nuscenes 点云 显示
时间: 2023-08-31 20:09:46 浏览: 147
要在nuscenes中显示点云,请执行以下步骤:
1. 确保您已安装nuscenes库,并已准备好nuscenes数据集。
2. 导入必要的库:
```python
import numpy as np
from nuscenes.nuscenes import NuScenes
from nuscenes.utils.data_classes import LidarPointCloud
from nuscenes.utils.geometry_utils import transform_matrix
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
```
3. 加载nuscenes数据集并选择一辆车:
```python
nusc = NuScenes(version='v1.0-mini', dataroot='/path/to/data', verbose=True)
sample_data = nusc.sample_data[0]
ego_pose = nusc.get('ego_pose', sample_data['ego_pose_token'])
lidar_data = nusc.get('sample_data', sample_data['data']['LIDAR_TOP'])
lidar_path = nusc.get_sample_data_path(sample_data['data']['LIDAR_TOP'])
pc = LidarPointCloud.from_file(lidar_path)
```
4. 将点云从车辆坐标系转换为全局坐标系:
```python
cs_record = nusc.get('calibrated_sensor', lidar_data['calibrated_sensor_token'])
pose_record = nusc.get('ego_pose', lidar_data['ego_pose_token'])
lidar_to_ego = transform_matrix(cs_record['translation'], cs_record['rotation'])
ego_to_global = transform_matrix(pose_record['translation'], pose_record['rotation'])
lidar_to_global = np.dot(ego_to_global, lidar_to_ego)
pc.transform(lidar_to_global)
```
5. 绘制点云:
```python
fig = plt.figure(figsize=(10, 10))
ax = fig.add_subplot(111, projection='3d')
ax.set_xlim(-50, 50)
ax.set_ylim(-50, 50)
ax.set_zlim(-5, 5)
ax.scatter(pc.points[0, :], pc.points[1, :], pc.points[2, :], s=0.01, c=pc.points[2, :])
plt.show()
```
这将在一个3D图中显示点云。如果要将点云可视化为2D图像,则可以使用以下代码:
```python
fig, ax = plt.subplots(figsize=(10, 10))
ax.set_xlim(-50, 50)
ax.set_ylim(-50, 50)
ax.scatter(pc.points[0, :], pc.points[1, :], s=0.01, c=pc.points[2, :])
plt.show()
```
这将在一个2D图中显示点云。