2022-11-07 10:56:19,879 adals INFO: 1 GPUs available
2022-11-07 10:56:19,879 adals INFO: Namespace(ckpt2d='@/model_2d_075000.pth', ckpt3d='@/model_3d_085000.pth', config_file='ADALS/config/kitti2nuscenes/adals_sn.yaml')
2022-11-07 10:56:19,879 adals INFO: Loaded configuration file ADALS/config/kitti2nuscenes/adals_sn.yaml
2022-11-07 10:56:19,879 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
2022-11-07 10:57:14,310 adals.validate INFO: Validation
2022-11-07 10:57:18,426 adals.validate INFO: iter: 1/1004  seg_loss_2d_point: 0.5464 (0.5464)  seg_loss_2d_pixel: 0.7206 (0.7206)  seg_loss_3d: 0.4205 (0.4205)  time: 4.1153 (4.1153)  data: 1.0943 (1.0943)  max mem: 2148
2022-11-07 10:57:49,830 adals.validate INFO: iter: 20/1004  seg_loss_2d_point: 0.7083 (0.7083)  seg_loss_2d_pixel: 0.8048 (0.8048)  seg_loss_3d: 0.4459 (0.4459)  time: 1.7760 (1.7760)  data: 0.0831 (0.0831)  max mem: 2396
2022-11-07 10:58:20,342 adals.validate INFO: iter: 40/1004  seg_loss_2d_point: 0.8043 (0.7563)  seg_loss_2d_pixel: 0.8858 (0.8453)  seg_loss_3d: 0.4590 (0.4524)  time: 1.5256 (1.6508)  data: 0.0278 (0.0555)  max mem: 2529
2022-11-07 10:58:51,082 adals.validate INFO: iter: 60/1004  seg_loss_2d_point: 0.7398 (0.7508)  seg_loss_2d_pixel: 0.8229 (0.8379)  seg_loss_3d: 0.5736 (0.4928)  time: 1.5370 (1.6129)  data: 0.0282 (0.0464)  max mem: 2764
2022-11-07 10:59:13,721 adals.validate INFO: iter: 80/1004  seg_loss_2d_point: 0.6445 (0.7242)  seg_loss_2d_pixel: 0.7456 (0.8148)  seg_loss_3d: 0.4867 (0.4913)  time: 1.1319 (1.4926)  data: 0.0294 (0.0421)  max mem: 2764
2022-11-07 10:59:38,792 adals.validate INFO: iter: 100/1004  seg_loss_2d_point: 0.5976 (0.6989)  seg_loss_2d_pixel: 0.7366 (0.7992)  seg_loss_3d: 0.2961 (0.4523)  time: 1.2536 (1.4448)  data: 0.0274 (0.0392)  max mem: 3204
2022-11-07 11:00:25,822 adals.validate INFO: iter: 120/1004  seg_loss_2d_point: 0.6590 (0.6923)  seg_loss_2d_pixel: 0.6534 (0.7749)  seg_loss_3d: 0.2680 (0.4215)  time: 2.3515 (1.5959)  data: 0.0274 (0.0372)  max mem: 4473
2022-11-07 11:01:03,856 adals.validate INFO: iter: 140/1004  seg_loss_2d_point: 0.6787 (0.6903)  seg_loss_2d_pixel: 0.5821 (0.7473)  seg_loss_3d: 0.2537 (0.3976)  time: 1.9017 (1.6396)  data: 0.0280 (0.0359)  max mem: 4473
2022-11-07 11:01:32,874 adals.validate INFO: iter: 160/1004  seg_loss_2d_point: 0.6437 (0.6845)  seg_loss_2d_pixel: 0.6670 (0.7373)  seg_loss_3d: 0.2758 (0.3823)  time: 1.4509 (1.6160)  data: 0.0271 (0.0348)  max mem: 4473
2022-11-07 11:01:57,504 adals.validate INFO: iter: 180/1004  seg_loss_2d_point: 0.4993 (0.6639)  seg_loss_2d_pixel: 0.6826 (0.7312)  seg_loss_3d: 0.2643 (0.3692)  time: 1.2315 (1.5733)  data: 0.0289 (0.0341)  max mem: 4473
2022-11-07 11:02:28,413 adals.validate INFO: iter: 200/1004  seg_loss_2d_point: 0.7641 (0.6739)  seg_loss_2d_pixel: 0.9211 (0.7502)  seg_loss_3d: 0.4389 (0.3762)  time: 1.5454 (1.5705)  data: 0.0283 (0.0335)  max mem: 4473
2022-11-07 11:03:02,745 adals.validate INFO: iter: 220/1004  seg_loss_2d_point: 0.7963 (0.6851)  seg_loss_2d_pixel: 0.8017 (0.7549)  seg_loss_3d: 0.3611 (0.3748)  time: 1.7166 (1.5838)  data: 0.0283 (0.0331)  max mem: 4473
