update documents for OpenPCDet v0.5.0

d1368b01 · Shaoshuai Shi · 17133605 · d1368b01 · d1368b01 · d1368b01
Commit d1368b01 authored Dec 01, 2021 by Shaoshuai Shi
6 changed files
--- a/README.md
+++ b/README.md
@@ -4,9 +4,9 @@
 `OpenPCDet` is a clear, simple, self-contained open source project for LiDAR-based 3D object detection. 
-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), [`[PV-RCNN]`](https://arxiv.org/abs/1912.13192) and [`[Voxel R-CNN]`](https://arxiv.org/abs/2012.15712). 
+It is also the official code release of [`[PointRCNN]`](https://arxiv.org/abs/1812.04244), [`[Part-A2-Net]`](https://arxiv.org/abs/1907.03670), [`[PV-RCNN]`](https://arxiv.org/abs/1912.13192) and [`[Voxel R-CNN]`](https://arxiv.org/abs/2012.15712). 
-[2021-12-01] **NEW**: `OpenPCDet` has been updated to `v0.5.0`.
+**NEW**: `OpenPCDet` has been updated to `v0.5.0` (Dec. 2021).
 ## Overview
 - [Changelog](#changelog)
@@ -130,7 +130,7 @@ By default, all models are trained with **20% data (~32k frames)** of all the tr
 |---------------------------------------------|----------:|:-------:|:-------:|:-------:|:-------:|:-------:|
 | [SECOND](tools/cfgs/waymo_models/second.yaml) | 70.96/70.34|62.58/62.02|65.23/54.24	|57.22/47.49|	57.13/55.62 |	54.97/53.53 | 
 | [CenterPoint](tools/cfgs/waymo_models/centerpoint_without_resnet.yaml)| 71.33/70.76|63.16/62.65|	72.09/65.49	|64.27/58.23|	68.68/67.39	|66.11/64.87|
-| [CenterPoint(ResNet)](tools/cfgs/waymo_models/centerpoint.yaml)|72.76/72.23|64.91/64.42	|74.19/67.96	|66.03/60.34|	71.04/69.79	|68.49/67.28 |
+| [CenterPoint (ResNet)](tools/cfgs/waymo_models/centerpoint.yaml)|72.76/72.23|64.91/64.42	|74.19/67.96	|66.03/60.34|	71.04/69.79	|68.49/67.28 |
 | [Part-A2-Anchor](tools/cfgs/waymo_models/PartA2.yaml) | 74.66/74.12	|65.82/65.32	|71.71/62.24	|62.46/54.06	|66.53/65.18	|64.05/62.75 |
 | [PV-RCNN (AnchorHead)](tools/cfgs/waymo_models/pv_rcnn.yaml) | 75.41/74.74	|67.44/66.80	|71.98/61.24	|63.70/53.95	|65.88/64.25	|63.39/61.82 | 
 | [PV-RCNN (CenterHead)](tools/cfgs/waymo_models/pv_rcnn_with_centerhead_rpn.yaml) | 75.95/75.43	|68.02/67.54	|75.94/69.40	|67.66/61.62	|70.18/68.98	|67.73/66.57|
@@ -149,7 +149,7 @@ All models are trained with 8 GTX 1080Ti GPUs and are available for download.
 ### Other datasets
-More datasets are on the way. 
+Welcome to support other datasets by submitting pull request. 
 ## Installation

--- a/docs/DEMO.md
+++ b/docs/DEMO.md
@@ -6,8 +6,11 @@ We suppose you already followed the [INSTALL.md](INSTALL.md) to install the `Ope
 1. Download the provided pretrained models as shown in the [README.md](../README.md). 
-2. Make sure you have already installed the `mayavi` visualization tools. If not, you could install it as follows:
+2. Make sure you have already installed the [`Open3D`](https://github.com/isl-org/Open3D) (faster) or `mayavi` visualization tools. 
