From 4ba030ac7825258b16fe5ebc6cac01ef90cb73d1 Mon Sep 17 00:00:00 2001 From: sunjiahao1999 <578431509@qq.com> Date: Thu, 22 Feb 2024 14:43:18 +0800 Subject: [PATCH] add lidarseg config && support torchsparse++ --- mmdet3d/configs/_base_/datasets/nus_seg.py | 221 ++++++++++++++++++ .../configs/_base_/schedules/lidarseg_50e.py | 34 +++ .../configs/_base_/schedules/lidarseg_80e.py | 34 +++ .../cylinder3d_8xb2_50e_semantickitti.py | 17 ++ .../cylinder3d_8xb2_80e_nus_seg.py | 23 ++ .../cylinder3d_8xb2_amp_50e_semantickitti.py | 7 + .../cylinder3d_8xb2_amp_80e_nus_seg.py | 7 + .../cylinder3d_8xb2_aug_50e_semantickitti.py | 88 +++++++ .../cylinder3d_8xb2_aug_80e_nus_seg.py | 92 ++++++++ ...linder3d_8xb2_aug_amp_50e_semantickitti.py | 7 + .../cylinder3d_8xb2_aug_amp_80e_nus_seg.py | 7 + ...8_w16_spconv_8xb2_amp_50e_semantickitti.py | 13 ++ ...kunet18_w16_spconv_8xb2_amp_80e_nus_seg.py | 13 ++ ...torchsparse2_8xb2_amp_50e_semantickitti.py | 13 ++ ...8_w16_torchsparse2_8xb2_amp_80e_nus_seg.py | 13 ++ ...8_w20_spconv_8xb2_amp_50e_semantickitti.py | 13 ++ ...kunet18_w20_spconv_8xb2_amp_80e_nus_seg.py | 13 ++ ...torchsparse2_8xb2_amp_50e_semantickitti.py | 13 ++ ...8_w20_torchsparse2_8xb2_amp_80e_nus_seg.py | 13 ++ ...8_w32_spconv_8xb2_amp_50e_semantickitti.py | 10 + ...kunet18_w32_spconv_8xb2_amp_80e_nus_seg.py | 10 + ...torchsparse2_8xb2_amp_50e_semantickitti.py | 21 ++ ...8_w32_torchsparse2_8xb2_amp_80e_nus_seg.py | 29 +++ ...net34_w32_spconv_8xb2_50e_semantickitti.py | 10 + .../minkunet34_w32_spconv_8xb2_80e_nus_seg.py | 10 + ...4_w32_spconv_8xb2_amp_50e_semantickitti.py | 10 + ...kunet34_w32_spconv_8xb2_amp_80e_nus_seg.py | 10 + ...4_w32_spconv_8xb2_aug_50e_semantickitti.py | 10 + ...kunet34_w32_spconv_8xb2_aug_80e_nus_seg.py | 10 + ...2_spconv_8xb2_aug_amp_50e_semantickitti.py | 10 + ...t34_w32_spconv_8xb2_aug_amp_80e_nus_seg.py | 10 + ...w32_torchsparse2_8xb2_50e_semantickitti.py | 22 ++ ...net34_w32_torchsparse2_8xb2_80e_nus_seg.py | 30 +++ ...torchsparse2_8xb2_amp_50e_semantickitti.py | 7 + ...4_w32_torchsparse2_8xb2_amp_80e_nus_seg.py | 7 + ...torchsparse2_8xb2_aug_50e_semantickitti.py | 88 +++++++ ...4_w32_torchsparse2_8xb2_aug_80e_nus_seg.py | 92 ++++++++ ...hsparse2_8xb2_aug_amp_50e_semantickitti.py | 7 + ...2_torchsparse2_8xb2_aug_amp_80e_nus_seg.py | 7 + ...pute_detection_metrics_main_single_process | Bin 0 -> 1890944 bytes mmdet3d/models/backbones/minkunet_backbone.py | 1 + mmdet3d/models/backbones/spvcnn_backone.py | 4 +- mmdet3d/models/layers/torchsparse_block.py | 21 +- requirements/mminstall.txt | 2 +- 44 files changed, 1073 insertions(+), 6 deletions(-) create mode 100644 mmdet3d/configs/_base_/datasets/nus_seg.py create mode 100644 mmdet3d/configs/_base_/schedules/lidarseg_50e.py create mode 100644 mmdet3d/configs/_base_/schedules/lidarseg_80e.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_50e_semantickitti.py create mode 100644 mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_80e_nus_seg.py create mode 100755 mmdet3d/evaluation/functional/waymo_utils/compute_detection_metrics_main_single_process diff --git a/mmdet3d/configs/_base_/datasets/nus_seg.py b/mmdet3d/configs/_base_/datasets/nus_seg.py new file mode 100644 index 0000000000..978044404a --- /dev/null +++ b/mmdet3d/configs/_base_/datasets/nus_seg.py @@ -0,0 +1,221 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmcv.transforms import TestTimeAug +from mmengine.dataset.sampler import DefaultSampler +from mmengine.visualization import LocalVisBackend + +from mmdet3d.datasets import NuScenesSegDataset +from mmdet3d.datasets.transforms import (GlobalRotScaleTrans, + LoadAnnotations3D, LoadPointsFromFile, + Pack3DDetInputs, PointSegClassMapping, + RandomFlip3D) +from mmdet3d.evaluation import SegMetric +from mmdet3d.models import Seg3DTTAModel +from mmdet3d.visualization