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pytorch 0.4.1
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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