log.test.10-21_09-17-17.dec5c0617569.txt


2022-10-21 09:17:17,749 adals INFO: 1 GPUs available
2022-10-21 09:17:17,749 adals INFO: Namespace(ckpt2d='@/model_2d_085000.pth', ckpt3d='@/model_3d_090000.pth', config_file='ADALS/config/kitti2nuscenes/adals_sn.yaml')
2022-10-21 09:17:17,749 adals INFO: Loaded configuration file ADALS/config/kitti2nuscenes/adals_sn.yaml
2022-10-21 09:17:17,749 adals INFO: Running with config:
AUTO_RESUME: True
DATALOADER:
  DROP_LAST: True
  NUM_WORKERS: 4
DATASET_SOURCE:
  SemanticKITTISCN:
    augmentation:
      cut_image: True
      cut_range: [512, 512]
      flip_y: 0.5
      height: 64
      noisy_rot: 0.1
      random_flip: True
      remove_large: True
      rot_z: 6.2831
      transl: True
      width: 2048
    full_scale: 4096
    merge_classes: True
    nuscenes: True
    root_dir: /_data/datasets/SemanticKITTI
    scale: 20
    trgl_dir: /_data/datasets/SemanticKITTI/semantic_kitti2nuscenes
  TRAIN: ('train',)
  TYPE: SemanticKITTISCN
DATASET_TARGET:
  NuScenesSCN:
    augmentation:
      cut_image: True
      cut_range: [512, 512]
      flip_x: 0.5
      height: 32
      noisy_rot: 0.1
      random_flip: True
      remove_large: True
      rot_z: 6.2831
      transl: True
      width: 1024
    full_scale: 4096
    lidarseg: False
    merge_classes: True
    root_dir: /_data/datasets/nuScenes/data/nuscenes
    scale: 20
  TEST: ('test_all',)
  TRAIN: ('train_all',)
  TYPE: NuScenesSCN
  VAL: ('val_all',)
MODEL:
  TYPE: 
MODEL_2D:
  CKPT_PATH: 
  DUAL_HEAD: True
  NUM_CLASSES: 6
  SalsaNextSeg:
    in_channels: 5
  TYPE: SalsaNextSeg
MODEL_3D:
  CKPT_PATH: 
  DUAL_HEAD: True
  NUM_CLASSES: 6
  SCN:
    block_reps: 1
    full_scale: 4096
    in_channels: 1
    m: 16
    num_planes: 7
    residual_blocks: False
  TYPE: SCN
OPTIMIZER:
  BASE_LR: 0.001
  TYPE: 
  WEIGHT_DECAY: 0.0
OPTIMIZER_2D:
  BASE_LR: 0.0025
  SGD:
    dampening: 0.0
    momentum: 0.9
  TYPE: SGD
  WEIGHT_DECAY: 0.0
OPTIMIZER_3D:
  Adam:
    betas: (0.9, 0.999)
  BASE_LR: 0.001
  TYPE: Adam
  WEIGHT_DECAY: 0.0
OPTIMIZER_DIS:
  Adam:
    betas: (0.9, 0.99)
  BASE_LR: 0.0001
  TYPE: Adam
  WEIGHT_DECAY: 0.0
OUTPUT_DIR: /workspace/DA-LPS/ADALS/output/@
RESUME_PATH: 
RESUME_STATES: True
RNG_SEED: 1
SCHEDULER:
  CLIP_LR: 0.0
  MAX_ITERATION: 100000
  MultiStepLR:
    gamma: 0.1
    milestones: (80000, 90000)
  TYPE: MultiStepLR
SCHEDULER_DIS:
  PolyLR:
    power: 0.9
  TYPE: PolyLR
TRAIN:
  ADALS:
    lambda_D_src_2d_feat: 0.1
    lambda_D_src_2d_pred: 0.1
    lambda_D_src_3d_pred: 0.1
    lambda_D_trg_2d_feat: 0.2
    lambda_D_trg_2d_pred: 0.2
    lambda_D_trg_3d_pred: 0.2
    lambda_G_trg_2d_feat: 0.001
    lambda_G_trg_2d_pred: 0.07
    lambda_G_trg_3d_pred: 0.05
    lambda_logcoral: 0.0
    lambda_minent: 0.0
    lambda_pixels: 0.1
    lambda_xm_src: 0.1
    lambda_xm_tgl: 0.02
