Code for Data Preprocessing of Argoverse Dataset

-> Also official data preprocessing for paper "Multimodal Motion Prediction with Stacked Transformers. (CVPR 2021)"

-> The preprocessing code is modified from this repository. Ensure the same dependencies.

Usage

0. Install Argoverse-api. Download HD-maps in argoverse-api as instructed.

1. Prepare raw Argoverse dataset:

   Put all data (folders named train/val/test or a single folder sample) in data folder.

   An example folder structure:

   data - train - *.csv
        \        \ ...
         \
          \- val - *.csv
           \       \ ...
            \
             \- test - *.csv
                      \ ...
   

2. Modify the config file utils/config.py. Use the proper env paths and arguments.

3. Feature preprocessing, save intermediate data input features (compute_feature_module.py)

   $ python compute_feature_module.py
   

Result Intermediate Data (Per Case)

Data format

Note!

We do not do any data augumentation (e.g. rotation) here to normalize the scene. The preprocessing code is to derive informative intermediate data from Argoverse API (without any transform).