Comments (3)
Hi @chqzeng, thanks for you interest in the project !
I have some point cloud in ( x, y, z, intensity) format, can I use one of the existing model
s3dis
do the training and apply to my custom dataset? which script should I use or modify from?
This will depend on your dataset :
- S3DIS: indoor scenes of a university acquired with a Matterport tripod, has RGB colorization
- KITTI-360: outdoor urban scenes acquired with a LiDAR sensor on a vehicle, has RGB colorization
- DALES: aerial urban scenes acquired with a LiDAR sensor on a plane, has intensity colorization
my dataset is quite special (like cup shapes), do I necessarily need some custom training? , If I need to prepare training dataset, what is the format I need to prepare?
For creating your own dataset, please refer to the Dataset. If you have ( x, y, z, intensity) attributes, you might want to get inspiration from DALES too. I draw your attention to the fact that SPT is primarily designed for dealing with large 3D scenes with multiple objects of complex geometry. If by "cup shapes" you mean your dataset is composed of isolated objects (à la ModelNet), then this project may be a little overkill for your needs... I don't know what your task is but have you tried a simple PointNet or PointNet++ first ?
run command:
python src/train.py experiment=s3dis_11g datamodule.fold=5
run command: `python src/eval.py experiment=s3dis datamodule.fold=5 ckpt_path=/path/to/your/checkpoint.ckpt``
Both errors seem connected, there seems to be a problem when reading the raw files. This process is done in parallel, to save time (reading S3DIS file format is quite laborious). From the tracebacks you share, I cannot interpret what is happening. Two suggestions:
- You may have an incorrect dataset file structure: make sure you downloaded and organized the S3DIS dataset as described here
- You may encounter multi-processing issues. This can happen on certain machines. See this issue. To check if multi-processing is the problem, you can try manually setting
processes=1
in these lines.
Best,
Damien
from superpoint_transformer.
Thank you Damien for the quick and detailed feedback.
I am not very familiar with your current data processing flow here, so yes I will take some time to look into the Dataset preparation info you provide. my data is close to the Dales, not a single cup, but a relative complicated scene with many culvert pipes for road construction with pebbles in background. I would like to try your model most for its "light-weight" with less parameter size.
For the running error, I confirm the data structure is correct, and tried to set the processes=1
still have the issue. I am running in Windows subsystem for Linux (WSL). I am not sure whether that is the reason.
the /etc/shm
is 16GB
I attached two new runs on two difference machine, both as WSL, and failed log. if you have some idea about why cause the error, then largely appreciated.
WSL_run_log.txt
WSL_run_log2.txt
thanks ,
Chui
from superpoint_transformer.
I can't provide much support for Windows-based machines, or docker environment, etc. The code was only tested on linux machines.
Looking at your second log file:
RuntimeError: DataLoader worker (pid 10844) is killed by signal: Bus error. It is possible that dataloader's workers are out of shared memory. Please try to raise your shared memory limit.
It seems you have CPU RAM memory issues, not just GPU memory issues. Check out this issue for directions.
PS: if you are interested in this project, don't forget to give it a ⭐, it matters to us !
from superpoint_transformer.
Related Issues (20)
- Project root directory not found. Indicators: ('.project-root', 'setup.cfg', 'setup.py', '.git', 'pyproject.toml') HOT 6
- Where can I get pretrained model? HOT 1
- About Superpoint-Graphs Computation HOT 1
- how to use the network for semantic segmentation? HOT 5
- OutOfMemoryError when run eval.py HOT 5
- Can't resolve OOM Error caused by FRNN HOT 3
- RuntimeError: DataLoader worker (pid 15163) is killed by signal: Bus error. It is possible that dataloader's workers are out of shared memory. Please try to raise your shared memory limit HOT 8
- Evaluation on KITTI-360 Test set HOT 1
- RANSAC Error on Custom Dataset HOT 3
- custom dataset problem HOT 1
- Prediction without sampling HOT 4
- Implementing SensatUrban HOT 4
- Custom Dataset Index Error HOT 8
- How to find `state_dict` in a `.ckpt` file ? HOT 3
- NAG.select() reveals `torch-geometric>=2.4` backward compatibility error HOT 4
- How to get the Superpoint Partitions of every room in S3DIS HOT 6
- nag.select().save() RuntimeError HOT 7
- Implementing PyTorch Lightning `predict` behavior HOT 7
- Empty tensor when running inference on custom dataset HOT 3
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