ispc-lab / lidar4d Goto Github PK

Hi, thank you for your good paper with beautiful code. I want to know how to train and test (data split) on the NuScenes dataset, and would you consider releasing the corresponding code?

In your readme.md, you mentioned SEQ_IDs such as 2350, 4950, 8120, 10200, 10750, 11400. How do I obtain these? I directly downloaded the Raw Velodyne Scans data, but it seems that I didn't see any information about SEQ_IDs.

The official website provides the following information:


So, are my SEQ_IDs 0000, 0002, 0003, 0004, and 0005?"

Thanks for your works. I'm testing on KITTI-360, I found the synthesized point stored as .npy. So I use this to convert it to pcd.

import numpy as np
import open3d as op

path = "./log/kitti360_lidar4d_f4950_release/results/test_lidar4d_ep0639_0002_depth_lidar.npy"
points = np.load(path)
print(points.shape,points[:10])
pcd = op.geometry.PointCloud()
pcd.points = op.utility.Vector3dVector(points)
op.io.write_point_cloud("2.pcd",pcd)

But it looks like the depths are wrong. Below image is captured from pcl_viewer

Below image is corresponding depth map

This is the output of evaluation

Could you please help me find where is wrong?

在按照教程进行安装的过程中，出现了nvcc: not found的错误。ubuntu20.04之前没有安装过cuda，但是这里却出现了这种错误

(lidar4d) supercoconut@supercoconut:~/Myfile/LiDAR4D/tiny-cuda-nn/bindings/torch$ python setup.py install
/home/supercoconut/Myfile/LiDAR4D/tiny-cuda-nn/bindings/torch/setup.py:5: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html
from pkg_resources import parse_version
Building PyTorch extension for tiny-cuda-nn version 1.7
Obtained compute capability 89 from PyTorch
sh: 1: nvcc: not found
Targeting C++ standard 14
running install
/home/supercoconut/anaconda3/envs/lidar4d/lib/python3.9/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
!!

    ********************************************************************************
    Please avoid running ``setup.py`` directly.
    Instead, use pypa/build, pypa/installer or other
    standards-based tools.

    See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
    ********************************************************************************

!!
self.initialize_options()
/home/supercoconut/anaconda3/envs/lidar4d/lib/python3.9/site-packages/setuptools/_distutils/cmd.py:66: EasyInstallDeprecationWarning: easy_install command is deprecated.
!!

    ********************************************************************************
    Please avoid running ``setup.py`` and ``easy_install``.
    Instead, use pypa/build, pypa/installer or other
    standards-based tools.

    See https://github.com/pypa/setuptools/issues/917 for details.
    ********************************************************************************

!!
self.initialize_options()
running bdist_egg
running egg_info
creating tinycudann.egg-info
writing tinycudann.egg-info/PKG-INFO
writing dependency_links to tinycudann.egg-info/dependency_links.txt
writing top-level names to tinycudann.egg-info/top_level.txt
writing manifest file 'tinycudann.egg-info/SOURCES.txt'
/home/supercoconut/anaconda3/envs/lidar4d/lib/python3.9/site-packages/torch/utils/cpp_extension.py:502: UserWarning: Attempted to use ninja as the BuildExtension backend but we could not find ninja.. Falling back to using the slow distutils backend.
warnings.warn(msg.format('we could not find ninja.'))
reading manifest file 'tinycudann.egg-info/SOURCES.txt'
writing manifest file 'tinycudann.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
creating build
creating build/lib.linux-x86_64-cpython-39
creating build/lib.linux-x86_64-cpython-39/tinycudann
copying tinycudann/modules.py -> build/lib.linux-x86_64-cpython-39/tinycudann
copying tinycudann/init.py -> build/lib.linux-x86_64-cpython-39/tinycudann
copying tinycudann/bindings.cpp -> build/lib.linux-x86_64-cpython-39/tinycudann
running build_ext
error: [Errno 2] No such file or directory: '/usr/local/cuda/bin/nvcc'

Hi,

This is excellent work. I am very grateful for your sharing.
However, I see that the experiments were conducted by training and testing on each sequence individually. How were the final metrics obtained? In other words, were all the experiments in this paper conducted using scene 4950 from the sequence 2013_05_28_drive_0000 for both training and testing? Or were there other setups?

对于kitti360数据集，在生成rangeview的过程中，你设置pano height=66, pano width=1030, 想问下这个是怎么得到的，因为我想要用我自己的lidar数据，这两个参数是和什么有关

Hi,

I'm very interested in your work.
I noticed that the code only uses the sequence 2013_05_28_drive_0000, and the frame splitting is hard-coded.

My questions are:

1. Are the results in the paper evaluated on 2013_05_28_drive_0000 or all sequences?
2. If they are evaluated on all sequences, how is the frame splitting done?

data/preprocess/generate_rangeview.py, line 73

same file, line 112