destroy_window()def load_view_point(pcd, filename):vis = o3d.visualization.Visualizer()vis.create_window()ctr = vis.get_view_control()param = o3d.io.read_pinhole_camera_parameters(filename)vis.add_geometry(pcd)ctr.convert_from_pinhole_camera_parameters(param)vis.run()vis.destroy_window()if __name__ == "__main__":pcd = o3d.io.read_point_cloud("../../test_data/fragment.pcd")save_view_point(pcd, "viewpoint.json")load_view_point(pcd, "viewpoint.json")

动态显示点云

# 方法2 类
# 参考：https://github.com/Jiang-Muyun/Open3D-Semantic-KITTI-Vis/blob/ddb188e1375a1d464dec077826725afd72a85e63/src/kitti_base.py#L43
class pt_Vis():def __init__(self,name='20m test',width=800,height=600,json='./config/view_point.json'):self.vis=o3d.visualization.Visualizer()self.vis.create_window(window_name=name,width=width,height=height)self.axis_pcd = o3d.geometry.TriangleMesh.create_coordinate_frame(size=5, origin=[0, 0, 0])# 可视化参数opt = self.vis.get_render_option()opt.background_color = np.asarray([0, 0, 0])opt.point_size = 1opt.show_coordinate_frame = Trueself.pcd = o3d.geometry.PointCloud()self.vis.add_geometry(self.pcd)# 读取viewpoint参数self.param=o3d.io.read_pinhole_camera_parameters(json)self.ctr=self.vis.get_view_control()self.ctr.convert_from_pinhole_camera_parameters(self.param)print('viewpoint json loaded!')# param = self.ctr.convert_to_pinhole_camera_parameters()## o3d.io.write_pinhole_camera_parameters('./config/new.json',param)# print('viewpoint json saved!')def __del__(self):self.vis.destroy_window()def update(self,pcd):''':param pcd: PointCLoud():return:'''self.pcd.points=pcd.pointsself.pcd=pcd# self.pcd.colors=pcd.colors# self.vis.clear_geometries()self.vis.update_geometry(self.pcd)          # 更新点云# self.vis.remove_geometry(self.pcd)          # 删除vis中的点云self.vis.add_geometry(self.pcd)             # 增加vis中的点云# 设置viewpointself.ctr.convert_from_pinhole_camera_parameters(self.param)self.vis.poll_events()self.vis.update_renderer()# self.vis.run()def capture_screen(self,fn, depth = False):if depth:self.vis.capture_depth_image(fn, False)else:self.vis.capture_screen_image(fn, False)

使用：创建一个对象，然后再循环中不断调用update函数就可以了。

动态显示点云

参考：https://www.cnblogs.com/brt2/p/14283547.html

import os
import numpy as np
import open3d as o3dfiles = os.listdir("0806_reconstruction/")vis = o3d.visualization.Visualizer()
vis.create_window()
pointcloud = o3d.geometry.PointCloud()
to_reset = True
vis.add_geometry(pointcloud)
for f in files:pcd = o3d.io.read_point_cloud("0806_reconstruction/" + f)pcd = np.asarray(pcd.points).reshape((-1, 3))pointcloud.points = o3d.utility.Vector3dVector(pcd)vis.update_geometry()# 注意，如果使用的是open3d 0.8.0以后的版本，这句话应该改为下面格式# vis.update_geometry(pointcloud)if to_reset:vis.reset_view_point(True)to_reset = Falsevis.poll_events()vis.update_renderer()

SemanticKITTI bin+label点云转PCD

参考：
https://github.com/PRBonn/semantic-kitti-api/blob/master/auxiliary/laserscan.py
https://github.com/mit-han-lab/spvnas/blob/master/visualize.py