    lambda_xm_trg: 0.01
  BATCH_SIZE: 8
  CHECKPOINT_PERIOD: 5000
  CLASS_WEIGHTS: [1.66759149, 1.09394955, 1.23188501, 1.09613089, 1.43978661, 1.0]
  FROZEN_PATTERNS: ()
  LOG_PERIOD: 50
  MAX_TO_KEEP: 100
  SUMMARY_PERIOD: 50
VAL:
  BATCH_SIZE: 6
  KNN:
    cutoff: 1.0
    knn: 5
    search: 5
    sigma: 1.0
  LOG_PERIOD: 20
  METRIC: seg_iou
  PERIOD: 5000
2022-10-21 09:18:15,847 adals.validate INFO: Validation
2022-10-21 09:18:21,043 adals.validate INFO: iter: 1/1004  seg_loss_2d_point: 1.0734 (1.0734)  seg_loss_2d_pixel: 0.7889 (0.7889)  seg_loss_3d: 0.4688 (0.4688)  time: 5.1798 (5.1798)  data: 1.6292 (1.6292)  max mem: 2148
2022-10-21 09:18:54,328 adals.validate INFO: iter: 20/1004  seg_loss_2d_point: 0.7364 (0.7364)  seg_loss_2d_pixel: 0.7523 (0.7523)  seg_loss_3d: 0.4088 (0.4088)  time: 1.9233 (1.9233)  data: 0.1172 (0.1172)  max mem: 2396
2022-10-21 09:19:25,371 adals.validate INFO: iter: 40/1004  seg_loss_2d_point: 0.7917 (0.7641)  seg_loss_2d_pixel: 0.8402 (0.7962)  seg_loss_3d: 0.4213 (0.4150)  time: 1.5522 (1.7377)  data: 0.0269 (0.0721)  max mem: 2529
2022-10-21 09:19:57,872 adals.validate INFO: iter: 60/1004  seg_loss_2d_point: 0.8180 (0.7820)  seg_loss_2d_pixel: 0.8455 (0.8126)  seg_loss_3d: 0.5752 (0.4684)  time: 1.6250 (1.7002)  data: 0.0278 (0.0573)  max mem: 2764
2022-10-21 09:20:21,334 adals.validate INFO: iter: 80/1004  seg_loss_2d_point: 0.6564 (0.7506)  seg_loss_2d_pixel: 0.7130 (0.7877)  seg_loss_3d: 0.4981 (0.4758)  time: 1.1731 (1.5684)  data: 0.0311 (0.0508)  max mem: 2764
2022-10-21 09:20:47,964 adals.validate INFO: iter: 100/1004  seg_loss_2d_point: 0.5123 (0.7030)  seg_loss_2d_pixel: 0.6172 (0.7536)  seg_loss_3d: 0.3304 (0.4467)  time: 1.3315 (1.5210)  data: 0.0508 (0.0508)  max mem: 3204
2022-10-21 09:21:37,401 adals.validate INFO: iter: 120/1004  seg_loss_2d_point: 0.8018 (0.7194)  seg_loss_2d_pixel: 0.6276 (0.7326)  seg_loss_3d: 0.2984 (0.4220)  time: 2.4718 (1.6795)  data: 0.0382 (0.0487)  max mem: 4473
2022-10-21 09:22:17,536 adals.validate INFO: iter: 140/1004  seg_loss_2d_point: 0.6538 (0.7101)  seg_loss_2d_pixel: 0.5262 (0.7031)  seg_loss_3d: 0.3006 (0.4047)  time: 2.0067 (1.7262)  data: 0.0319 (0.0463)  max mem: 4473
2022-10-21 09:22:47,509 adals.validate INFO: iter: 160/1004  seg_loss_2d_point: 0.6648 (0.7044)  seg_loss_2d_pixel: 0.6393 (0.6952)  seg_loss_3d: 0.3407 (0.3967)  time: 1.4986 (1.6978)  data: 0.0306 (0.0443)  max mem: 4473
2022-10-21 09:23:13,810 adals.validate INFO: iter: 180/1004  seg_loss_2d_point: 0.4791 (0.6794)  seg_loss_2d_pixel: 0.5860 (0.6830)  seg_loss_3d: 0.3494 (0.3914)  time: 1.3151 (1.6553)  data: 0.0279 (0.0425)  max mem: 4473
2022-10-21 09:23:46,699 adals.validate INFO: iter: 200/1004  seg_loss_2d_point: 0.7815 (0.6896)  seg_loss_2d_pixel: 0.8344 (0.6982)  seg_loss_3d: 0.5191 (0.4042)  time: 1.6445 (1.6542)  data: 0.0272 (0.0410)  max mem: 4473
