目录
bin格式mayavi 效果好
1.安装依赖库 python3.10 ok
pip install PyQt5
pip install vtk
pip install mayavi -i https://pypi.tuna.tsinghua.edu.cn/simple
2. bin文件可视化 ok
import mayavi.mlab
import numpy as np
import os
def viz_mayavi(points, vals="distance"): # 可视化只用到了3维数据(x,y,z)！
x=points[:, 0]
y=points[:, 1]
z=points[:, 2]
r=points[:, 3] # reflectance value of point
d=np.sqrt(x**2+y**2)
if vals == "height":
col = z
else:
col = d
# 创建可视化模板的尺寸
fig=mayavi.mlab.figure(bgcolor=(0, 0, 0), size=(1280, 720))
mayavi.mlab.points3d(x, y, z,
col,
mode="point",
colormap='spectral',
figure=fig,
)
mayavi.mlab.show()
if __name__ == "__main__":
bin_file_path = 'bin_2pcd'
bin_files = os.listdir(bin_file_path)
for bin_file in bin_files:
if bin_file.endswith(".bin"):
mypointcloud = np.fromfile(bin_file_path + '/' + bin_file, dtype=np.float32, count=-1).reshape([-1, 4])
viz_mayavi(mypointcloud,vals="height")npy可视化
import numpy as np
from mayavi import mlab
# 加载npy文件
data = np.load('0001.npy')
# 可视化数据
src = mlab.pipeline.scalar_field(data)
mlab.pipeline.iso_surface(src, contours=[data.min() + 0.1 * data.ptp(), ], opacity=0.5)
mlab.show()open3d可视化：
成功可视化bin文件
import math
import numpy as np
import struct
import os
import open3d as o3d
def read_velodyne_bin(path):
pc_list = []
with open(path, 'rb') as f:
content = f.read()
pc_iter = struct.iter_unpack('ffff', content)
for idx, point in enumerate(pc_iter):
pc_list.append([point[0], point[1], point[2]])
return np.asarray(pc_list, dtype=np.float32)
def show_point(data):
pcd = o3d.geometry.PointCloud()
# pcd.points = o3d.utility.Vector3dVector(origin)
# o3d.visualization.draw_geometries([pcd])
pcd.points = o3d.utility.Vector3dVector(data)
o3d.visualization.draw_geometries([pcd])
def main():
root_dir = r'\\tsclient\velodyne' # 激光雷达bin文件路径
cat = os.listdir(root_dir)
iteration_num = len(cat)
for i in range(iteration_num):
filename = os.path.join(root_dir, cat[i])
db_np = read_velodyne_bin(filename)
show_point(db_np)
if __name__ == '__main__':
main()参考：Open3d显示点云数据_open3d 加载bin代码-CSDN博客
显示3d box
import open3d as o3d
import numpy as np
# 创建一个缩小一半的3D盒子
def create_half_size_3d_box():
vertices = [
[0, 0, 0],
[0.5, 0, 0],
[0.5, 0.5, 0],
[0, 0.5, 0],
[0, 0, 0.5],
[0.5, 0, 0.5],
[0.5, 0.5, 0.5],
[0, 0.5, 0.5]
]
lines = [
[0, 1], [1, 2], [2, 3], [3, 0],
[4, 5], [5, 6], [6, 7], [7, 4],
[0, 4], [1, 5], [2, 6], [3, 7]
]
colors = [
[1, 0, 0] for _ in range(len(lines))
]
line_set = o3d.geometry.LineSet()
line_set.points = o3d.utility.Vector3dVector(vertices)
line_set.lines = o3d.utility.Vector2iVector(lines)
line_set.colors = o3d.utility.Vector3dVector(colors)
return line_set
# 显示缩小一半的3D盒子，并将盒子最小化显示在窗口中
def show_half_size_3d_box_with_minimized_display():
half_size_box = create_half_size_3d_box()
# 设置摄像机参数
vis = o3d.visualization.Visualizer()
vis.create_window(window_name='Open3D', width=800, height=600)
render_option = vis.get_render_option()
render_option.background_color = np.asarray([0, 0, 0]) # 设置背景色为黑色 RGB=[0,0,0]
ctr = vis.get_view_control()
params = ctr.convert_to_pinhole_camera_parameters()
intrinsic = params.intrinsic
intrinsic.set_intrinsics(400, 300, 525, 525, 200, 150) # 设置视角范围
ctr.convert_from_pinhole_camera_parameters(params)
vis.add_geometry(half_size_box)
vis.run()
vis.destroy_window()
show_half_size_3d_box_with_minimized_display()npy可视化
matplotlib可视化
import numpy as np
import matplotlib.pyplot as plt
depthmap = np.load('0000.npy') #使用numpy载入npy文件
plt.imshow(depthmap) #执行这一行后并不会立即看到图像，这一行更像是将depthmap载入到plt里
plt.savefig('depthmap.jpg') #执行后可以将文件保存为jpg格式图像，可以双击直接查看。也可以不执行这一行，直接执行下一行命令进行可视化。但是如果要使用命令行将其保存，则需要将这行代码置于下一行代码之前，不然保存的图像是空白的
plt.show() #在线显示图像