Creator-wei / Once

Oncebencmark

ONCE Benchmark

Using the Flex_Match method

This is a reproduced benchmark for 3D object detection on the ONCE (One Million Scenes) dataset.

The code is mainly based on OpenPCDet.

Introduction

We provide the dataset API and some reproduced models on the ONCE dataset.

Installation

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 develop

If you haven't installed OpenPCDet, please refer to INSTALL.md for the installation.

Getting Started

Please refer to GETTING_STARTED.md to learn more usage about this project.

1. 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

2. Traing with signal GPU

 python semi_train.py --cfg_file ./cfgs/once_models/semi_learning_models/ioumatch3d_second_small.yaml

3. Traing with mutil GPUs

bash scripts/dist_train.sh 2 --cfg_file ./cfgs/once_models/semi_learning_models/ioumatch3d_second_small.yaml