import Det3DLocalVisualizer + +# For nuScenes we usually do 16-class segmentation. +# For labels_map we follow the uniform format of MMDetection & MMSegmentation +# i.e. we consider the unlabeled class as the last one, which is different +# from the original implementation of some methods e.g. Cylinder3D. +data_root = 'data/nuscenes/' +class_names = [ + 'barrier', 'bicycle', 'bus', 'car', 'construction_vehicle', 'motorcycle', + 'pedestrian', 'traffic_cone', 'trailer', 'truck', 'driveable_surface', + 'other_flat', 'sidewalk', 'terrain', 'manmade', 'vegetation' +] +labels_map = { + 0: 16, + 1: 16, + 2: 6, + 3: 6, + 4: 6, + 5: 16, + 6: 6, + 7: 16, + 8: 16, + 9: 0, + 10: 16, + 11: 16, + 12: 7, + 13: 16, + 14: 1, + 15: 2, + 16: 2, + 17: 3, + 18: 4, + 19: 16, + 20: 16, + 21: 5, + 22: 8, + 23: 9, + 24: 10, + 25: 11, + 26: 12, + 27: 13, + 28: 14, + 29: 16, + 30: 15, + 31: 16 +} + +metainfo = dict( + classes=class_names, seg_label_mapping=labels_map, max_label=31) + +input_modality = dict(use_lidar=True, use_camera=False) +data_prefix = dict( + pts='samples/LIDAR_TOP', + img='', + pts_semantic_mask='lidarseg/v1.0-trainval') + +# Example to use different file client +# Method 1: simply set the data root and let the file I/O module +# automatically infer from prefix (not support LMDB and Memcache yet) + +# data_root = 's3://openmmlab/datasets/detection3d/nuscenes/' + +# Method 2: Use backend_args, file_client_args in versions before 1.1.0 +# backend_args = dict( +# backend='petrel', +# path_mapping=dict({ +# './data/': 's3://openmmlab/datasets/detection3d/', +# 'data/': 's3://openmmlab/datasets/detection3d/' +# })) +backend_args = None + +train_pipeline = [ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping), + dict( + type=RandomFlip3D, + sync_2d=False, + flip_ratio_bev_horizontal=0.5, + flip_ratio_bev_vertical=0.5), + dict( + type=GlobalRotScaleTrans, + rot_range=[-0.78539816, 0.78539816], + scale_ratio_range=[0.95, 1.05], + translation_std=[0.1, 0.1, 0.1]), + dict(type=Pack3DDetInputs, keys=['points', 'pts_semantic_mask']) +] +test_pipeline = [ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping), + dict(type=Pack3DDetInputs, keys=['points']) +] +tta_pipeline = [ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping), + dict( + type=TestTimeAug, + transforms=[[ + dict( + type=RandomFlip3D, + sync_2d=False, + flip_ratio_bev_horizontal=0., + flip_ratio_bev_vertical=0.), + dict( + type=RandomFlip3D, + sync_2d=False, + flip_ratio_bev_horizontal=0., + flip_ratio_bev_vertical=1.), + dict( + type=RandomFlip3D, + sync_2d=False, + flip_ratio_bev_horizontal=1., + flip_ratio_bev_vertical=0.), + dict( + type=RandomFlip3D, + sync_2d=False, + flip_ratio_bev_horizontal=1., + flip_ratio_bev_vertical=1.) + ], + [ + dict( + type=GlobalRotScaleTrans, + rot_range=[pcd_rotate_range, pcd_rotate_range], + scale_ratio_range=[ + pcd_scale_factor, pcd_scale_factor + ], + translation_std=[0, 0, 0]) + for pcd_rotate_range in [-0.78539816, 0.0, 0.78539816] + for pcd_scale_factor in [0.95, 1.0, 1.05] + ], [dict(type=Pack3DDetInputs, keys=['points'])]]) +] + +train_dataloader = dict( + batch_size=2, + num_workers=4, + persistent_workers=True, + sampler=dict(type=DefaultSampler, shuffle=True), + dataset=dict( + type=NuScenesSegDataset, + data_root=data_root, + ann_file='nuscenes_infos_train.pkl', + data_prefix=data_prefix, + pipeline=train_pipeline, + metainfo=metainfo, + modality=input_modality, + ignore_index=16, + backend_args=backend_args)) +val_dataloader = dict( + batch_size=1, + num_workers=1, + persistent_workers=True, + drop_last=False, + sampler=dict(type=DefaultSampler, shuffle=False), + dataset=dict( + type=NuScenesSegDataset, + data_root=data_root, + ann_file='nuscenes_infos_val.pkl', + data_prefix=data_prefix, + pipeline=test_pipeline, + metainfo=metainfo, + modality=input_modality, + ignore_index=16, + test_mode=True, + backend_args=backend_args)) +test_dataloader = val_dataloader + +val_evaluator = dict(type=SegMetric) +test_evaluator = val_evaluator + +vis_backends = [dict(type=LocalVisBackend)] +visualizer = dict( + type=Det3DLocalVisualizer, vis_backends=vis_backends, name='visualizer') + +tta_model = dict(type=Seg3DTTAModel) diff --git a/mmdet3d/configs/_base_/schedules/lidarseg_50e.py b/mmdet3d/configs/_base_/schedules/lidarseg_50e.py new file mode 100644 index 0000000000..6cfdfe15f1 --- /dev/null +++ b/mmdet3d/configs/_base_/schedules/lidarseg_50e.py @@ -0,0 +1,34 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine.optim.optimizer.optimizer_wrapper import OptimWrapper +from mmengine.optim.scheduler.lr_scheduler import OneCycleLR +from mmengine.runner.loops import EpochBasedTrainLoop, TestLoop, ValLoop +from torch.optim.adamw import AdamW + +# training schedule for 50e +train_cfg = dict(type=EpochBasedTrainLoop, max_epochs=50, val_interval=1) +val_cfg = dict(type=ValLoop) +test_cfg = dict(type=TestLoop) + +# learning rate +lr = 0.01 +param_scheduler = [ + dict( + type=OneCycleLR, + eta_max=lr, + pct_start=0.2, + div_factor=25.0, + final_div_factor=100.0, + by_epoch=False) +] + +# optimizer +optim_wrapper = dict( + type=OptimWrapper, + optimizer=dict( + type=AdamW, lr=lr, betas=(0.9, 0.999), weight_decay=0.01, eps=1e-6)) + +# Default setting for scaling LR automatically +# - `enable` means enable scaling LR automatically +# or not by default. +# - `base_batch_size` = (8 GPUs) x (2 samples per GPU). +auto_scale_lr = dict(enable=False, base_batch_size=16) diff --git a/mmdet3d/configs/_base_/schedules/lidarseg_80e.py b/mmdet3d/configs/_base_/schedules/lidarseg_80e.py new file mode 100644 index 0000000000..736a809733 --- /dev/null +++ b/mmdet3d/configs/_base_/schedules/lidarseg_80e.py @@ -0,0 +1,34 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine.optim.optimizer.optimizer_wrapper import OptimWrapper +from mmengine.optim.scheduler.lr_scheduler import OneCycleLR +from mmengine.runner.loops import EpochBasedTrainLoop, TestLoop, ValLoop +from torch.optim.adamw import AdamW + +# training schedule for 80e +train_cfg = dict(type=EpochBasedTrainLoop, max_epochs=80, val_interval=1) +val_cfg = dict(type=ValLoop) +test_cfg = dict(type=TestLoop) + +# learning rate +lr = 0.01 +param_scheduler = [ + dict( + type=OneCycleLR, + eta_max=lr, + pct_start=0.2, + div_factor=25.0, + final_div_factor=100.0, + by_epoch=False) +] + +# optimizer +optim_wrapper = dict( + type=OptimWrapper, + optimizer=dict( + type=AdamW, lr=lr, betas=(0.9, 0.999), weight_decay=0.01, eps=1e-6)) + +# Default setting for scaling LR automatically +# - `enable` means enable scaling LR automatically +# or not by default. +# - `base_batch_size` = (8 GPUs) x (2 samples per GPU). +auto_scale_lr = dict(enable=False, base_batch_size=16) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_50e_semantickitti.py new file mode 100644 index 0000000000..2a9f0759c7 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_50e_semantickitti.py @@ -0,0 +1,17 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.semantickitti import * + from .._base_.models.cylinder3d import * + from .._base_.schedules.lidarseg_50e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_80e_nus_seg.py new file mode 100644 index 0000000000..7152b37adb --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_80e_nus_seg.py @@ -0,0 +1,23 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.nus_seg import * + from .._base_.models.cylinder3d import * + from .._base_.schedules.lidarseg_80e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +model.update(dict(decode_head=dict(num_classes=17, ignore_index=16))) + +train_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_train.pkl'))) +test_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_val.pkl'))) +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..806ec64640 