• [可视化] 点云可视化工具open3d的使用

    文章目录

    1. open3d 可视化语义分割点云和box(with angle)

    • visualize semantic segmentation points
    
def draw_boxes(vis, boxes, color):
    """
    Args:
        vis: o3d.visualization.Visualizer
        boxes: (N, 7)
        color: (0, 1, 0)
    """
    for i, box in enumerate(boxes):
        b = o3d.geometry.OrientedBoundingBox()
        b.center = box[:3]
        b.extent = box[3:6]
        print(box[6])
        R = o3d.geometry.OrientedBoundingBox.get_rotation_matrix_from_xyz((0, 0, box[6]))
        b.rotate(R, b.center)
        b.color = color
        vis.add_geometry(b) 

point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(valid_points1[:, :])
point_cloud.colors = o3d.utility.Vector3dVector(colors[valid_points[:, 8].astype(np.int32)])
vis = o3d.visualization.Visualizer()
vis.create_window()
vis.add_geometry(point_cloud)
draw_boxes(vis, boxes, (0,1,0))
vis.get_render_option().background_color = np.asarray([0, 0, 0])  # you can set the bg color
vis.run()
vis.destroy_window()

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    • visualize box with angle
    # (N, 7)
point_cloud = o3d.geometry.PointCloud()
point_cloud.points = o3d.utility.Vector3dVector(valid_points1[:, :])
point_cloud.colors = o3d.utility.Vector3dVector(colors[valid_points[:, 8].astype(np.int32)])
vis = o3d.visualization.Visualizer()
vis.create_window()
vis.add_geometry(point_cloud)
for i, box in enumerate(bboxes):
    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)  
    # 2nd method
    #lines_box = np.array([[0, 1], [1, 2], [0, 3], [2, 3], [4, 5], [4, 7], [5, 6], [6, 7],
    #                    [0, 4], [1, 5], [2, 6], [3, 7]])
    #colors = np.array([[0, 1, 0] for j in range(len(lines_box))])
    #line_set = o3d.geometry.LineSet()
    #line_set.lines = o3d.utility.Vector2iVector(lines_box)
    #line_set.colors = o3d.utility.Vector3dVector(colors)
    #line_set.points = o3d.utility.Vector3dVector(points_3dbox)
    #vis.add_geometry(line_set)
    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()

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    • 将vis可视化效果保存为图片形式
    vis.capture_screen_image("temp_%04d.jpg" % i)

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    2. 一些官方示例-用于参考

      
# ----------------------------------------------------------------------------
# -                        Open3D: www.open3d.org                            -
# ----------------------------------------------------------------------------
# The MIT License (MIT)
#
# Copyright (c) 2018-2021 www.open3d.org
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
# IN THE SOFTWARE.
# ----------------------------------------------------------------------------

from time import sleep
from numpy import outer
import open3d as o3d

if __name__ == "__main__":
    # o3d.visualization.webrtc_server.enable_webrtc()
    # cube_red = o3d.geometry.TriangleMesh.create_box(1, 2, 4)
    # cube_red.compute_vertex_normals()
    # cube_red.paint_uniform_color((1.0, 0.0, 0.0))
    # o3d.visualization.draw(cube_red)
    import numpy as np
    import open3d.ml as ml3d
    # or import open3d.ml.tf as ml3d
    # OPEN3D.ML.VISUALIZER不行
    # data = [ {
    #     'name': 'my_point_cloud',
    #     'points': np.random.rand(100,3).astype(np.float32),
    #     'point_attr1': np.random.rand(100).astype(np.float32),
    #     } ]
    # box1 = o3d.ml.vis.BoundingBox3D((20,1,1), front=(1,1,0),
    #                             up = (0,0,1),
    #                             left=(-1,1,0),
    #                             size=(2,2,4), 
    #                             label_class=1, 
    #                             confidence=0.5, 
    #                             show_class=True, 
    #                             show_confidence=True, 
    #                             arrow_length=1.0)
    # box2 = o3d.ml.vis.BoundingBox3D((10,1,1), front=(1,0,0),
    #                             up = (0,0,1),
    #                             left=(0,1,0),
    #                             size=(4,2,2), 
    #                             label_class=0, 
    #                             confidence=0.5, 
    #                             arrow_length=1.0)
    # lut = o3d.ml.vis.LabelLUT()
    # lut.add_label("car", 1, (1,0,0))
    # lut.add_label("people", 0, (0,1,0))
    # # box_cl = o3d.ml.vis.BoundingBox3D.create_lines(data_box["bboxes"], lut, out_format="lineset")

    # vis = ml3d.vis.Visualizer()
    # vis.visualize(data, lut, bounding_boxes=[box2, box1])

    # import pickle
    # import numpy as np
    # with open("train_0_197.pkl", 'rb') as f:
    #     data = pickle.load(f)
    #     #print(len(data))
    #     #print(data[0])
    #     for k, v in data[0].items():
    #         print(k)
    #     # print(data[0]['point_cloud'])
    # np.set_printoptions(suppress=True)
    # data = np.fromfile("0000000.bin", dtype=np.float32)
    # data = data.reshape(-1, 6)

