This implementation has some bugs. The bugs are fixed in https://github.com/zye1996/3DSSD-torch. Thanks for his efforts in the debugging process since the debugging is the much more difficult that write the bugs.
I have implemented the 3DSSD in the OpenPCDet framework. Thanks for the mmlab to provide such a good framework for 3D object detection!!!
I have put new implementation into a new Repositories. The eval performance is very satisfactory:
Car [email protected], 0.70, 0.70:
bbox AP:96.5468, 90.0235, 89.4066
bev AP:90.3444, 88.0784, 86.0698
3d AP:89.2219, 78.8593, 77.5890
aos AP:96.52, 89.95, 89.25
Car [email protected], 0.70, 0.70:
bbox AP:98.2011, 95.0305, 92.6650
bev AP:93.2919, 89.1952, 88.1910
3d AP:91.4331, 82.2283, 77.8059
aos AP:98.18, 94.93, 92.49
Car [email protected], 0.50, 0.50:
bbox AP:96.5468, 90.0235, 89.4066
bev AP:96.6237, 90.1257, 89.6772
3d AP:96.5594, 90.0998, 89.6259
aos AP:96.52, 89.95, 89.25
Car [email protected], 0.50, 0.50:
bbox AP:98.2011, 95.0305, 92.6650
bev AP:98.3041, 95.4983, 95.0182
3d AP:98.2703, 95.3970, 94.8667
aos AP:98.18, 94.93, 92.49
3DSSD's implementation with Pytorch
This repository contains a PyTorch implementation of 3DSSD on the KITTI benchmark.
There are several characteristics to make you easy to understand and modify the code:
- I keep the name of the folders. files and the fucntions the same as the official code as much as possible.
- The "Trainner" in the lib/core/trainner.py draws on the code style of the PCDet.
- I borrow the visualization code with the MeshLab from the VoteNet.
If you want to use the F-FPS or the Dilated-Ball-Query, you can just use the files in lib/pointnet2.
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Clone this repository
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Install the Python dependencies.
pip install -r requirements.txt
- Install python functions. the functions are partly borrowed from the Pointnet2 in PointRCNN. The F-FPS and dilated-ball-query are implemented by myself.
cd lib/pointnet2
python setup.py install
- Prepare data with according to the "Data Preparation" in the 3DSSD
python lib/core/trainer.py --cfg configs/kitti/3dssd/3dssd.yaml
The trainning log and tensorboard log are saved into output dir