This is a reproduced repo of Point2Seq for 3D object detection.

The code is mainly based on OpenPCDet.


We provide code and training configurations of PointSeq on the ONCE and Waymo Open dataset under tools/cfgs.


The codes are tested in the following environment:

  • Ubuntu 18.04
  • Python 3.6
  • PyTorch 1.5
  • CUDA 10.1
  • OpenPCDet v0.3.0
  • spconv v1.2.1


a. Clone this repository.

b. Install the dependent libraries as follows:

  • Install the dependent python libraries:
pip install -r requirements.txt 
  • Install the SparseConv library, we use the implementation from [spconv].
    • If you use PyTorch 1.1, then make sure you install the spconv v1.0 with (commit 8da6f96) instead of the latest one.
    • If you use PyTorch 1.3+, then you need to install the spconv v1.2. As mentioned by the author of spconv, you need to use their docker if you use PyTorch 1.4+.

c. Compile CUDA operators by running the following command:

python setup.py develop


All the models are trained with Tesla V100 GPUs (32G). If you use different number of GPUs for training, it’s necessary to change the respective training epochs to attain a decent performance.


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