A small framework created to compare some SOTA online action detection methods, with focus on appliance in ADAS and ADS.

Consider using conda or Docker to isolate your other projects or applications you use. Take a note, that Python version must be 3.11 for this setup.

1. Install the proper PyTorch wheel for your hardware:
   • CUDA / CPU
   • XPU
2. Run pip install -r requirements.txt to install basic requirements
3. Run python setup/get_mmaction2.py to install MMAction2
4. (optional) Download ROAD_Waymo from here
   • Download videos and road_waymo_trainval_v1.0.json with gsutil, and place these files in ./data/road_waymo

     mkdir "data/road_waymo"
     cd "data/road_waymo"
     gcloud auth login
     gsutil -m cp -r "gs://waymo_open_dataset_road_plus_plus/road_waymo_trainval_v1.0.json" "gs://waymo_open_dataset_road_plus_plus/videos" .
     cd ../..

     You need to register yourself and accept terms of use before downloading.
5. Run python setup/get_road.py
   • ./data/ file structure should be following (including ROAD_Waymo):

     road-waymo/
         - road_trainval_v1.0.json
         - videos/
             - 2014-06-25-16-45-34_stereo_centre_02.mp4
             - 2014-06-26-09-53-12_stereo_centre_02.mp4
             - 2014-07-14-14-49-50_stereo_centre_01.mp4
             ...
     road-waymo/
         - road_waymo_trainval_v1.0.json
         - videos/
             - Train_00000.mp4
             - Train_00001.mp4
             - Train_00002.mp4
             ...