+If not, you could install it as follows:
   ```
+   pip install open3d
+   # or 
   pip install mayavi
   ```

--- a/docs/GETTING_STARTED.md
+++ b/docs/GETTING_STARTED.md
@@ -71,11 +71,14 @@ OpenPCDet
 │   │   │── raw_data
 │   │   │   │── segment-xxxxxxxx.tfrecord
 |   |   |   |── ...
-|   |   |── waymo_processed_data
+|   |   |── waymo_processed_data_v0_5_0
 │   │   │   │── segment-xxxxxxxx/
 |   |   |   |── ...
-│   │   │── pcdet_gt_database_train_sampled_xx/
+│   │   │── waymo_processed_data_v0_5_0_gt_database_train_sampled_1/
-│   │   │── pcdet_waymo_dbinfos_train_sampled_xx.pkl   
+│   │   │── waymo_processed_data_v0_5_0_waymo_dbinfos_train_sampled_1.pkl
+│   │   │── waymo_processed_data_v0_5_0_gt_database_train_sampled_1_global.npy (optional)
+│   │   │── waymo_processed_data_v0_5_0_infos_train.pkl (optional)
+│   │   │── waymo_processed_data_v0_5_0_infos_val.pkl (optional)
 ├── pcdet
 ├── tools
 ```
@@ -87,7 +90,7 @@ pip3 install waymo-open-dataset-tf-2-0-0==1.2.0 --user
 ```
 * Extract point cloud data from tfrecord and generate data infos by running the following command (it takes several hours, 
-and you could refer to `data/waymo/waymo_processed_data` to see how many records that have been processed): 
+and you could refer to `data/waymo/waymo_processed_data_v0_5_0` to see how many records that have been processed): 
 ```python 
 python -m pcdet.datasets.waymo.waymo_dataset --func create_waymo_infos \
    --cfg_file tools/cfgs/dataset_configs/waymo_dataset.yaml
@@ -96,7 +99,7 @@ python -m pcdet.datasets.waymo.waymo_dataset --func create_waymo_infos \
 Note that you do not need to install `waymo-open-dataset` if you have already processed the data before and do not need to evaluate with official Waymo Metrics. 
 ## Pretrained Models
-If you would like to train [CaDDN](../tools/cfgs/kitti_models/CaDDN.yaml), download the pretrained [DeepLabV3 model](https://download.pytorch.org/models/deeplabv3_resnet101_coco-586e9e4e.pth) and place within the `checkpoints` directory
+If you would like to train [CaDDN](../tools/cfgs/kitti_models/CaDDN.yaml), download the pretrained [DeepLabV3 model](https://download.pytorch.org/models/deeplabv3_resnet101_coco-586e9e4e.pth) and place within the `checkpoints` directory. Please make sure the [kornia](https://github.com/kornia/kornia) is installed since it is needed for `CaDDN`.
 ```
 OpenPCDet
 ├── checkpoints

--- a/docs/INSTALL.md
+++ b/docs/INSTALL.md
@@ -2,15 +2,15 @@
 ### Requirements
 All the codes are tested in the following environment:
-* Linux (tested on Ubuntu 14.04/16.04)
+* Linux (tested on Ubuntu 14.04/16.04/18.04/20.04/21.04)
 * Python 3.6+
-* PyTorch 1.1 or higher (tested on PyTorch 1.1, 1,3, 1,5)
+* PyTorch 1.1 or higher (tested on PyTorch 1.1, 1,3, 1,5~1.10)
 * CUDA 9.0 or higher (PyTorch 1.3+ needs CUDA 9.2+)
-* [`spconv v1.0 (commit 8da6f96)`](https://github.com/traveller59/spconv/tree/8da6f967fb9a054d8870c3515b1b44eca2103634) or [`spconv v1.2`](https://github.com/traveller59/spconv)
+* [`spconv v1.0 (commit 8da6f96)`](https://github.com/traveller59/spconv/tree/8da6f967fb9a054d8870c3515b1b44eca2103634) or [`spconv v1.2`](https://github.com/traveller59/spconv) or [`spconv v2.x`](https://github.com/traveller59/spconv)
-### Install `pcdet v0.3`
+### Install `pcdet v0.5`
-NOTE: Please re-install `pcdet v0.3` by running `python setup.py develop` even if you have already installed previous version.
