This is a reproduced benchmark for 3D object detection on the ONCE (One Million Scenes) dataset.
The code is mainly based on OpenPCDet.
We provide the dataset API and some reproduced models on the ONCE dataset.
The repo is based on OpenPCDet. If you have already installed OpenPCDet (version >= v0.3.0), you can skip this part and use the existing environment, but remember to re-compile CUDA operators by
pip install -r requirements.txt
python setup.py developIf you haven't installed OpenPCDet, please refer to INSTALL.md for the installation.
Please refer to GETTING_STARTED.md to learn more usage about this project.
- Preparation the dataset
- Flow these instructure to organize the data
ONCE_Benchmark
├── data
│ ├── once
│ │ │── ImageSets
| | | ├──train.txt
| | | ├──val.txt
| | | ├──test.txt
| | | ├──raw_small.txt (100k unlabeled)
| | | ├──raw_medium.txt (500k unlabeled)
| | | ├──raw_large.txt (1M unlabeled)
│ │ │── data
│ │ │ ├──000000
| | | | |──000000.json (infos)
| | | | |──lidar_roof (point clouds)
| | | | | |──frame_timestamp_1.bin
| | | | | ...
| | | | |──cam0[1-9] (images)
| | | | | |──frame_timestamp_1.jpg
| | | | | ...
| | | | ...
├── pcdet
├── tools
- Using once_dataset to generate the data
python -m pcdet.datasets.once.once_dataset --func create_once_infos --cfg_file tools/cfgs/dataset_configs/once_dataset.yaml
- Traing with signal GPU
python semi_train.py --cfg_file ./cfgs/once_models/semi_learning_models/ioumatch3d_second_small.yaml
- Traing with mutil GPUs
bash scripts/dist_train.sh 2 --cfg_file ./cfgs/once_models/semi_learning_models/ioumatch3d_second_small.yaml
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