sung98/sdtagnet-nusc-r50-30ep-newsplit-longrange

SDTagNet - nuScenes (new split, long range), ResNet-50, 30ep schedule

Best checkpoints from an SDTagNet training run on nuScenes with the new split and the 100 x 50 m long-range setting (pc_range = [-25, -50, -10, 25, 50, 10], BEV (200, 100)). ResNet-50 image backbone, camera-only SDTagNet, 30-epoch schedule.

This repository replaces the earlier upload under the same repo name with the later sdtagnet_nusc_r50_30ep_100_50_range_mapping_last run.

Evaluation on long-range new-split val

Checkpoint	Save time (UTC)	NuscMap_chamfer/mAP	divider_AP	boundary_AP	ped_crossing_AP
mAP_epoch_8.pth	2026-04-29 22:15	0.2070	0.2399	0.2700	0.1112
mAP_epoch_20.pth	2026-04-30 19:49	0.2251	0.2490	0.3077	0.1188

AP by chamfer threshold (@1.0 / @1.5 / @2.0 m):

mAP_epoch_8.pth

Class	@1.0	@1.5	@2.0
divider	0.1364	0.2490	0.3343
boundary	0.1064	0.2837	0.4197
ped_crossing	0.0349	0.1112	0.1876

mAP_epoch_20.pth

Class	@1.0	@1.5	@2.0
divider	0.1534	0.2587	0.3348
boundary	0.1293	0.3199	0.4737
ped_crossing	0.0368	0.1187	0.2009

Recorded mAP progression:

Epoch	mAP
2	0.1345
4	0.1855
6	0.1965
8	0.2070
10	0.2157
12	0.2180
14	0.2240
16	0.2200
18	0.2238
20	0.2251
22	0.2210

Range / BEV / modality

• pc_range = [-25.0, -50.0, -10.0, 25.0, 50.0, 10.0]
• bev_size = (200, 100)
• use_lidar = False (camera-only SDTagNet)
• Image backbone: ResNet-50
• Training schedule in the saved config: 30 epochs

Files

Path	Description
mAP_epoch_8.pth	Best checkpoint at epoch 8 (~579 MB)
mAP_epoch_20.pth	Best checkpoint at epoch 20, highest recorded mAP in this run (~579 MB)
sdtagnet_nusc_r50_30ep_100_50_range_mapping_last.py	Exact config snapshot saved in the work_dir
logs/20260429_103003.log / .log.json	Training/eval log covering epochs 2-8
logs/20260430_021112.log / .log.json	Continuation log covering epochs 10-22

Config notes

The config expects:

• data_root = '/datasets/public/nuscenes/'
• train/val pkl: nuscenes_map_infos_temporal_newsplit_100x50_{train,val}.pkl
• eval json: nuscenes_map_anns_val_sdtagnet_100x50.json
• work_dir = './work_dirs/sdtagnet_nusc_r50_30ep_100_50_range_mapping_last'

Override paths for your own environment.

Related checkpoints

• sung98/sdtagnet-nusc-r50-110ep-newsplit - SDTagNet, standard range, new split
• sung98/sdtagnet-nusc-r50-30ep-oldsplit - SDTagNet, old split, standard range
• sung98/maptrv2-nusc-r50-110ep-lidar-newsplit - MapTRv2 LiDAR, new split
• sung98/maptrv2-nusc-r50-24ep-lidar-oldsplit - MapTRv2 LiDAR, old split
• sung98/maptrv2-nusc-r50-24ep-lidar-newsplit-longrange - MapTRv2 LiDAR, long range, new split

Numbers across runs are not directly comparable (different range / split / eval thresholds / model).

Loading

from mmcv import Config
from mmdet3d.models import build_model
from mmcv.runner import load_checkpoint

cfg = Config.fromfile('sdtagnet_nusc_r50_30ep_100_50_range_mapping_last.py')
cfg.model.train_cfg = None
model = build_model(cfg.model, test_cfg=cfg.get('test_cfg'))
load_checkpoint(model, 'mAP_epoch_20.pth', map_location='cpu')
model.eval()