+NOTE: Please re-install `pcdet v0.5` by running `python setup.py develop` even if you have already installed previous version.
 a. Clone this repository.
 ```shell
@@ -19,16 +19,20 @@ git clone https://github.com/open-mmlab/OpenPCDet.git
 b. Install the dependent libraries as follows:
-* Install the dependent python libraries: 
+[comment]: <> (* Install the dependent python libraries: )
-```
-pip install -r requirements.txt 
+[comment]: <> (```)
-```
+[comment]: <> (pip install -r requirements.txt )
+[comment]: <> (```)
 * Install the SparseConv library, we use the implementation from [`[spconv]`](https://github.com/traveller59/spconv). 
    * If you use PyTorch 1.1, then make sure you install the `spconv v1.0` with ([commit 8da6f96](https://github.com/traveller59/spconv/tree/8da6f967fb9a054d8870c3515b1b44eca2103634)) 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`](https://github.com/traveller59/spconv), you need to use their docker if you use PyTorch 1.4+. 
+    * You could also install latest `spconv v2.x` with pip, see the official documents of [spconv](https://github.com/traveller59/spconv).
-c. Install this `pcdet` library by running the following command:
+c. Install this `pcdet` library and its dependent libraries by running the following command:
 ```shell
 python setup.py develop
 ```
--- a/requirements.txt
+++ b/requirements.txt
-numpy
+numpy<=1.20
-torch>=1.1
+llvmlite
 numba
+torch>=1.1
 tensorboardX
 easydict
 pyyaml
 scikit-image
 tqdm
-kornia
 torchvision
 SharedArray
--- a/setup.py
+++ b/setup.py
 import os
-import sys
 import subprocess
 from setuptools import find_packages, setup
-from setuptools.command.install import install
-# TODO: This is a bit buggy since it requires torch before installing torch.
 from torch.utils.cpp_extension import BuildExtension, CUDAExtension
@@ -30,15 +27,6 @@ def write_version_to_file(version, target_file):
        print('__version__ = "%s"' % version, file=f)
-class PostInstallation(install):
-    """Post-installation for installation mode."""
-    def run(self):
-        install.run(self)
-        # Note: buggy for kornia==0.5.3 and it will be fixed in the next version.
-        # Set kornia to 0.5.2 temporarily
-        subprocess.call([sys.executable, '-m', 'pip', 'install', 'kornia==0.5.2', '--no-dependencies'])
 if __name__ == '__main__':
    version = '0.5.0+%s' % get_git_commit_number()
    write_version_to_file(version, 'pcdet/version.py')
@@ -48,23 +36,24 @@ if __name__ == '__main__':
        version=version,
        description='OpenPCDet is a general codebase for 3D object detection from point cloud',
        install_requires=[
-            'numpy',
+            'numpy<=1.20',
-            'torch>=1.1',
+            'llvmlite',
-            # 'spconv',  # spconv has different names depending on the cuda version
            'numba',
            'tensorboardX',
            'easydict',
-            'pyyaml'
+            'pyyaml',
+            'scikit-image',
+            'tqdm',
+            'SharedArray',
+            # 'spconv',  # spconv has different names depending on the cuda version
        ],
        author='Shaoshuai Shi',
        author_email='shaoshuaics@gmail.com',
        license='Apache License 2.0',
        packages=find_packages(exclude=['tools', 'data', 'output']),
        cmdclass={
            'build_ext': BuildExtension,
-            'install': PostInstallation,
-            # Post installation cannot be done. ref: https://github.com/pypa/setuptools/issues/1936.
-            # 'develop': PostInstallation,
        },
        ext_modules=[
            make_cuda_ext(