2021-10-04 07:01:38 +00:00
|
|
|
# pointMLP-pytorch
|
|
|
|
Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
|
2021-10-04 07:26:41 +00:00
|
|
|
|
|
|
|
|
|
|
|
## Install
|
2021-10-04 07:48:33 +00:00
|
|
|
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/.
|
|
|
|
```
|
2021-10-04 07:26:41 +00:00
|
|
|
|
|
|
|
## Classification ModelNet40
|
2021-10-04 16:11:38 +00:00
|
|
|
The dataset will be automatically downloaded, directly 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.
|
|
|
|
```
|
|
|
|
|
2021-10-04 07:26:41 +00:00
|
|
|
|
|
|
|
## Classification ScanObjectNN
|
|
|
|
|
|
|
|
|
|
|
|
## Part segmentation
|