2022-10-21 09:24:23,742 adals.validate INFO: iter: 220/1004  seg_loss_2d_point: 0.7783 (0.6976)  seg_loss_2d_pixel: 0.7203 (0.7002)  seg_loss_3d: 0.3277 (0.3972)  time: 1.8521 (1.6722)  data: 0.0279 (0.0398)  max mem: 4473
2022-10-21 09:25:04,020 adals.validate INFO: iter: 240/1004  seg_loss_2d_point: 0.7613 (0.7029)  seg_loss_2d_pixel: 0.7350 (0.7031)  seg_loss_3d: 0.4184 (0.3990)  time: 2.0139 (1.7006)  data: 0.0271 (0.0387)  max mem: 4473
2022-10-21 09:25:30,143 adals.validate INFO: iter: 260/1004  seg_loss_2d_point: 0.6826 (0.7014)  seg_loss_2d_pixel: 0.7521 (0.7069)  seg_loss_3d: 0.4753 (0.4049)  time: 1.3062 (1.6703)  data: 0.0316 (0.0382)  max mem: 4473
2022-10-21 09:26:08,144 adals.validate INFO: iter: 280/1004  seg_loss_2d_point: 0.7552 (0.7052)  seg_loss_2d_pixel: 0.7425 (0.7094)  seg_loss_3d: 0.5780 (0.4172)  time: 1.9000 (1.6867)  data: 0.0297 (0.0376)  max mem: 4473
2022-10-21 09:26:46,338 adals.validate INFO: iter: 300/1004  seg_loss_2d_point: 0.7050 (0.7052)  seg_loss_2d_pixel: 0.6748 (0.7071)  seg_loss_3d: 0.4277 (0.4179)  time: 1.9097 (1.7016)  data: 0.0277 (0.0369)  max mem: 4473
2022-10-21 09:27:37,692 adals.validate INFO: iter: 320/1004  seg_loss_2d_point: 0.8956 (0.7171)  seg_loss_2d_pixel: 0.6577 (0.7040)  seg_loss_3d: 0.3783 (0.4154)  time: 2.5677 (1.7557)  data: 0.0302 (0.0365)  max mem: 4473
2022-10-21 09:28:14,381 adals.validate INFO: iter: 340/1004  seg_loss_2d_point: 0.6538 (0.7134)  seg_loss_2d_pixel: 0.7312 (0.7056)  seg_loss_3d: 0.3533 (0.4118)  time: 1.8344 (1.7603)  data: 0.0283 (0.0360)  max mem: 4473
2022-10-21 09:28:39,237 adals.validate INFO: iter: 360/1004  seg_loss_2d_point: 0.5683 (0.7053)  seg_loss_2d_pixel: 0.5831 (0.6988)  seg_loss_3d: 0.2669 (0.4037)  time: 1.2428 (1.7316)  data: 0.0279 (0.0355)  max mem: 4473
2022-10-21 09:29:20,039 adals.validate INFO: iter: 380/1004  seg_loss_2d_point: 0.6575 (0.7028)  seg_loss_2d_pixel: 0.6516 (0.6963)  seg_loss_3d: 0.3639 (0.4016)  time: 2.0401 (1.7478)  data: 0.0298 (0.0352)  max mem: 4473
2022-10-21 09:30:16,899 adals.validate INFO: iter: 400/1004  seg_loss_2d_point: 0.6504 (0.7002)  seg_loss_2d_pixel: 0.5616 (0.6896)  seg_loss_3d: 0.2981 (0.3965)  time: 2.8430 (1.8026)  data: 0.0280 (0.0349)  max mem: 4473
2022-10-21 09:30:56,008 adals.validate INFO: iter: 420/1004  seg_loss_2d_point: 0.5161 (0.6914)  seg_loss_2d_pixel: 0.5069 (0.6809)  seg_loss_3d: 0.1524 (0.3848)  time: 1.9554 (1.8099)  data: 0.0289 (0.0346)  max mem: 4473
2022-10-21 09:31:38,577 adals.validate INFO: iter: 440/1004  seg_loss_2d_point: 0.7927 (0.6960)  seg_loss_2d_pixel: 0.7258 (0.6829)  seg_loss_3d: 0.3120 (0.3815)  time: 2.1285 (1.8243)  data: 0.0280 (0.0343)  max mem: 4473
2022-10-21 09:32:22,330 adals.validate INFO: iter: 460/1004  seg_loss_2d_point: 0.8592 (0.7031)  seg_loss_2d_pixel: 0.6756 (0.6826)  seg_loss_3d: 0.4870 (0.3861)  time: 2.1876 (1.8401)  data: 0.0279 (0.0340)  max mem: 4473
