lipan
29f1d45d66
算法更新: delivery v1.2.1、平整度v1.5、测距v2.2、整车配准v1.3 适配器: vehicle-registration 新增、各算法 manifest 和 adapter 更新 后端: taskCadFiles/source 字段迁移、derivedPointClouds 注册、取消任务联动 前端: ElapsedTime 时长显示、两步算法流程、canRun 逻辑修复 文档: 新增5份算法性能分析报告
30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
from __future__ import annotations
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import copy
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import numpy as np
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import open3d as o3d
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class GaussianNoiseAdder:
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"""Add Gaussian noise to an Open3D point cloud."""
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def __init__(self, noise_std: float = 4.0, seed: int | None = None) -> None:
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self.noise_std = noise_std
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self.seed = seed
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def apply(self, pointcloud: o3d.geometry.PointCloud) -> o3d.geometry.PointCloud:
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noisy = copy.deepcopy(pointcloud)
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points = np.asarray(noisy.points)
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rng = np.random.default_rng(self.seed)
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noise = rng.normal(0, self.noise_std, points.shape)
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noisy.points = o3d.utility.Vector3dVector(points + noise)
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return noisy
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def noise_level(self, clean: o3d.geometry.PointCloud, noisy: o3d.geometry.PointCloud) -> float:
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clean_points = np.asarray(clean.points)
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noisy_points = np.asarray(noisy.points)
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if clean_points.shape != noisy_points.shape:
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raise ValueError("Clean and noisy point clouds must have the same point count.")
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return float(np.mean(np.linalg.norm(noisy_points - clean_points, axis=1)))
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