VoxelNet-tensorflow
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A 3D object detection system for autonomous driving.
VoxelNet-tensorflow
A tensorflow implementation for VoxelNet.
Requirement
Python 3.5+tensorflow 1.4+NumPy, etc.
Usage
- have a look at
config.pyfor model configurations, split your data into test/train set by this. - run
setup.pyto build the Cython module.
$ python setup.py build_ext --inplace
- make sure your working directory looks like this (some files are omitted):
├── 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
- run
train.py. Some cmdline parameters is needed, just checktrain.pyfor them. - launch a tensorboard and wait for the training result.
Data augmentation
Since c928317, data augmentation is done in an online manner, so there is no need for generating augmented samples.
Result
TBD
Acknowledgement
Thanks to @ring00 for the implementation of VFE layer and Jialin Zhao for the implementation of the RPN.
License
MIT