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_50e_semantickitti import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..088a6f2bae --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_80e_nus_seg import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_50e_semantickitti.py new file mode 100644 index 0000000000..5868792a0c --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_50e_semantickitti.py @@ -0,0 +1,88 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_50e_semantickitti import * + +from mmcv.transforms.wrappers import RandomChoice + +from mmdet3d.datasets.transforms.formating import Pack3DDetInputs +from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D, + LoadPointsFromFile, + PointSegClassMapping) +from mmdet3d.datasets.transforms.transforms_3d import (GlobalRotScaleTrans, + LaserMix, PolarMix) + +train_pipeline = [ + dict(type=LoadPointsFromFile, coord_type='LIDAR', load_dim=4, use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping), + dict( + type=RandomChoice, + transforms=[ + [ + dict( + type=LaserMix, + num_areas=[3, 4, 5, 6], + pitch_angles=[-25, 3], + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=4, + use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + [ + dict( + type=PolarMix, + instance_classes=[0, 1, 2, 3, 4, 5, 6, 7], + swap_ratio=0.5, + rotate_paste_ratio=1.0, + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=4, + use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + ], + prob=[0.5, 0.5]), + dict( + type=GlobalRotScaleTrans, + rot_range=[0., 6.28318531], + scale_ratio_range=[0.95, 1.05], + translation_std=[0, 0, 0], + ), + dict(type=Pack3DDetInputs, keys=['points', 'pts_semantic_mask']) +] + +train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline))) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_80e_nus_seg.py new file mode 100644 index 0000000000..92bf949a17 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_80e_nus_seg.py @@ -0,0 +1,92 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_80e_nus_seg import * + +from mmcv.transforms.wrappers import RandomChoice + +from mmdet3d.datasets.transforms.formating import Pack3DDetInputs +from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D, + LoadPointsFromFile, + PointSegClassMapping) +from mmdet3d.datasets.transforms.transforms_3d import (GlobalRotScaleTrans, + LaserMix, PolarMix) + +train_pipeline = [ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping), + dict( + type=RandomChoice, + transforms=[ + [ + dict( + type=LaserMix, + num_areas=[3, 4, 5, 6], + pitch_angles=[-30, 10], + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + [ + dict( + type=PolarMix, + instance_classes=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], + swap_ratio=0.5, + rotate_paste_ratio=1.0, + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + ], + prob=[0.5, 0.5]), + dict( + type=GlobalRotScaleTrans, + rot_range=[0., 6.28318531], + scale_ratio_range=[0.95, 1.05], + translation_std=[0, 0, 0], + ), + dict(type=Pack3DDetInputs, keys=['points', 'pts_semantic_mask']) +] + +train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline))) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_50e_semantickitti.py new file mode 100644 index 0000000000..6108d42428 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_50e_semantickitti.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_aug_50e_semantickitti import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_80e_nus_seg.py new file mode 100644 index 0000000000..89d2f0f783 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/cylinder3d_8xb2_aug_amp_80e_nus_seg.