Data preparation guide

ScanNetV2 dataset

1) Download the ScanNetV2 dataset.

2) Put the downloaded scans and scans_test folder as follows.

ISBNet
├── dataset
│   ├── scannetv2
│   │   ├── scans
│   │   ├── scans_test

3) Split and preprocess data

cd ISBNet/dataset/scannetv2
bash prepare_data.sh

The script data into train/val/test folder and preprocess the data. After running the script the scannet dataset structure should look like below.

ISBNet
├── dataset
│   ├── scannetv2
│   │   ├── scans
│   │   ├── scans_test
│   │   ├── train
│   │   ├── val
│   │   ├── test
│   │   ├── superpoints

ScanNetV2-200 dataset

1) Download the new scannetv2-labels.combined.tsv from ScanNetV2 and put it to folder dataset/scannet200.

2) Split and preprocess data

cd ISBNet/dataset/scannet200
bash prepare_data.sh

The script data into train/val/test folder and preprocess the data. After running the script the scannet200 dataset structure should look like below.

ISBNet
├── dataset
│   ├── scannet200
│   │   ├── train
│   │   ├── val
│   │   ├── test
│   │   ├── superpoints

S3DIS dataset

1) Download the S3DIS dataset (v1.2_Aligned_Version).

2) Download the preprocessed superpoints from Box2Mask: superpoints and organize as below.

ISBNet
├── dataset
│   ├── s3dis
│   │   ├── Stanford3dDataset_v1.2_Aligned_Version
│   │   │   ├── Area_1
│   │   │   │   ├── hallway_1 
│   │   │   │   │   ├── Annotations # Contains instances information 
│   │   │   │   │   │   ├── door_2.txt 
│   │   │   │   │   │   ├── floor_1.txt
│   │   │   │   │   │   ├── wall_2.txt
│   │   │   │   │   │   ├── ...
│   │   │   │   │   ├── hallway_1.txt # Contains positions and colors of scene points
│   │   │   │   ├── office_1
│   │   │   │   ├── ...
│   │   │   ├── Area_2
│   │   │   ├── Area_3
│   │   │   ├── Area_4
│   │   │   ├── Area_5
│   │   │   ├── Area_6
│   │   ├── learned_superpoin_graph_segmentations

3) Preprocess data

cd ISBNet/dataset/s3dis
bash prepare_data.sh

After running the script the scannet dataset structure should look like below.

ISBNet
├── dataset
│   ├── s3dis
│   │   ├── Stanford3dDataset_v1.2_Aligned_Version
│   │   ├── learned_superpoin_graph_segmentations
│   │   ├── preprocess
│   │   ├── superpoints

STLPS3D dataset

1) Download the STPLS3D dataset.

2) Put Synthetic_v3_InstanceSegmentation.zip to dataset/stpls3d and unzip.

3) Preprocess data

cd ISBNet/dataset/stpls3d
bash prepare_data.sh

After running the script the scannet dataset structure should look like below.

ISBNet
├── dataset
│   ├── stpls3d
│   │   ├── train
│   │   ├── val