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Data pipeline

You can download the data used in our paper directly. Or you can try to reproduce the data from scratch.

The final data structure of datasets/ is as follows:

datasets
├── data_transform.py
├── nr3d
│   ├── nr3d.csv   (optional)
│   └── nr3d_sa.csv
├── README.md
├── scannet -> /PATH/TO/SCANNET
│   ├── instruct-insertion
│   ├── scannetv2-labels.combined.tsv
│   ├── scans
│   ├── scans_test
│   └── tasks
└── sr3d
│   ├── sr3d+.csv   (optional)
    └── sr3d+_sa.csv

Download ScanNet data

First, go to ScanNet Repo and get their downloading script as instruct-insertion/scripts/download_scannet.py. We did not include the complete script in our repo because ScanNet is released under their Term of Use, not MIT license.

We modified the script to remove unnecessary data. Make sure the following lines in instruct-insertion/scripts/download_scannet.py:

FILETYPES = [
    ".aggregation.json",
    # ".sens",
    ".txt",
    # "_vh_clean.ply",
    "_vh_clean_2.0.010000.segs.json",
    "_vh_clean_2.ply",
    # "_vh_clean.segs.json",
    # "_vh_clean.aggregation.json",
    "_vh_clean_2.labels.ply",
    # "_2d-instance.zip",
    # "_2d-instance-filt.zip",
    # "_2d-label.zip",
    # "_2d-label-filt.zip",
]

Since the ScanNet dataset is large, we recommend you to create datasets/scannet as a soft link to somewhere in the HDD before running our downloading script.

python instruct-insertion/scripts/download_scannet.py -o datasets/scannet

After the ScanNet is downloaded, preprocess the data by running:

bash instruct-insertion/scripts/preprocess_scannet_data.sh

Context-aware Indoor PCG data

Donwload from Google Drive

The Sr3D-SA and Nr3D-SA datasets can be downloaded from the Google Drive.

Put them under datasets/sr3d and datasets/nr3d respectively.

Build from source

If you want to build the data from source, you should set up ReferIt3D dataset and OpenAI API Token first.

Download ReferIt3D dataset:

pushd datasets
# Download Nr3D
gdown https://drive.google.com/file/d/1qswKclq4BlnHSGMSgzLmUu8iqdUXD8ZC/view?usp=drive_link -O nr3d/nr3d.csv
# Download Sr3D+
gdown https://drive.google.com/file/d/1kcxscHp8yA_iKLT3BdTNghlY3SBfKAQI/view?usp=drive_link -O sr3d/sr3d+.csv
popd

Check datasets/data_transform.py for more details.