Reproducing VoxelNet from Apple, forked from https://github.com/jeasinema/VoxelNet-tensorflow Adding YOLO-structure

Log: Aug 13, 2018, Monday

• python 3.5
• tensorflow 1.4
• numpy
• opencv

[root]
 data       : kitti dataset( : should be linked to your original kitti dataset)
 model      : model
 utils      : utils files
 
 and some files such as data_aug, evaluate_object, misc_utils, train .. are not located inside folders
 

data -> object -> [training, testing, ...] training -> [calib, image_2, label_2, velodyne, ..] testing -> [calib, image_2, velodyne, ..] <- no label_2 folder in testing folder

All configurations are defined in config.py

cd [root]
CUDA_VISIBLE_DEVICES=2,3 python3.5 train.py

To use multiple gpus, you need to modify __C.GPU_AVAILABLE='0,1' in config.py file If you use 3 gpus, __C.GPU_AVAILABLE='0,1,2' regardless of the actual numbering of your gpus such as (gpu 0, gpu 2, gpu 3) in CUDUA_VISIBLE_DEVICES=0,2,3

It will save model in 'save model' folder that will be automatically generated. It also save images in 'save_image' folder which also be generated automatically. And finally, it calls validation program to save the result in result folder and plot folder inside in it.

Currently no test script. It is included in validation step.