`OpenPCDet` is a clear, simple, self-contained open source project for LiDAR-based 3D object detection.
`OpenPCDet` is a clear, simple, self-contained open source project for LiDAR-based 3D object detection.
It is also the official code release of [`[Part-A^2 net]`](https://arxiv.org/abs/1907.03670) and [`[PV-RCNN]`](https://arxiv.org/abs/1912.13192).
It is also the official code release of [`PointRCNN`](https://arxiv.org/abs/1812.04244), [`[Part-A^2 net]`](https://arxiv.org/abs/1907.03670) and [`[PV-RCNN]`](https://arxiv.org/abs/1912.13192).
## Overview
-[Changelog](#changelog)
-[Design Pattern](#openpcdet-design-pattern)
-[Model Zoo](#model zoo)
-[Quick Demo](#quick demo)
-[Getting Started](#Getting-Started)
-[Citation](#citation)
## Changelog
[2020-07-17] Add simple visualization codes and a quick demo to test with custom data.
[2020-06-24] `OpenPCDet` v0.2.0 is released with pretty new structures to support more models and datasets.
[2020-03-16] `OpenPCDet` v0.1.0 is released.
## Introduction
### What does `OpenPCDet` toolbox do?
### What does `OpenPCDet` toolbox do?
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@@ -54,44 +72,43 @@ Contributions are also welcomed.
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@@ -54,44 +72,43 @@ Contributions are also welcomed.
- [x] Support GPU version 3D IoU calculation and rotated NMS
- [x] Support GPU version 3D IoU calculation and rotated NMS
## ChangeLog
[2020-07-17] Add simple visualization codes and a quick demo to test with custom data.
[2020-06-24] `OpenPCDet` v0.2.0 is released with pretty new structures to support more models and datasets.
[2020-03-16] `OpenPCDet` v0.1.0 is released.
## Model Zoo
## Model Zoo
### KITTI 3D Object Detection Baselines
### KITTI 3D Object Detection Baselines
Selected supported methods are shown in the below table. The results are the 3D detection performance of car class on the *val* set of KITTI dataset.
Selected supported methods are shown in the below table. The results are the 3D detection performance of car class on the *val* set of KITTI dataset.
All models are trained with 8 GTX 1080Ti GPUs and are available for download.
All models are trained with 8 GTX 1080Ti GPUs and are available for download.
The dataset configs are located within [tools/cfgs/dataset_configs](tools/cfgs/dataset_configs),
The dataset configs are located within [tools/cfgs/dataset_configs](tools/cfgs/dataset_configs),
and the model configs are located within [tools/cfgs](tools/cfgs) for different datasets, like [tools/cfgs/kitti_models/](tools/cfgs/kitti_models/).
and the model configs are located within [tools/cfgs](tools/cfgs) for different datasets, like [tools/cfgs/kitti_models/](tools/cfgs/kitti_models/).
## Dataset Preparation
Currently we provide the dataloader of KITTI dataset and NuScenes dataset, and the supporting of more datasets are on the way.
### KITTI Dataset
* Please download the official [KITTI 3D object detection](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) dataset and organize the downloaded files as follows (the road planes could be downloaded from [[road plane]](https://drive.google.com/file/d/1d5mq0RXRnvHPVeKx6Q612z0YRO1t2wAp/view?usp=sharing), which are optional for data augmentation in the training):
* NOTE: if you already have the data infos from `pcdet v0.1`, you can choose to use the old infos and set the DATABASE_WITH_FAKELIDAR option in tools/cfgs/dataset_configs/kitti_dataset.yaml as True. The second choice is that you can create the infos and gt database again and leave the config unchanged.
NOTE: Please re-install `pcdet v0.2` by running `python setup.py develop` if you have already installed `pcdet v0.1` previously.
NOTE: Please re-install `pcdet v0.3` by running `python setup.py develop` if you have already installed `pcdet v0.1` previously.
a. Clone this repository.
a. Clone this repository.
```shell
```shell
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@@ -31,29 +31,3 @@ c. Install this `pcdet` library by running the following command:
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@@ -31,29 +31,3 @@ c. Install this `pcdet` library by running the following command:
```shell
```shell
python setup.py develop
python setup.py develop
```
```
## Dataset Preparation
Currently we provide the dataloader of KITTI dataset, and the supporting of more datasets are on the way.
### KITTI Dataset
* Please download the official [KITTI 3D object detection](http://www.cvlibs.net/datasets/kitti/eval_object.php?obj_benchmark=3d) dataset and organize the downloaded files as follows (the road planes could be downloaded from [[road plane]](https://drive.google.com/file/d/1d5mq0RXRnvHPVeKx6Q612z0YRO1t2wAp/view?usp=sharing), which are optional for data augmentation in the training):
* NOTE: if you already have the data infos from `pcdet v0.1`, you can choose to use the old infos and set the DATABASE_WITH_FAKELIDAR option in tools/cfgs/dataset_configs/kitti_dataset.yaml as True. The second choice is that you can create the infos and gt database again and leave the config unchanged.
