# pointMLP-pytorch Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework ## Install Please ensure that python3.7+ is installed. We suggest user use conda to create a new environment. Install dependencies ```bash pip install -r requirement.txt ``` Install CUDA kernels ```bash pip install pointnet2_ops_lib/. ``` ## Classification ModelNet40 The dataset will be automatically downloaded, run following command to train ```bash # train pointMLP python main.py --model pointMLP # train pointMLP-elite python main.py --model pointMLPElite # please add other paramemters as you wish. ``` By default, it will create a fold named "checkpoints/{modelName}-{msg}-{randomseed}", which includes args.txt, best_checkpoint.pth, last_checkpoint.pth, log.txt, out.txt. To conduct voting experiments, run ```bash # please modify the msg accrodingly python voting.py --model pointMLP --msg demo ``` ## Classification ScanObjectNN ## Part segmentation