Configs for Centerpoint on KITTI

.gitignore

@@ -15,3 +15,4 @@ venv/
 *.bin
 output
 version.py
+.vscode/

Dockerfile

@@ -0,0 +1,88 @@
+# This tag does not exist anymore it was changed to the next closest: FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
+FROM nvidia/cuda:11.7.1-cudnn8-devel-ubuntu18.04
+
+RUN echo 'debconf debconf/frontend select Noninteractive' | debconf-set-selections
+
+# Install basics
+RUN apt-get clean && rm -rf /var/lib/apt/lists/*
+RUN apt-get update -y \
+ && apt-get install -y build-essential \
+ && apt-get install -y apt-utils git curl ca-certificates bzip2 tree htop wget \
+ && apt-get install -y libglib2.0-0 libsm6 libxext6 libxrender-dev bmon iotop g++ python3.8 python3.8-dev python3.8-distutils
+
+# Install cmake v3.13.2
+RUN apt-get purge -y cmake && \
+ mkdir /root/temp && \
+ cd /root/temp && \
+ wget https://github.com/Kitware/CMake/releases/download/v3.13.2/cmake-3.13.2.tar.gz && \
+ tar -xzvf cmake-3.13.2.tar.gz && \
+ cd cmake-3.13.2 && \
+ bash ./bootstrap && \
+ make && \
+ make install && \
+ cmake --version && \
+ rm -rf /root/temp
+
+# Install python
+RUN ln -sv /usr/bin/python3.8 /usr/bin/python
+RUN wget https://bootstrap.pypa.io/get-pip.py && \
+ python get-pip.py && \
+ rm get-pip.py
+
+# Install python packages
+RUN PIP_INSTALL="python -m pip --no-cache-dir install" && \
+ # $PIP_INSTALL numpy==1.19.3 llvmlite numba
+ $PIP_INSTALL numpy==1.24.4 llvmlite numba
+
+# Install torch and torchvision
+# See https://pytorch.org/ for other options if you use a different version of CUDA
+# RUN pip install --user torch==1.6 torchvision==0.7.0 -f https://download.pytorch.org/whl/cu102/torch_stable.html
+# RUN pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
+RUN pip install torch torchvision torchaudio
+
+# Install python packages
+RUN PIP_INSTALL="python -m pip --no-cache-dir install" && \
+ $PIP_INSTALL tensorboardX easydict pyyaml scikit-image tqdm SharedArray six
+
+WORKDIR /root
+
+# Install Boost geometry
+RUN wget https://jaist.dl.sourceforge.net/project/boost/boost/1.68.0/boost_1_68_0.tar.gz && \
+ tar xzvf boost_1_68_0.tar.gz && \
+ cp -r ./boost_1_68_0/boost /usr/include && \
+ rm -rf ./boost_1_68_0 && \
+ rm -rf ./boost_1_68_0.tar.gz
+
+# A weired problem that hasn't been solved yet
+RUN pip uninstall -y SharedArray && \
+ pip install SharedArray
+
+RUN pip install spconv-cu117
+
+RUN pip install torch_geometric
+
+RUN pip install open3d
+
+RUN pip install mayavi
+
+RUN pip install kornia
+
+RUN apt-get update && apt-get install -y libgl1-mesa-glx
+
+RUN apt-get update && apt-get install -y \
+ openssh-client \
+ git
+
+RUN git clone https://github.com/MarcBrede/OpenPCDet.git
+
+ENV PYTHONPATH /root/OpenPCDet/
+
+RUN pip install av2
+
+RUN pip install torch-cluster -f https://pytorch-geometric.com/whl/torch-2.0.1+cu117.html
+RUN pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-2.0.1+cu117.html
+RUN pip install tensorboard
+
+# RUN ls /root/OpenPCDet/
+
+# RUN python /root/OpenPCDet/setup.py develop

pcdet/datasets/__init__.py

@@ -12,7 +12,7 @@
 from .pandaset.pandaset_dataset import PandasetDataset
 from .lyft.lyft_dataset import LyftDataset
 from .once.once_dataset import ONCEDataset
-from .argo2.argo2_dataset import Argo2Dataset
+# from .argo2.argo2_dataset import Argo2Dataset
 from .custom.custom_dataset import CustomDataset
 