# 将bin+label转为xyzrgb格式的PCD文件import numpy as np
import logging
import open3d as o3dlogging.basicConfig(format='%(asctime)s.%(msecs)03d [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s',datefmt='## %Y-%m-%d %H:%M:%S')logging.getLogger().setLevel(logging.DEBUG)
logger = logging.getLogger()label_name_mapping = {0: 'unlabeled',1: 'outlier',10: 'car',11: 'bicycle',13: 'bus',15: 'motorcycle',16: 'on-rails',18: 'truck',20: 'other-vehicle',30: 'person',31: 'bicyclist',32: 'motorcyclist',40: 'road',44: 'parking',48: 'sidewalk',49: 'other-ground',50: 'building',51: 'fence',52: 'other-structure',60: 'lane-marking',70: 'vegetation',71: 'trunk',72: 'terrain',80: 'pole',81: 'traffic-sign',99: 'other-object',252: 'moving-car',253: 'moving-bicyclist',254: 'moving-person',255: 'moving-motorcyclist',256: 'moving-on-rails',257: 'moving-bus',258: 'moving-truck',259: 'moving-other-vehicle'
}kept_labels = ['road', 'sidewalk', 'parking', 'other-ground', 'building', 'car', 'truck','bicycle', 'motorcycle', 'other-vehicle', 'vegetation', 'trunk', 'terrain','person', 'bicyclist', 'motorcyclist', 'fence', 'pole', 'traffic-sign'
]cmap = np.array([[245, 150, 100, 255],[245, 230, 100, 255],[150, 60, 30, 255],[180, 30, 80, 255],[255, 0, 0, 255],[30, 30, 255, 255],[200, 40, 255, 255],[90, 30, 150, 255],[255, 0, 255, 255],[255, 150, 255, 255],[75, 0, 75, 255],[75, 0, 175, 255],[0, 200, 255, 255],[50, 120, 255, 255],[0, 175, 0, 255],[0, 60, 135, 255],[80, 240, 150, 255],[150, 240, 255, 255],[0, 0, 255, 255],
])
cmap = cmap[:, [2, 1, 0, 3]]  # convert bgra to rgbaclass BinConvertor:def __init__(self, bin_name, label_name):self.bin_name = bin_nameself.label_name = label_nameself.points = np.zeros((0, 3), dtype=np.float32)self.sem_label = np.zeros((0, 1), dtype=np.uint32)  # [m, 1]: labelself.sem_label_color = np.zeros((0, 3), dtype=np.float32)  # [m ,3]: color# label mapreverse_label_name_mapping = {}self.label_map = np.zeros(260)cnt = 0for label_id in label_name_mapping:if label_id > 250:if label_name_mapping[label_id].replace('moving-','') in kept_labels:self.label_map[label_id] = reverse_label_name_mapping[label_name_mapping[label_id].replace('moving-', '')]else:self.label_map[label_id] = 255elif label_id == 0:self.label_map[label_id] = 255else:if label_name_mapping[label_id] in kept_labels:self.label_map[label_id] = cntreverse_label_name_mapping[label_name_mapping[label_id]] = cntcnt += 1else:self.label_map[label_id] = 255self.reverse_label_name_mapping = reverse_label_name_mappingdef read_bin(self):scan = np.fromfile(self.bin_name, dtype=np.float32)scan = scan.reshape((-1, 4))self.points = scan[:,:3]def read_label(self):label = np.fromfile(self.label_name, dtype=np.uint32)label = label.reshape((-1))self.sem_label = label & 0xFFFFassert self.points.shape[0] == self.sem_label.shape[0]self.sem_label = self.label_map[self.sem_label].astype(np.int64)def set_cloud(self):# make color tablecolor_dict = {}for i in range(19):color_dict[i] = cmap[i, :]color_dict[255] = [0,0,0,255]pc = o3d.geometry.PointCloud()pc.points = o3d.utility.Vector3dVector(self.points)cloud_color = [color_dict[i] for i in list(self.sem_label)]self.sem_label_color = np.array(cloud_color).reshape((-1,4))[:,:3] / 255pc.colors = o3d.utility.Vector3dVector(self.sem_label_color)o3d.visualization.draw_geometries([pc])output_path = "F:\git\qt_visualizer_pcl\qt_visualizer\data\\000005.pcd"o3d.io.write_point_cloud(output_path, pc)logger.info("===> point cloud save to {}".format(output_path))if __name__ == '__main__':bin_name = "F:\git\qt_visualizer_pcl\qt_visualizer\data\\velodyne\\000005.bin"label_name = "F:\git\qt_visualizer_pcl\qt_visualizer\data\labels\\000005.label"bc = BinConvertor(bin_name, label_name)bc.read_bin()bc.read_label()bc.set_cloud()

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【Open3d】使用open3d可视化

目录

网络中同一视角显示点云

可视化点云

使用knn搜索点云，并指定颜色

可视化点云+label

可视化两个点云

保存与读取view point

动态显示点云

动态显示点云

SemanticKITTI bin+label点云转PCD

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