A 3D object detection system for autonomous driving.
A tensorflow implementation for VoxelNet.
Python 3.5+
tensorflow 1.4+
NumPy
, etc.config.py
for model configurations, split your data into test/train set by this.setup.py
to build the Cython module.$ python setup.py build_ext --inplace
├── build <-- Cython build file
├── model <-- some src files
├── utils <-- some src files
├── setup.py
├── config.py
├── test.py
├── train.py
├── train_hook.py
├── README.md
└── data <-- KITTI data directory
└── object
├── training <-- training data
| ├── image_2
| ├── label_2
| └── velodyne
└── testing <--- testing data
├── image_2
├── label_2
└── velodyne
train.py
. Some cmdline parameters is needed, just check train.py
for them.Since c928317, data augmentation is done in an online manner, so there is no need for generating augmented samples.
TBD
Thanks to @ring00 for the implementation of VFE layer and Jialin Zhao for the implementation of the RPN.
MIT