2022-10-21 09:32:57,022 adals.validate INFO: iter: 480/1004  seg_loss_2d_point: 0.7358 (0.7045)  seg_loss_2d_pixel: 0.8218 (0.6884)  seg_loss_3d: 0.4755 (0.3898)  time: 1.7346 (1.8357)  data: 0.0274 (0.0337)  max mem: 4473
2022-10-21 09:33:33,625 adals.validate INFO: iter: 500/1004  seg_loss_2d_point: 0.9331 (0.7136)  seg_loss_2d_pixel: 0.9576 (0.6992)  seg_loss_3d: 0.5855 (0.3977)  time: 1.8301 (1.8355)  data: 0.0261 (0.0334)  max mem: 4473
2022-10-21 09:34:14,977 adals.validate INFO: iter: 520/1004  seg_loss_2d_point: 0.9752 (0.7237)  seg_loss_2d_pixel: 0.9738 (0.7097)  seg_loss_3d: 0.8676 (0.4157)  time: 2.0676 (1.8444)  data: 0.0271 (0.0332)  max mem: 4687
2022-10-21 09:35:05,127 adals.validate INFO: iter: 540/1004  seg_loss_2d_point: 1.0388 (0.7354)  seg_loss_2d_pixel: 0.9976 (0.7204)  seg_loss_3d: 0.6264 (0.4235)  time: 2.5075 (1.8690)  data: 0.0276 (0.0330)  max mem: 4687
2022-10-21 09:36:00,489 adals.validate INFO: iter: 560/1004  seg_loss_2d_point: 1.1350 (0.7496)  seg_loss_2d_pixel: 0.8714 (0.7258)  seg_loss_3d: 0.3971 (0.4226)  time: 2.7681 (1.9011)  data: 0.0265 (0.0328)  max mem: 4687
2022-10-21 09:36:55,547 adals.validate INFO: iter: 580/1004  seg_loss_2d_point: 1.1092 (0.7620)  seg_loss_2d_pixel: 0.8156 (0.7289)  seg_loss_3d: 0.3495 (0.4201)  time: 2.7529 (1.9305)  data: 0.0273 (0.0326)  max mem: 4687
2022-10-21 09:37:39,881 adals.validate INFO: iter: 600/1004  seg_loss_2d_point: 0.6235 (0.7574)  seg_loss_2d_pixel: 0.5479 (0.7229)  seg_loss_3d: 0.2291 (0.4137)  time: 2.2167 (1.9400)  data: 0.0282 (0.0324)  max mem: 4687
2022-10-21 09:38:27,603 adals.validate INFO: iter: 620/1004  seg_loss_2d_point: 0.7011 (0.7556)  seg_loss_2d_pixel: 0.6705 (0.7212)  seg_loss_3d: 0.3279 (0.4109)  time: 2.3861 (1.9544)  data: 0.0276 (0.0323)  max mem: 4687
2022-10-21 09:38:58,557 adals.validate INFO: iter: 640/1004  seg_loss_2d_point: 0.7968 (0.7569)  seg_loss_2d_pixel: 0.6812 (0.7199)  seg_loss_3d: 0.3392 (0.4087)  time: 1.5477 (1.9417)  data: 0.0290 (0.0322)  max mem: 4687
2022-10-21 09:39:22,335 adals.validate INFO: iter: 660/1004  seg_loss_2d_point: 0.7446 (0.7565)  seg_loss_2d_pixel: 0.7939 (0.7222)  seg_loss_3d: 0.4417 (0.4097)  time: 1.1889 (1.9189)  data: 0.0274 (0.0320)  max mem: 4687
2022-10-21 09:39:50,728 adals.validate INFO: iter: 680/1004  seg_loss_2d_point: 0.6685 (0.7539)  seg_loss_2d_pixel: 0.7987 (0.7244)  seg_loss_3d: 0.3901 (0.4091)  time: 1.4197 (1.9042)  data: 0.0279 (0.0319)  max mem: 4687
2022-10-21 09:40:25,839 adals.validate INFO: iter: 700/1004  seg_loss_2d_point: 0.8813 (0.7576)  seg_loss_2d_pixel: 0.8042 (0.7267)  seg_loss_3d: 0.3086 (0.4063)  time: 1.7556 (1.9000)  data: 0.0285 (0.0318)  max mem: 4687