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .cylinder3d_8xb2_aug_80e_nus_seg import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..c28f97b1e9 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_spconv_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + backbone=dict( + base_channels=16, + encoder_channels=[16, 32, 64, 128], + decoder_channels=[128, 64, 48, 48]), + decode_head=dict(channels=48))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..422ecd08dc --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_spconv_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_spconv_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + backbone=dict( + base_channels=16, + encoder_channels=[16, 32, 64, 128], + decoder_channels=[128, 64, 48, 48]), + decode_head=dict(channels=48))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..49584222ee --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + backbone=dict( + base_channels=16, + encoder_channels=[16, 32, 64, 128], + decoder_channels=[128, 64, 48, 48]), + decode_head=dict(channels=48))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..422ecd08dc --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w16_torchsparse2_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_spconv_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + backbone=dict( + base_channels=16, + encoder_channels=[16, 32, 64, 128], + decoder_channels=[128, 64, 48, 48]), + decode_head=dict(channels=48))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..9e3c84c8e4 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_spconv_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + backbone=dict( + base_channels=20, + encoder_channels=[20, 40, 81, 163], + decoder_channels=[163, 81, 61, 61]), + decode_head=dict(channels=61))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..5f254bf78b --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_spconv_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_spconv_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + backbone=dict( + base_channels=20, + encoder_channels=[20, 40, 81, 163], + decoder_channels=[163, 81, 61, 61]), + decode_head=dict(channels=61))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..85a213bcc3 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + backbone=dict( + base_channels=20, + encoder_channels=[20, 40, 81, 163], + decoder_channels=[163, 81, 61, 61]), + decode_head=dict(channels=61))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..eed583fc1b --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w20_torchsparse2_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,13 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + backbone=dict( + base_channels=20, + encoder_channels=[20, 40, 81, 163], + decoder_channels=[163, 81, 61, 61]), + decode_head=dict(channels=61))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..fd3271433b --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..09ec2479a9 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_spconv_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..926b0c5dc8 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,21 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.semantickitti import * + from .._base_.models.minkunet import * + from .._base_.schedules.lidarseg_50e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +model.update(dict(data_preprocessor=dict(max_voxels=None, batch_first=True))) + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) + +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..ed1981aa7a --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet18_w32_torchsparse2_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,29 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.nus_seg import * + from .._base_.models.minkunet import * + from .._base_.schedules.lidarseg_80e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +model.update( + dict( + data_preprocessor=dict( + max_voxels=None, + batch_first=True, + voxel_layer=dict(voxel_size=[0.1, 0.1, 0.1])), + decode_head=dict(num_classes=17, ignore_index=16))) + +train_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_train.pkl'))) +test_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_val.pkl'))) +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_50e_semantickitti.py new file mode 100644 index 0000000000..54e80a324c --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_50e_semantickitti.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_50e_semantickitti import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_80e_nus_seg.py new file mode 100644 index 0000000000..7acd447a53 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_80e_nus_seg.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_80e_nus_seg import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..389147d989 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_amp_50e_semantickitti import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..e771ad05aa --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_amp_80e_nus_seg import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_50e_semantickitti.py new file mode 100644 index 0000000000..aed1f2077b --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_50e_semantickitti.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_80e_nus_seg.py new file mode 100644 index 0000000000..f39bb9a8f8 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_80e_nus_seg.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_50e_semantickitti.py new file mode 100644 index 0000000000..4857438145 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_50e_semantickitti.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_amp_50e_semantickitti import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_80e_nus_seg.py new file mode 100644 index 0000000000..2ab21245e5 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_spconv_8xb2_aug_amp_80e_nus_seg.py @@ -0,0 +1,10 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_amp_80e_nus_seg import * + +model.update( + dict( + data_preprocessor=dict(batch_first=True), + backbone=dict(sparseconv_backend='spconv'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_50e_semantickitti.py new file mode 100644 index 0000000000..536a416ab2 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_50e_semantickitti.py @@ -0,0 +1,22 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.semantickitti import * + from .._base_.models.minkunet import * + from .._base_.schedules.lidarseg_50e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +model.update( + dict( + data_preprocessor=dict(max_voxels=None, batch_first=True), + backbone=dict(encoder_blocks=[2, 3, 4, 6]))) + +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_80e_nus_seg.py new file mode 100644 index 0000000000..d7d0883d52 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_80e_nus_seg.py @@ -0,0 +1,30 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .._base_.datasets.nus_seg import * + from .._base_.models.minkunet import * + from .._base_.schedules.lidarseg_80e import * + from .._base_.default_runtime import * + +from mmengine.hooks.checkpoint_hook import CheckpointHook +from mmengine.visualization.vis_backend import LocalVisBackend, WandbVisBackend + +model.update( + dict( + data_preprocessor=dict( + max_voxels=None, + batch_first=True, + voxel_layer=dict(voxel_size=[0.1, 0.1, 0.1])), + backbone=dict(encoder_blocks=[2, 3, 4, 6]), + decode_head=dict(num_classes=17, ignore_index=16))) + +train_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_train.pkl'))) +test_dataloader.update( + dict(dataset=dict(ann_file='nuscenes_lidarseg_infos_val.pkl'))) +visualizer.update( + dict(vis_backends=[dict(type=LocalVisBackend), + dict(type=WandbVisBackend)])) +default_hooks.update( + dict(checkpoint=dict(type=CheckpointHook, save_best='miou'))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_50e_semantickitti.py new file mode 100644 index 0000000000..748d267755 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_50e_semantickitti.