    

    # import time
    # import open3d as o3d
    # # Monkey-patch torch.utils.tensorboard.SummaryWriter
    # from open3d.visualization.tensorboard_plugin import summary
    # # Utility function to convert Open3D geometry to a dictionary format
    # from open3d.visualization.tensorboard_plugin.util import to_dict_batch
    # from torch.utils.tensorboard import SummaryWriter

    # cube = o3d.geometry.TriangleMesh.create_box(1, 2, 4)
    # cube.compute_vertex_normals()
    # cylinder = o3d.geometry.TriangleMesh.create_cylinder(radius=1.0,
    #                                                     height=2.0,
    #                                                     resolution=20,
    #                                                     split=4)
    # cylinder.compute_vertex_normals()
    # colors = [(1.0, 0.0, 0.0), (0.0, 1.0, 0.0), (0.0, 0.0, 1.0)]
    # # ... geometry creation code as above ...
    # logdir = "/home/shimingli/Projects/3d_seg_head/scripts/test"
    # writer = SummaryWriter(logdir)
    # box1 = o3d.ml.vis.BoundingBox3D((20,1,1), front=(1,1,0),
    #                             up = (0,0,1),
    #                             left=(-1,1,0),
    #                             size=(2,2,4), 
    #                             label_class=1, 
    #                             confidence=0.5, 
    #                             show_class=True, 
    #                             show_confidence=True, 
    #                             arrow_length=1.0)
    # box2 = o3d.ml.vis.BoundingBox3D((10,1,1), front=(1,0,0),
    #                             up = (0,0,1),
    #                             left=(0,1,0),
    #                             size=(4,2,2), 
    #                             label_class=0, 
    #                             confidence=0.5, 
    #                             arrow_length=1.0)
    # print(to_dict_batch([cylinder]))
    # import torch
    # shape = data[None, :, :3].shape

    # data = {
    #     "vertex_positions": data[None, :, :3],
    #     "vertex_colors": np.zeros(shape)
    # }

    # data_box = {
    #     "bboxes":[box1, box2],
    # }
    # lut = o3d.ml.vis.LabelLUT()
    # lut.add_label("car", 1, (1,0,0))
    # lut.add_label("people", 0, (0,1,0))
    # box_cl = o3d.ml.vis.BoundingBox3D.create_lines(data_box["bboxes"], lut, out_format="lineset")
    
    # # print(box_cl)
    # # bbox_labels and bbox_confidences not supported in v14
    # # box_cl.pop("bbox_labels")
    # # box_cl.pop("bbox_confidences")
    # # writer.add_3d('points', data, step=0)
    # writer.add_3d("bboxes", to_dict_batch([box_cl]),step=1)
    # writer.add_text('bboxes', 'This is an lstm', 0)

    # mat = o3d.visualization.rendering.MaterialRecord()
    # mat.shader = "unlitLine"
    # mat.line_width = 5  # note that this is scaled with respect to pixels,
    # # so will give different results depending on the
    # # scaling values of your system
    # o3d.visualization.draw({
    #     "name": "lines",
    #     "geometry": box_cl,
    #     "material": mat
    # })
    # #writer.add_3d("color", box_cl,step=0)
    # # for step in range(3):
    # #     cube.paint_uniform_color(colors[step])
    # #     writer.add_3d('cube', data, step=step)
    # #     # cylinder.paint_uniform_color(colors[step])
    # #     # writer.add_3d('cylinder', to_dict_batch([cylinder]), step=step)
    # #     time.sleep(1)

    import numpy as np
    import open3d as o3d
    import open3d.visualization.gui as gui
    import open3d.visualization.rendering as rendering
    app = gui.Application.instance
    app.initialize()
    def make_point_cloud(npts, center, radius):
        pts = np.random.uniform(-radius, radius, size=[npts, 3]) + center
        cloud = o3d.geometry.PointCloud()
        cloud.points = o3d.utility.Vector3dVector(pts)
        colors = np.random.uniform(0.0, 1.0, size=[npts, 3])
        cloud.colors = o3d.utility.Vector3dVector(colors)
        return cloud

    points = make_point_cloud(100, (0, 0, 0), 1.0)

    vis = o3d.visualization.O3DVisualizer("Open3D - 3D Text", 1024, 768)
    vis.show_settings = True
    vis.add_geometry("Points", points)
    for idx in range(0, len(points.points)):
        vis.add_3d_label(points.points[idx], "{}".format(idx))
    vis.reset_camera_to_default()
    

    app.add_window(vis)
    app.run()


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    3. 绘制箭头

    refs

    tensorboard 联合

    可以和tensorboard融合，但是要与pip install tensorboard, 不是tensorflow的tensorboard； anaconda/bin/tensorboard 是可以的，否则出现datest not found问题

    参考文献

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  • 原文地址：https://blog.csdn.net/mingshili/article/details/124714290