xharlie / grid-gcn Goto Github PK
View Code? Open in Web Editor NEWGrid-GCN for Fast and Scalable Point Cloud Learning
Grid-GCN for Fast and Scalable Point Cloud Learning
Thanks for your work, it is great.
I have question about the voxel size, in your down sample part, if the voxel size is too large, there is not enough number of voxel centers, that means I cannot get M points firstly.
I think the down sample will be broken in this situation?
Am i correct or do you have some methods to solve it ?
Hi, When I use Anaconda to install mxnet=1.5.1,like Command:pip install mxnet-cu100==1.5.1,
I can run the example successfully, But when I try to find the 'mx_home', there is no those directions such as follows.
Could you tell where are those directions: ../3rdparty/..
thank you for your kind help!
dmlc_inc=${mx_home}/3rdparty/dmlc-core/include
nnvm_inc=${mx_home}/3rdparty/nnvm/include
mshadow_inc=${mx_home}/3rdparty/mshadow
dlpack_inc=${mx_home}/3rdparty/dlpack/include
mxnet_src_inc=${mx_home}/src/operator
mxnet_common_inc=${mx_home}/src/common
Hi Xharlie,
I'm trying to use grid-gcn for point cloud segmentation. From your paper it seems you trained the network using RGB- point clouds, nevertheless, I feel the code you provided deals with points only having (x, y, z) coordinates as features. I'm trying to modify the code to use other features but I'm struggling to understand the code that builds the network symbol.
I would really appreciate if you could guide me so that I can extend the code to the usage of input points with additional features, showing me what are the lines I should modify.
Thank you in advance.
hello.
I got some errors when making the file.
when I try to make the file, there is error:
/usr/bin/ld: cannot find -lmxnet
could you pls give me some instructions?
Hello! I joined CVPR2020 to talk with you but I coudln't as you don't answer me ;/
I have no choice but to write my question here so please understand me.
I'm trying to get only some(maybe 8) meaningful keypoint(such as FPS points) as below
this pic shows the detected results from KeypointNet.
(https://keypointnet.github.io/)
the Figure5 in your paper shows an example of sampled kpts on airplane and I wonder your method can detect(sample) on the same positions on the surface consistently as the above picture?
especially I want to find the keypoint on a symmetric object like a cup or a bottle.
that's really what I'm looking for! if not can you suggest an idea to achieve my goal?
I guess I need to train your model with an additional loss function like the one used in KeypointNet.
please give me some hint.
Thank you!
Hello, I'm a novice. I'm sorry to take up your time. After compiling mxnet and your gridofyop module, I was return the following error when I run the dataset:
nohup: 忽略输入
/home/christina/Grid-GCN/classification/train/../../gridifyop/additional.so
terminate called after throwing an instance of 'dmlc::Error'
what(): [10:39:56] /home/christina/incubator-mxnet/src/runtime/registry.cc:73: Check failed: override: Global PackedFunc _Integer is already registered
I don't know what to do. I just come to you when I really can't find a solution.
By the way, in the classification section of readme, you said "refer to Pointnet", it means your program need Pointnet, or it just for comparison with your results?
Thank you very much.
Hello, I'm a novice. I'm sorry to take up your time. After compiling mxnet and your gridofyop module, I was return the following error when I run the dataset:
nohup: 忽略输入
terminate called after throwing an instance of 'dmlc::Error'
what(): [10:57:02] /home/christina/apache-mxnet-src-1.5.0-incubating/include/mxnet/./tuple.h:354: Check failed: ndim >= -1 (-131976896 vs. -1) : ndim cannot be less than -1, received -131976896
Stack trace:
[bt] (0) /home/christina/Grid-GCN/classification/train/../../gridifyop/additional.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x43) [0x7ffa179ea333]
[bt] (1) /home/christina/Grid-GCN/classification/train/../../gridifyop/additional.so(mxnet::Tuple::SetDim(int)+0x1cb) [0x7ffa179eccdb]
[bt] (2) /usr/lib/libmxnet.so(dmlc::parameter::FieldEntryBase<dmlc::parameter::FieldEntry<mxnet::Tuple >, mxnet::Tuple >::GetStringValueabi:cxx11 const+0xaa) [0x7ff9eeb0c25a]
[bt] (3) /home/christina/Grid-GCN/classification/train/../../gridifyop/additional.so(dmlc::parameter::ParamManager::GetFieldInfo() const+0x2c7) [0x7ffa179ec667]
[bt] (4) /usr/lib/libmxnet.so(+0x1dda1dd) [0x7ff9ee5ed1dd]
[bt] (5) /lib64/ld-linux-x86-64.so.2(+0x10783) [0x7ffa256c7783]
[bt] (6) /lib64/ld-linux-x86-64.so.2(+0x1524f) [0x7ffa256cc24f]
[bt] (7) /lib/x86_64-linux-gnu/libc.so.6(_dl_catch_exception+0x6f) [0x7ffa2520e51f]
[bt] (8) /lib64/ld-linux-x86-64.so.2(+0x1481a) [0x7ffa256cb81a]
I don't know what to do. I just come to you when I really can't find a solution.
By the way, in the classification section of readme, you said "refer to Pointnet", it means your program need Pointnet, or it just for comparison with your results?
Thank you very much.
is random voxel sampling(RVS) strategy implemented in gridify.cu
?
i didn't found anything about the coverage aware sampling(CAS in paper).
could you please let me know where is CAS.
hope for your reply. many thanks QAQ
Hello, Thanks for sharing your codes. It is an interesting work!
To use the 3rdparty, I install mxnet=1.5.0 from the source code. I test it with an example to make sure the functions are correct.
Following the procedure suggested by the author, I change the mx_home and set the compute power as 61.
However, there is an error.
Makefile:25: recipe for target 'gridifyknn.o' failed
make: *** [gridifyknn.o] Error 1
I have no idea how to deal with it. Could you give me some advice? Thanks!
你好,请问你把这个网络调通了吗?方便留个联系方式交流一下吗
Hello, could you provide a data set modelnet10_ply_hdf5_2048, thank you very much!
Hello. I'm trying to reproduce your work. Thank you for sharing the code perfectly. But I have some problems to configure mxnet(Not sure, maybe).
Currently, I use the docker image from Nvidia. (https://ngc.nvidia.com/catalog/containers/nvidia:mxnet)
It seems your gridifyop
need headers on 3rdparty
, src
and include
to build. So I added apache/incubator-mxnet on my workspace with following command.
git clone -b 1.5.0 --recursive https://github.com/apache/incubator-mxnet mxnet
And I update Makefile
as the following image.
Then, I got an error like the followings.
$ CUDA_VISIBLE_DEVICES=1 python -u train/train_gpu_ggcn_mdl40.py > .
./../GAPCN/GridGCN_v1_20200921/mdl40.log
terminate called after throwing an instance of 'std::bad_alloc'
what(): std::bad_alloc
Aborted (core dumped
Now, I have some questions.
Thank you :)
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.