2022-10-21 09:40:50,336 adals.validate INFO: iter: 720/1004  seg_loss_2d_point: 0.7847 (0.7583)  seg_loss_2d_pixel: 0.8233 (0.7294)  seg_loss_3d: 0.3825 (0.4056)  time: 1.2248 (1.8812)  data: 0.0285 (0.0317)  max mem: 4687
2022-10-21 09:41:16,372 adals.validate INFO: iter: 740/1004  seg_loss_2d_point: 1.0427 (0.7660)  seg_loss_2d_pixel: 1.0690 (0.7386)  seg_loss_3d: 0.9455 (0.4202)  time: 1.3018 (1.8655)  data: 0.0279 (0.0316)  max mem: 4687
2022-10-21 09:41:47,659 adals.validate INFO: iter: 760/1004  seg_loss_2d_point: 0.8111 (0.7672)  seg_loss_2d_pixel: 0.7660 (0.7393)  seg_loss_3d: 0.4857 (0.4219)  time: 1.5643 (1.8576)  data: 0.0278 (0.0315)  max mem: 4687
2022-10-21 09:42:17,077 adals.validate INFO: iter: 780/1004  seg_loss_2d_point: 0.7956 (0.7679)  seg_loss_2d_pixel: 0.8433 (0.7419)  seg_loss_3d: 0.4612 (0.4229)  time: 1.4709 (1.8477)  data: 0.0273 (0.0314)  max mem: 4687
2022-10-21 09:42:39,182 adals.validate INFO: iter: 800/1004  seg_loss_2d_point: 0.6463 (0.7649)  seg_loss_2d_pixel: 0.7382 (0.7418)  seg_loss_3d: 0.3972 (0.4223)  time: 1.1053 (1.8291)  data: 0.0282 (0.0313)  max mem: 4687
2022-10-21 09:43:12,919 adals.validate INFO: iter: 820/1004  seg_loss_2d_point: 0.8275 (0.7664)  seg_loss_2d_pixel: 0.8834 (0.7453)  seg_loss_3d: 0.4410 (0.4227)  time: 1.6868 (1.8257)  data: 0.0294 (0.0313)  max mem: 4687
2022-10-21 09:43:42,285 adals.validate INFO: iter: 840/1004  seg_loss_2d_point: 0.8136 (0.7675)  seg_loss_2d_pixel: 0.8866 (0.7487)  seg_loss_3d: 0.4625 (0.4237)  time: 1.4683 (1.8172)  data: 0.0281 (0.0312)  max mem: 4687
2022-10-21 09:44:14,456 adals.validate INFO: iter: 860/1004  seg_loss_2d_point: 0.7525 (0.7672)  seg_loss_2d_pixel: 0.7146 (0.7479)  seg_loss_3d: 0.4096 (0.4234)  time: 1.6085 (1.8123)  data: 0.0296 (0.0312)  max mem: 4687
2022-10-21 09:44:59,349 adals.validate INFO: iter: 880/1004  seg_loss_2d_point: 0.7288 (0.7663)  seg_loss_2d_pixel: 0.7236 (0.7473)  seg_loss_3d: 0.3504 (0.4217)  time: 2.2446 (1.8221)  data: 0.0290 (0.0311)  max mem: 4687
2022-10-21 09:45:35,715 adals.validate INFO: iter: 900/1004  seg_loss_2d_point: 0.7164 (0.7652)  seg_loss_2d_pixel: 0.7255 (0.7468)  seg_loss_3d: 0.4329 (0.4219)  time: 1.8183 (1.8221)  data: 0.0274 (0.0310)  max mem: 4687
2022-10-21 09:46:04,341 adals.validate INFO: iter: 920/1004  seg_loss_2d_point: 0.8665 (0.7674)  seg_loss_2d_pixel: 0.8853 (0.7498)  seg_loss_3d: 0.6724 (0.4274)  time: 1.4313 (1.8136)  data: 0.0283 (0.0310)  max mem: 4687
2022-10-21 09:46:35,191 adals.validate INFO: iter: 940/1004  seg_loss_2d_point: 0.7447 (0.7669)  seg_loss_2d_pixel: 0.8139 (0.7512)  seg_loss_3d: 0.5165 (0.4293)  time: 1.5425 (1.8078)  data: 0.0275 (0.0309)  max mem: 4687
2022-10-21 09:47:00,063 adals.validate INFO: iter: 960/1004  seg_loss_2d_point: 0.6330 (0.7641)  seg_loss_2d_pixel: 0.6830 (0.7498)  seg_loss_3d: 0.4318 (0.4293)  time: 1.2436 (1.7960)  data: 0.0280 (0.0308)  max mem: 4687
