ModelNet40 cls demo

This repo is a unofficial implementations for classification on ModelNet40

Install

The latest codes are tested on CUDA10.1, PyTorch 1.6 and Python 3.7:

conda install pytorch==1.6.0 cudatoolkit=10.1 -c pytorch

Classification (ModelNet40)

Data Preparation

Download alignment ModelNet here

Split ModelNet40 into train set, validation set and test set.

Default split ratio (train set : validation set : test set = 0.8 : 0.1 : 0.1)

python ./dataset/data_split.py --dataset_path <ModelNet40 path> --split_ratio <split_ratio>

Run

You can run PointNet or PointNet++ on ModelNet40 cls task.

• use --model pointnet++ or --model pointnet

Training

python ./train.py --model <model_name> --dataset_path <ModelNet40 path> --batchSize <batchsize> --nepoch <epoch_num>

Support Models

• PointNet
• PointNet++
• PointCNN
• DGCNN
• PCT

Performance

Our results are got by 30 epochs training.

Model	Accuracy
PointNet (Official without T-Net)	87.1
PointNet2 (Official)	91.9
PointNet (Pytorch without normal and T-Net)	88.6
PointNet2_MSG (Pytorch without normal)	91.9

Reference

fxia22/pointnet.pytorch
yanx27/Pointnet_Pointnet2_pytorch

Environments

see requirement.txt