BF3D

BF3D: Bi-directional Fusion 3D Detector with Semantic Sampling and Geometric Mapping

Install

The Environment：

• Linux (tested on Ubuntu 16.04)
• Python 3.6+
• PyTorch 1.0+

a. Install the dependent python libraries like easydict,tqdm, tensorboardX etc.

b. Build and install the pointnet2_lib, iou3d, roipool3d libraries by executing the following command:

sh build_and_install.sh

Dataset preparation

Please download the official KITTI 3D object detection dataset and organize the downloaded files as follows:

BF3D
├── data
│   ├── KITTI
│   │   ├── ImageSets
│   │   ├── object
│   │   │   ├──training
│   │   │      ├──calib & velodyne & label_2 & image_2 & (optional: planes)
│   │   │   ├──testing
│   │   │      ├──calib & velodyne & image_2
├── lib
├── pointnet2_lib
├── tools

Trained model

The pre-trained model can be obtained from Baidu(i8cr)

Implementation

Training

Run BF3D for single gpu:

CUDA_VISIBLE_DEVICES=0 python train_rcnn.py --cfg_file cfgs/LI_Fusion_with_attention_use_ce_loss_car.yaml --batch_size 2 --train_mode rcnn_online --epochs 50  --ckpt_save_interval 1 --output_dir ./log/Car/full_epnet_without_iou_branch/   --set LI_FUSION.ENABLED True LI_FUSION.ADD_Image_Attention True RCNN.POOL_EXTRA_WIDTH 0.2 RPN.SCORE_THRESH 0.2 RCNN.SCORE_THRESH 0.2  USE_IOU_BRANCH False TRAIN.CE_WEIGHT 5.0

Run BF3D for multi gpus:

CUDA_VISIBLE_DEVICES=0,1,2,3 python train_rcnn.py --cfg_file cfgs/LI_Fusion_with_attention_use_ce_loss_car.yaml --batch_size 8 --train_mode rcnn_online --epochs 50 --mgpus --ckpt_save_interval 1 --output_dir ./log/Car/full_epnet_without_iou_branch/   --set LI_FUSION.ENABLED True LI_FUSION.ADD_Image_Attention True RCNN.POOL_EXTRA_WIDTH 0.2 RPN.SCORE_THRESH 0.2 RCNN.SCORE_THRESH 0.2  USE_IOU_BRANCH False TRAIN.CE_WEIGHT 5.0

Testing

CUDA_VICUDA_VISIBLE_DEVICES=0 python eval_rcnn.py --cfg_file cfgs/LI_Fusion_with_attention_use_ce_loss_car.yaml --eval_mode rcnn_online  --eval_all  --output_dir ./log/Car_temp1/full_epnet_without_iou_branch/eval_results/  --ckpt_dir ./log/Car_temp1/full_epnet_without_iou_branch/ckpt --set  LI_FUSION.ENABLED True LI_FUSION.ADD_Image_Attention True RCNN.POOL_EXTRA_WIDTH 0.2  RPN.SCORE_THRESH 0.2 RCNN.SCORE_THRESH 0.2  USE_IOU_BRANCH False