MinkowskiEngine语义分割

MinkowskiEngine是一个用于高效处理稀疏张量的PyTorch库。它可以用于许多任务，包括语义分割。以下是MinkowskiEngine语义分割的示例代码：

1.安装Open3D和open3d-python

pip install open3d
pip install open3d-python

2.加载数据并体素化（量化）数据

import open3d as o3d
import numpy as np
from MinkowskiEngine import SparseTensor, MinkowskiConvolution

# 加载点云数据
pcd = o3d.read_point_cloud(file_name)
coords = np.array(pcd.points)
feats = np.array(pcd.colors)

# 体素化数据
quantization_size = 0.05
coords = np.floor(coords / quantization_size)
coords = coords - coords.min(0)
print('Voxelization')
print('Point cloud has {} points'.format(coords.shape[0]))
print('Voxel size is {}'.format(quantization_size))
print('Voxelizing...')
coords = coords[:, [2, 1, 0]]
voxel_size = np.array([quantization_size, quantization_size, quantization_size])
padded_voxel_size = voxel_size + [0.2, 0.2, 0.2]
quantized_coords = (coords / voxel_size).astype(int)
print('Computing occupancies...')
occupancies = np.zeros(quantized_coords.max(0) + 1, dtype=bool)
occupancies[tuple(quantized_coords.T)] = True
print('Done.')

3.创建稀疏张量并进行卷积

# 创建稀疏张量
print('Creating sparse tensor...')
tensor_stride = 1
sp_tensor = SparseTensor(
    feats, coords=quantized_coords, tensor_stride=tensor_stride)

# 进行卷积
print('Convolving...')
kernel_size = 3
conv = MinkowskiConvolution(
    in_channels=3,
    out_channels=32,
    kernel_size=kernel_size,
    stride=1,
    dilation=1,
    bias=True)
output = conv(sp_tensor)
print('Done.')