jhzhang19 / Contfuse

Contfuse: Deep Continuous Fusion for Multi-Sensor 3D Object Detection

Introduction

It's a unofficial tensorflow Implementation of Contfuse: Deep Continuous Fusion for Multi-Sensor 3D Object Detection. It uses C++ \ CUDA C \ Python to complete this project.

Train on KITTI Dataset

I split KITTI train data to testing data \ training data \ verification data.

kitti dataset:   <-- 7481 train data
|-- data_object_calib   <-- 7481
    |--calib
|-- image_2    <-- 7481
|-- lidar_files   <-- 7481
|-- testing
    |-- label_files <-- 1000
|-- training
    |-- label_files <-- 6431
|-- val
    |-- label_files <-- 50

How to use it?

Dependencies

tensorflow 1.14 numpy 1.16 opencv 3.4 easydict cudnn 7.6.0 cuda 10.1 python 3.7 tqdm

train

step. 1 Generate dataset index document, you need modified dataset path.

cd src/scripts
python gen_dataset_idx.py

step. 2 train

python train.py

predict

python predict.py

Credit

CONTFUSE: Deep Continuous Fusion for Multi-Sensor 3D Object Detection

PIXOR: Real-time 3D Object Detection from Point Clouds