 __all__ = {
@@ -24,7 +24,7 @@
  'LyftDataset': LyftDataset,
  'ONCEDataset': ONCEDataset,
  'CustomDataset': CustomDataset,
- 'Argo2Dataset': Argo2Dataset
+ # 'Argo2Dataset': Argo2Dataset
 }
 
 

pcdet/datasets/augmentor/database_sampler.py

@@ -5,7 +5,7 @@
 import numpy as np
 from skimage import io
 import torch
-import SharedArray
+# import SharedArray
 import torch.distributed as dist
 
 from ...ops.iou3d_nms import iou3d_nms_utils
@@ -70,16 +70,17 @@ def __setstate__(self, d):
  self.__dict__.update(d)
 
  def __del__(self):
- if self.use_shared_memory:
- self.logger.info('Deleting GT database from shared memory')
- cur_rank, num_gpus = common_utils.get_dist_info()
- sa_key = self.sampler_cfg.DB_DATA_PATH[0]
- if cur_rank % num_gpus == 0 and os.path.exists(f"/dev/shm/{sa_key}"):
- SharedArray.delete(f"shm://{sa_key}")
-
- if num_gpus > 1:
- dist.barrier()
- self.logger.info('GT database has been removed from shared memory')
+ pass
+ # if self.use_shared_memory:
+ # self.logger.info('Deleting GT database from shared memory')
+ # cur_rank, num_gpus = common_utils.get_dist_info()
+ # sa_key = self.sampler_cfg.DB_DATA_PATH[0]
+ # if cur_rank % num_gpus == 0 and os.path.exists(f"/dev/shm/{sa_key}"):
+ # SharedArray.delete(f"shm://{sa_key}")
+
+ # if num_gpus > 1:
+ # dist.barrier()
+ # self.logger.info('GT database has been removed from shared memory')
 
  def load_db_to_shared_memory(self):
  self.logger.info('Loading GT database to shared memory')
@@ -379,11 +380,11 @@ def add_sampled_boxes_to_scene(self, data_dict, sampled_gt_boxes, total_valid_sa
  # convert sampled 3D boxes to image plane
  img_aug_gt_dict = self.initilize_image_aug_dict(data_dict, gt_boxes_mask)
 
- if self.use_shared_memory:
- gt_database_data = SharedArray.attach(f"shm://{self.gt_database_data_key}")
- gt_database_data.setflags(write=0)
- else:
-  gt_database_data = None
+ # if self.use_shared_memory:
+ #  gt_database_data = SharedArray.attach(f"shm://{self.gt_database_data_key}")
+ #  gt_database_data.setflags(write=0)
+ # else:
+ gt_database_data = None
 
  for idx, info in enumerate(total_valid_sampled_dict):
  if self.use_shared_memory:
@@ -392,12 +393,13 @@ def add_sampled_boxes_to_scene(self, data_dict, sampled_gt_boxes, total_valid_sa
  else:
  file_path = self.root_path / info['path']
 
- obj_points = np.fromfile(str(file_path), dtype=np.float32).reshape(
- [-1, self.sampler_cfg.NUM_POINT_FEATURES])
+ obj_points = np.fromfile(str(file_path), dtype=np.float32).reshape([-1, self.sampler_cfg.NUM_POINT_FEATURES])
  if obj_points.shape[0] != info['num_points_in_gt']:
  obj_points = np.fromfile(str(file_path), dtype=np.float64).reshape(-1, self.sampler_cfg.NUM_POINT_FEATURES)
 