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_50e_semantickitti import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_80e_nus_seg.py new file mode 100644 index 0000000000..17d9d6cd4c --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_amp_80e_nus_seg.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_80e_nus_seg import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti.py new file mode 100644 index 0000000000..c9d84a2da5 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti.py @@ -0,0 +1,88 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_50e_semantickitti import * + +from mmcv.transforms.wrappers import RandomChoice + +from mmdet3d.datasets.transforms.formating import Pack3DDetInputs +from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D, + LoadPointsFromFile, + PointSegClassMapping) +from mmdet3d.datasets.transforms.transforms_3d import (GlobalRotScaleTrans, + LaserMix, PolarMix) + +train_pipeline = [ + dict(type=LoadPointsFromFile, coord_type='LIDAR', load_dim=4, use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping), + dict( + type=RandomChoice, + transforms=[ + [ + dict( + type=LaserMix, + num_areas=[3, 4, 5, 6], + pitch_angles=[-25, 3], + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=4, + use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + [ + dict( + type=PolarMix, + instance_classes=[0, 1, 2, 3, 4, 5, 6, 7], + swap_ratio=0.5, + rotate_paste_ratio=1.0, + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=4, + use_dim=4), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.int32', + seg_offset=2**16, + dataset_type='semantickitti'), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + ], + prob=[0.5, 0.5]), + dict( + type=GlobalRotScaleTrans, + rot_range=[0., 6.28318531], + scale_ratio_range=[0.95, 1.05], + translation_std=[0, 0, 0], + ), + dict(type=Pack3DDetInputs, keys=['points', 'pts_semantic_mask']) +] + +train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg.py new file mode 100644 index 0000000000..a0b831ad69 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg.py @@ -0,0 +1,92 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_80e_nus_seg import * + +from mmcv.transforms.wrappers import RandomChoice + +from mmdet3d.datasets.transforms.formating import Pack3DDetInputs +from mmdet3d.datasets.transforms.loading import (LoadAnnotations3D, + LoadPointsFromFile, + PointSegClassMapping) +from mmdet3d.datasets.transforms.transforms_3d import (GlobalRotScaleTrans, + LaserMix, PolarMix) + +train_pipeline = [ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping), + dict( + type=RandomChoice, + transforms=[ + [ + dict( + type=LaserMix, + num_areas=[3, 4, 5, 6], + pitch_angles=[-30, 10], + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + [ + dict( + type=PolarMix, + instance_classes=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], + swap_ratio=0.5, + rotate_paste_ratio=1.0, + pre_transform=[ + dict( + type=LoadPointsFromFile, + coord_type='LIDAR', + load_dim=5, + use_dim=4, + backend_args=backend_args), + dict( + type=LoadAnnotations3D, + with_bbox_3d=False, + with_label_3d=False, + with_seg_3d=True, + seg_3d_dtype='np.uint8', + backend_args=backend_args), + dict(type=PointSegClassMapping) + ], + prob=1) + ], + ], + prob=[0.5, 0.5]), + dict( + type=GlobalRotScaleTrans, + rot_range=[0., 6.28318531], + scale_ratio_range=[0.95, 1.05], + translation_std=[0, 0, 0], + ), + dict(type=Pack3DDetInputs, keys=['points', 'pts_semantic_mask']) +] + +train_dataloader.update(dict(dataset=dict(pipeline=train_pipeline))) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_50e_semantickitti.