
The test requires only 12GB GPU memory, while the training needs at least 40GB GPU memory. When the batch_size is less than 4 during training, it will seriously affect the convergence effect. We train 150 epochs by default and enable train.py line 82-83 to produce better results.

### Preparation

Download [S3DIS](http://buildingparser.stanford.edu/dataset.html) and unzip it. We use Stanford3dDataset_v1.2_Aligned_Version.

Set the dataset path according to prepare_s3dis.py (don't run it, read the top lines).

Then run prepare_s3dis.py to process raw data into tensors. Fix illegal characters and rerun if necessary.

```bash
python prepare_s3dis.py
```