2022-10-21 09:47:32,698 adals.validate INFO: iter: 980/1004  seg_loss_2d_point: 0.7461 (0.7638)  seg_loss_2d_pixel: 0.7217 (0.7492)  seg_loss_3d: 0.3761 (0.4283)  time: 1.6318 (1.7927)  data: 0.0271 (0.0308)  max mem: 4687
2022-10-21 09:48:02,549 adals.validate INFO: iter: 1000/1004  seg_loss_2d_point: 0.6953 (0.7624)  seg_loss_2d_pixel: 0.7554 (0.7493)  seg_loss_3d: 0.4317 (0.4283)  time: 1.4926 (1.7867)  data: 0.0273 (0.0307)  max mem: 4687
2022-10-21 09:48:08,136 adals.validate INFO: 2D Point overall accuracy=74.02%
2022-10-21 09:48:08,136 adals.validate INFO: 2D Point overall IOU=51.91
2022-10-21 09:48:08,143 adals.validate INFO: 2D Point class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      64.20 | 50.10 | 10205497 |
| driveable_surface |      85.03 | 76.14 | 56047567 |
| sidewalk          |      41.56 | 29.95 | 12630603 |
| manmade           |      72.33 | 58.17 | 31666701 |
| terrain           |      55.95 | 43.86 | 13619746 |
| vegetation        |      82.78 | 53.23 | 21948012 |
+-------------------+------------+-------+----------+
2022-10-21 09:48:08,144 adals.validate INFO: 2D Pixel overall accuracy=73.95%
2022-10-21 09:48:08,144 adals.validate INFO: 2D Pixel overall IOU=52.18
2022-10-21 09:48:08,144 adals.validate INFO: 2D Pixel class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      72.80 | 40.95 | 10677430 |
| driveable_surface |      81.95 | 77.22 | 54844581 |
| sidewalk          |      54.93 | 34.02 | 12171662 |
| manmade           |      68.85 | 59.08 | 34481419 |
| terrain           |      61.76 | 41.47 | 13108653 |
| vegetation        |      79.15 | 60.35 | 27021702 |
+-------------------+------------+-------+----------+
2022-10-21 09:48:08,144 adals.validate INFO: 3D overall accuracy=86.08%
2022-10-21 09:48:08,144 adals.validate INFO: 3D overall IOU=70.69
2022-10-21 09:48:08,145 adals.validate INFO: 3D class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      79.43 | 78.59 | 10205497 |
| driveable_surface |      92.36 | 88.67 | 56047567 |
| sidewalk          |      79.34 | 51.94 | 12630603 |
| manmade           |      85.76 | 77.45 | 31666701 |
| terrain           |      64.88 | 53.72 | 13619746 |
| vegetation        |      90.60 | 73.78 | 21948012 |
+-------------------+------------+-------+----------+
2022-10-21 09:48:08,145 adals.validate INFO: 2D+3D overall accuracy=86.71%
2022-10-21 09:48:08,145 adals.validate INFO: 2D+3D overall IOU=71.27
2022-10-21 09:48:08,146 adals.validate INFO: 2D+3D class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      79.63 | 77.40 | 10205497 |
| driveable_surface |      94.05 | 89.72 | 56047567 |
| sidewalk          |      73.55 | 53.40 | 12630603 |
| manmade           |      85.77 | 77.81 | 31666701 |
| terrain           |      67.06 | 56.22 | 13619746 |
| vegetation        |      92.36 | 73.08 | 21948012 |
+-------------------+------------+-------+----------+