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_50e_semantickitti.py new file mode 100644 index 0000000000..2f5d3b0557 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_50e_semantickitti.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_50e_semantickitti import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_80e_nus_seg.py b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_80e_nus_seg.py new file mode 100644 index 0000000000..390b5847d6 --- /dev/null +++ b/mmdet3d/configs/lidarseg_benchmark/minkunet34_w32_torchsparse2_8xb2_aug_amp_80e_nus_seg.py @@ -0,0 +1,7 @@ +# Copyright (c) OpenMMLab. All rights reserved. +from mmengine import read_base + +with read_base(): + from .minkunet34_w32_torchsparse2_8xb2_aug_80e_nus_seg import * + +optim_wrapper.update(dict(type='AmpOptimWrapper', loss_scale='dynamic')) diff --git a/mmdet3d/evaluation/functional/waymo_utils/compute_detection_metrics_main_single_process b/mmdet3d/evaluation/functional/waymo_utils/compute_detection_metrics_main_single_process new file mode 100755 index 0000000000000000000000000000000000000000..eda360c47825926eb7eaa8e27f87ec088de47181 GIT binary patch literal 1890944 zcmcG%3w%_?`3AfRw}_XG;3aC+R8heTO^{0>UJ@X17I!6bQMAPnLITl{#AFwO6$mDa z9M_f97E7&E)LN<4N>!Aikc3;}Jz%Q{DiJT7HF6OY5s`e)Gc#v*Hp#L6f8X~VJehf) zdFTGlJMYYySr_DZM<*sExa=p?(EO9-%5e3@-~O&kTs=W| z7Z^hrmKEowB?{7IyGfFCb%V=zWK!k921)I!(~F z>q?fvjK{L}e@KS+|Jy_nV7tbdl5cya%1Omz@kG33D&9&JPq|sD{I+Y?k9FgFzY4!U zF$)ywEIO`K@i*p@mrw5J{^|5jJVWL;@eG-t?VeUH*j%=2$GZ{nSk9mOsOq_TAp+BI zY8RW&cJ2C&SNS=`+kS#9iS63)epOODZRp@%l}x{)q_{LtbwyRi&?|-x9#~m6aF8em 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b/mmdet3d/models/backbones/spvcnn_backone.py @@ -12,7 +12,9 @@ import torchsparse import torchsparse.nn.functional as F from torchsparse.nn.utils import get_kernel_offsets - from torchsparse.tensor import PointTensor, SparseTensor + + # from torchsparse.tensor import PointTensor, SparseTensor + PointTensor = SparseTensor = None else: PointTensor = SparseTensor = None diff --git a/mmdet3d/models/layers/torchsparse_block.py b/mmdet3d/models/layers/torchsparse_block.py index 727db5f3da..540f960f78 100644 --- a/mmdet3d/models/layers/torchsparse_block.py +++ b/mmdet3d/models/layers/torchsparse_block.py @@ -37,6 +37,7 @@ def __init__(self, out_channels: int, kernel_size: Union[int, Sequence[int]], stride: Union[int, Sequence[int]] = 1, + padding: Union[int, Sequence[int]] = 0, dilation: int = 1, bias: bool = False, transposed: bool = False, @@ -47,8 +48,15 @@ def __init__(self, **kwargs) -> None: super().__init__(init_cfg) layers = [ - spnn.Conv3d(in_channels, out_channels, kernel_size, stride, - dilation, bias, transposed) + spnn.Conv3d( + in_channels=in_channels, + out_channels=out_channels, + kernel_size=kernel_size, + stride=stride, + padding=padding, + dilation=dilation, + bias=bias, + transposed=transposed) ] if norm_cfg is not None: _, norm = build_norm_layer(norm_cfg, out_channels) @@ -93,8 +101,13 @@ def __init__(self, _, norm2 = build_norm_layer(norm_cfg, out_channels) self.net = nn.Sequential( - spnn.Conv3d(in_channels, out_channels, kernel_size, stride, - dilation, bias), norm1, spnn.ReLU(inplace=True), + spnn.Conv3d( + in_channels, + out_channels, + kernel_size, + stride, + dilation=dilation, + bias=bias), norm1, spnn.ReLU(inplace=True), spnn.Conv3d( out_channels, out_channels, diff --git a/requirements/mminstall.txt b/requirements/mminstall.txt index 066a0ae47d..499aaccb11 100644 --- a/requirements/mminstall.txt +++ b/requirements/mminstall.txt @@ -1,3 +1,3 @@ mmcv>=2.0.0rc4,<2.2.0 -mmdet>=3.0.0,<3.3.0 +mmdet>=3.0.0rc5,<3.4.0 mmengine>=0.7.1,<1.0.0