Prepare SUN RGB-D Data

We follow the procedure in votenet.

1. Download SUNRGBD data HERE. Then, move SUNRGBD.zip, SUNRGBDMeta2DBB_v2.mat, SUNRGBDMeta3DBB_v2.mat and SUNRGBDtoolbox.zip to the OFFICIAL_SUNRGBD folder, unzip the zip files.

2. Enter the matlab folder, Extract point clouds and annotations by running extract_split.m, extract_rgbd_data_v2.m and extract_rgbd_data_v1.m.

3. Enter the project root directory, Generate training data by running

python tools/create_data.py sunrgbd --root-path ./data/sunrgbd --out-dir ./data/sunrgbd --extra-tag sunrgbd

The overall process could be achieved through the following script

cd matlab
matlab -nosplash -nodesktop -r 'extract_split;quit;'
matlab -nosplash -nodesktop -r 'extract_rgbd_data_v2;quit;'
matlab -nosplash -nodesktop -r 'extract_rgbd_data_v1;quit;'
cd ../../..
python tools/create_data.py sunrgbd --root-path ./data/sunrgbd  --out-dir ./data/sunrgbd --extra-tag sunrgbd

NOTE: SUNRGBDtoolbox.zip should have MD5 hash 18d22e1761d36352f37232cba102f91f (you can check the hash with md5 SUNRGBDtoolbox.zip on Mac OS or md5sum SUNRGBDtoolbox.zip on Linux)

NOTE: If you would like to play around with ImVoteNet, the image data (./data/sunrgbd/sunrgbd_trainval/image) are required. If you pre-processed the data before mmdet3d version 0.12.0, please pre-process the data again due to some updates in data pre-processing

NOTE: Before mmdet3d version 1.0.0 we sampled 50000 points following VoteNet preprocessing. On training and evaluation we use PointSample to sample the amount of points needed for each detector e.g. 20000 for VoteNet and GroupFree. However, modern voxel-based detectors (e.g. FCAF3D) utilize 100000 points and are able to utilize all of them. So since 1.0.0 version we do not limit the maximum number of points during preprocessing, giving the users more flexibility with PointSample. If you have some reasons to keep only 50000 points here please set --num-points=50000 for create_data.py.

The directory structure after pre-processing should be as below

sunrgbd
├── README.md
├── matlab
│   ├── extract_rgbd_data_v1.m
│   ├── extract_rgbd_data_v2.m
│   ├── extract_split.m
├── OFFICIAL_SUNRGBD
│   ├── SUNRGBD
│   ├── SUNRGBDMeta2DBB_v2.mat
│   ├── SUNRGBDMeta3DBB_v2.mat
│   ├── SUNRGBDtoolbox
├── sunrgbd_trainval
│   ├── calib
│   ├── depth
│   ├── image
│   ├── label
│   ├── label_v1
│   ├── seg_label
│   ├── train_data_idx.txt
│   ├── val_data_idx.txt
├── points
├── sunrgbd_infos_train.pkl
├── sunrgbd_infos_val.pkl