- assert obj_points.shape[0] == info['num_points_in_gt']
+
+ error_string = 'GT database error for file %s info: %s, %s, %s, %s' % (file_path, info['name'], info['path'], str(info['image_idx']), str(info['gt_idx']))
+ assert obj_points.shape[0] == info['num_points_in_gt'], error_string
  obj_points[:, :3] += info['box3d_lidar'][:3].astype(np.float32)
 
  if self.sampler_cfg.get('USE_ROAD_PLANE', False):

pcdet/datasets/waymo/waymo_dataset.py

@@ -9,7 +9,7 @@
 import numpy as np
 import torch
 import multiprocessing
-import SharedArray
+# import SharedArray
 import torch.distributed as dist
 from tqdm import tqdm
 from pathlib import Path
@@ -149,7 +149,7 @@ def clean_shared_memory(self):
  if not os.path.exists(f"/dev/shm/{sa_key}"):
  continue
 
- SharedArray.delete(f"shm://{sa_key}")
+ # SharedArray.delete(f"shm://{sa_key}")
 
  if num_gpus > 1:
  dist.barrier()
@@ -352,11 +352,11 @@ def __getitem__(self, index):
  input_dict = {
  'sample_idx': sample_idx
  }
- if self.use_shared_memory and index < self.shared_memory_file_limit:
- sa_key = f'{sequence_name}___{sample_idx}'
- points = SharedArray.attach(f"shm://{sa_key}").copy()
- else:
-  points = self.get_lidar(sequence_name, sample_idx)
+ # if self.use_shared_memory and index < self.shared_memory_file_limit:
+ #  sa_key = f'{sequence_name}___{sample_idx}'
+ #  points = SharedArray.attach(f"shm://{sa_key}").copy()
+ # else:
+ points = self.get_lidar(sequence_name, sample_idx)
 
  if self.dataset_cfg.get('SEQUENCE_CONFIG', None) is not None and self.dataset_cfg.SEQUENCE_CONFIG.ENABLED:
  points, num_points_all, sample_idx_pre_list, poses, pred_boxes, pred_scores, pred_labels = self.get_sequence_data(
@@ -714,6 +714,8 @@ def create_waymo_infos(dataset_cfg, class_names, data_path, save_path,
  os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
  print('---------------Start to generate data infos---------------')
 
+ raw_data_tag = 'training'
+
  dataset.set_split(train_split)
  waymo_infos_train = dataset.get_infos(
  raw_data_path=data_path / raw_data_tag,
@@ -724,6 +726,8 @@ def create_waymo_infos(dataset_cfg, class_names, data_path, save_path,
  pickle.dump(waymo_infos_train, f)
  print('----------------Waymo info train file is saved to %s----------------' % train_filename)
 
+ raw_data_tag = 'validation'
+
  dataset.set_split(val_split)
  waymo_infos_val = dataset.get_infos(
  raw_data_path=data_path / raw_data_tag,

pcdet/models/detectors/PartA2_relation_net.py

@@ -0,0 +1,36 @@
+from .detector3d_template import Detector3DTemplate
+from ..object_relation import build_object_relation_module
+
+
+class PartA2NetRelation(Detector3DTemplate):
+ def __init__(self, model_cfg, num_class, dataset):
+ super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
+ self.module_list = self.build_networks()
+ self.object_relation = build_object_relation_module(model_cfg.OBJECT_RELATION)
+
+ def forward(self, batch_dict):
+ for cur_module in self.module_list:
+ batch_dict = cur_module(batch_dict)
+
+ batch_dict = self.object_relation(batch_dict)
+ batch_dict = self.roi_head.final_predictions(batch_dict)
+
+ if self.training:
+ loss, tb_dict, disp_dict = self.get_training_loss()
+
+ ret_dict = {
+ 'loss': loss
+ }
+ return ret_dict, tb_dict, disp_dict
+ else:
+ pred_dicts, recall_dicts = self.post_processing(batch_dict)
+ return pred_dicts, recall_dicts
+
+ def get_training_loss(self):
+ disp_dict = {}
+ loss_rpn, tb_dict = self.dense_head.get_loss()
+ loss_point, tb_dict = self.point_head.get_loss(tb_dict)
+ loss_rcnn, tb_dict = self.roi_head.get_loss(tb_dict)
+
+ loss = loss_rpn + loss_point + loss_rcnn
+ return loss, tb_dict, disp_dict

