• pytorch 0.4.1

• Preparation

  Download the full KITTI detection dataset. Then place a softlink (or the actual data) in M3DSSD/data/kitti*.

   cd M3DSSD
   ln -s /path/to/kitti data/kitti

  Then use the following scripts to extract the data splits, which use softlinks to the above directory for efficient storage.

  # extract the data splits
  python data/kitti_split1/setup_split.py
  
  # build  the KITTI devkit eval for each split.
  sh data/kitti_split1/devkit/cpp/build.sh

  Build the nms modules

  cd lib/nms
  make
  

  Build the DCN modules

  cd model/DCNv2
  sh ./make.sh
  

Review the configurations in scripts/config for details.

python scripts/train_rpn_3d.py --config=kitti_3d_base --exp_name base

• Tips: It is recommended to load a pre-trained model when training with feature alignment.

Modify the conf_path and weights_path to run test.

python scripts/test_rpn_3d.py

• Thanks Garrick Brazil for his great works.
• Thanks CharlesShang for his works.
• Thanks traveller59 for his works