This repository provides the code for our paper Machining tool identification utilizing temporal 3D point clouds
Please consider citing this work if you find it influential or useful in your research.
@article{Zoumpekas2023JIMS,
author = {Zoumpekas, Thanasis and Leutgeb, Alexander and Puig, Anna and Salamó, Maria},
title = {Machining tool identification utilizing temporal 3D point clouds},
journal = {Journal of Intelligent Manufacturing},
doi = {10.1007/s10845-023-02093-5},
year = {2023}
}
Please install Python Poetry. Then simply run (inside the project directory):
poetry install
poetry shell
pip install torch==1.12.1+cu102 torchvision==0.13.1+cu102 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu102
The code was tested with CUDA 10.2 and PyTorch 1.12.1 on Ubuntu Linux 20.04.
If all the dependencies installed correctly then you can train and test new models from scratch.
The temporal 3D point clouds are available here: (TPCOMP dataset) https://doi.org/10.34810/data205
- 16 Tools Large Dataset: Please put it under
data/16_Tools_Large_Dataset/
- 16 Tools Small Dataset: Please put it under
data/16_Tools_Small_Dataset/
python train_classification_tools_L --model pointnet_cls --batch_size 8
python test_classification_tools_L --log_dir "path_to_trained_model_log"
Our code is mainly based on the following repository: https://github.com/yanx27/Pointnet_Pointnet2_pytorch
MIT License.