pcdet/models/detectors/__init__.py

@@ -15,6 +15,11 @@
 from .voxelnext import VoxelNeXt
 from .transfusion import TransFusion
 from .bevfusion import BevFusion
+from .pv_rcnn_relation import PVRCNNRelation
+from .pv_rcnn_plusplus_relation import PVRCNNPlusPlusRelation
+from .centerpoint_twostage import CenterPointTwoStage
+from .PartA2_relation_net import PartA2NetRelation
+from .voxel_rcnn_relation import VoxelRCNNRelation
 
 __all__ = {
  'Detector3DTemplate': Detector3DTemplate,
@@ -35,6 +40,11 @@
  'VoxelNeXt': VoxelNeXt,
  'TransFusion': TransFusion,
  'BevFusion': BevFusion,
+ 'PVRCNNRelation': PVRCNNRelation,
+ 'PVRCNNPlusPlusRelation': PVRCNNPlusPlusRelation,
+ 'CenterPointTwoStage': CenterPointTwoStage,
+ 'PartA2NetRelation': PartA2NetRelation,
+ 'VoxelRCNNRelation': VoxelRCNNRelation,
 }
 
 

pcdet/models/detectors/centerpoint_twostage.py

@@ -0,0 +1,56 @@
+from .detector3d_template import Detector3DTemplate
+
+
+class CenterPointTwoStage(Detector3DTemplate):
+ def __init__(self, model_cfg, num_class, dataset):
+ super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
+ self.module_list = self.build_networks()
+
+ def forward(self, batch_dict):
+ batch_dict = self.vfe(batch_dict)
+ batch_dict = self.backbone_3d(batch_dict)
+ batch_dict = self.map_to_bev_module(batch_dict)
+ batch_dict = self.backbone_2d(batch_dict)
+ batch_dict = self.dense_head(batch_dict)
+ batch_dict = self.roi_head(batch_dict)
+
+ if self.training:
+ loss, tb_dict, disp_dict = self.get_training_loss()
+
+ ret_dict = {
+ 'loss': loss
+ }
+ return ret_dict, tb_dict, disp_dict
+ else:
+ pred_dicts, recall_dicts = self.post_processing(batch_dict)
+ return pred_dicts, recall_dicts
+
+ def get_training_loss(self):
+ disp_dict = {}
+ loss_rpn, tb_dict = self.dense_head.get_loss()
+ tb_dict = {
+ 'loss_rpn': loss_rpn.item(),
+ **tb_dict
+ }
+
+ loss_rcnn, tb_dict = self.roi_head.get_loss(tb_dict)
+
+ loss = loss_rpn + loss_rcnn
+ return loss, tb_dict, disp_dict
+
+ # def post_processing(self, batch_dict):
+ # post_process_cfg = self.model_cfg.POST_PROCESSING
+ # batch_size = batch_dict['batch_size']
+ # # final_pred_dict = batch_dict['final_box_dicts']
+ # final_preds = batch_dict['batch_box_preds']
+ # recall_dict = {}
+ # for index in range(batch_size):
+ # pred_boxes = final_pred_dict[index]['pred_boxes']
+
+ # recall_dict = self.generate_recall_record(
+ # box_preds=pred_boxes,
+ # recall_dict=recall_dict, batch_index=index, data_dict=batch_dict,
+ # thresh_list=post_process_cfg.RECALL_THRESH_LIST
+ # )
+
+ # return final_pred_dict, recall_dict