We follow the procedure in [votenet](https://github.com/facebookresearch/votenet/).
1. Download SUNRGBD v2 data [HERE](http://rgbd.cs.princeton.edu/data/)(SUNRGBD.zip, SUNRGBDMeta2DBB_v2.mat, SUNRGBDMeta3DBB_v2.mat) and the toolkits (SUNRGBDtoolbox.zip). Move all the downloaded files under OFFICIAL_SUNRGBD. Unzip the zip files.
1. Download SUNRGBD v2 data [HERE](http://rgbd.cs.princeton.edu/data/). Then, move SUNRGBD.zip, SUNRGBDMeta2DBB_v2.mat, SUNRGBDMeta3DBB_v2.mat and SUNRGBDtoolbox.zip to the OFFICIAL_SUNRGBD folder, unzip the zip files.
2. Extract point clouds and annotations (class, v2 2D -- xmin,ymin,xmax,ymax, and 3D bounding boxes -- centroids, size, 2D heading) by running`extract_split.m`, `extract_rgbd_data_v2.m` and `extract_rgbd_data_v1.m`under the `matlab` folder.
2. Enter the `matlab` folder, run`extract_split.m`, `extract_rgbd_data_v2.m` and `extract_rgbd_data_v1.m`to extract point clouds and annotations.
3.Prepare data by running `python sunrgbd_data.py --gen_v1_data`
3.Back to this level, prepare data by running `python sunrgbd_data.py --gen_v1_data`
4. 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`.
