voxel_gen.py

# Copyright 2021 Yan Yan
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import numpy as np 

from cumm import tensorview as tv 
from spconv.utils import Point2VoxelCPU3d


def main():
    # voxel gen source code: spconv/csrc/sparse/pointops.py
    gen = Point2VoxelCPU3d(
        vsize_xyz=[0.1, 0.1, 0.1], 
        coors_range_xyz=[-80, -80, -2, 80, 80, 6], 
        num_point_features=3, 
        max_num_voxels=5000, 
        max_num_points_per_voxel=5)

    pc = np.random.uniform(-10, 10, size=[1000, 3])
    pc_tv = tv.from_numpy(pc)
    # generate voxels, note that voxels_tv reference to a persistent buffer in generator,
    # so we can't run it in multi-thread.
    voxels_tv, indices_tv, num_p_in_vx_tv = gen.point_to_voxel(pc_tv)
    voxels_np = voxels_tv.numpy_view()
    indices_np = indices_tv.numpy_view()
    num_p_in_vx_np = num_p_in_vx_tv.numpy_view()
    print("------Raw Voxels-------")
    print(voxels_np[0])
    # run voxel gen and FILL MEAN VALUE to voxel remain
    voxels_tv, indices_tv, num_p_in_vx_tv = gen.point_to_voxel_empty_mean(pc_tv)
    voxels_np = voxels_tv.numpy_view()
    indices_np = indices_tv.numpy_view()
    num_p_in_vx_np = num_p_in_vx_tv.numpy_view()
    print("------Voxels with mean filled-------")
    print(voxels_np[0])

if __name__ == "__main__":
    main()