2022-11-07 11:03:40,222 adals.validate INFO: iter: 240/1004  seg_loss_2d_point: 0.7731 (0.6924)  seg_loss_2d_pixel: 0.7723 (0.7563)  seg_loss_3d: 0.4208 (0.3787)  time: 1.8739 (1.6080)  data: 0.0293 (0.0328)  max mem: 4473
2022-11-07 11:04:04,852 adals.validate INFO: iter: 260/1004  seg_loss_2d_point: 0.7862 (0.6996)  seg_loss_2d_pixel: 0.8602 (0.7643)  seg_loss_3d: 0.5041 (0.3883)  time: 1.2315 (1.5790)  data: 0.0278 (0.0324)  max mem: 4473
2022-11-07 11:04:40,228 adals.validate INFO: iter: 280/1004  seg_loss_2d_point: 0.7476 (0.7030)  seg_loss_2d_pixel: 0.7670 (0.7645)  seg_loss_3d: 0.5409 (0.3992)  time: 1.7688 (1.5926)  data: 0.0276 (0.0320)  max mem: 4473
2022-11-07 11:05:15,828 adals.validate INFO: iter: 300/1004  seg_loss_2d_point: 0.6958 (0.7026)  seg_loss_2d_pixel: 0.7604 (0.7642)  seg_loss_3d: 0.4090 (0.3999)  time: 1.7800 (1.6051)  data: 0.0283 (0.0318)  max mem: 4473
2022-11-07 11:06:03,159 adals.validate INFO: iter: 320/1004  seg_loss_2d_point: 0.8821 (0.7138)  seg_loss_2d_pixel: 0.7753 (0.7649)  seg_loss_3d: 0.3542 (0.3970)  time: 2.3665 (1.6526)  data: 0.0279 (0.0315)  max mem: 4473
2022-11-07 11:06:37,337 adals.validate INFO: iter: 340/1004  seg_loss_2d_point: 0.6273 (0.7087)  seg_loss_2d_pixel: 0.7640 (0.7649)  seg_loss_3d: 0.3601 (0.3948)  time: 1.7089 (1.6560)  data: 0.0287 (0.0314)  max mem: 4473
2022-11-07 11:07:00,925 adals.validate INFO: iter: 360/1004  seg_loss_2d_point: 0.5014 (0.6972)  seg_loss_2d_pixel: 0.6537 (0.7587)  seg_loss_3d: 0.2354 (0.3860)  time: 1.1794 (1.6295)  data: 0.0278 (0.0312)  max mem: 4473
2022-11-07 11:07:39,086 adals.validate INFO: iter: 380/1004  seg_loss_2d_point: 0.6679 (0.6956)  seg_loss_2d_pixel: 0.7672 (0.7591)  seg_loss_3d: 0.3530 (0.3842)  time: 1.9080 (1.6441)  data: 0.0269 (0.0310)  max mem: 4473
2022-11-07 11:08:31,766 adals.validate INFO: iter: 400/1004  seg_loss_2d_point: 0.7471 (0.6982)  seg_loss_2d_pixel: 0.6894 (0.7557)  seg_loss_3d: 0.2633 (0.3782)  time: 2.6340 (1.6936)  data: 0.0284 (0.0308)  max mem: 4473
2022-11-07 11:09:08,071 adals.validate INFO: iter: 420/1004  seg_loss_2d_point: 0.5897 (0.6930)  seg_loss_2d_pixel: 0.5768 (0.7471)  seg_loss_3d: 0.1450 (0.3671)  time: 1.8152 (1.6994)  data: 0.0285 (0.0307)  max mem: 4473
2022-11-07 11:09:48,038 adals.validate INFO: iter: 440/1004  seg_loss_2d_point: 0.6616 (0.6916)  seg_loss_2d_pixel: 0.7175 (0.7458)  seg_loss_3d: 0.2978 (0.3639)  time: 1.9984 (1.7130)  data: 0.0275 (0.0306)  max mem: 4473
2022-11-07 11:10:29,135 adals.validate INFO: iter: 460/1004  seg_loss_2d_point: 0.7460 (0.6940)  seg_loss_2d_pixel: 0.6982 (0.7437)  seg_loss_3d: 0.4209 (0.3664)  time: 2.0548 (1.7279)  data: 0.0270 (0.0304)  max mem: 4473
2022-11-07 11:11:01,888 adals.validate INFO: iter: 480/1004  seg_loss_2d_point: 0.7571 (0.6966)  seg_loss_2d_pixel: 0.8388 (0.7477)  seg_loss_3d: 0.4178 (0.3686)  time: 1.6376 (1.7241)  data: 0.0275 (0.0303)  max mem: 4473
2022-11-07 11:11:36,686 adals.validate INFO: iter: 500/1004  seg_loss_2d_point: 0.9916 (0.7084)  seg_loss_2d_pixel: 1.0147 (0.7584)  seg_loss_3d: 0.4790 (0.3730)  time: 1.7399 (1.7247)  data: 0.0295 (0.0303)  max mem: 4473
2022-11-07 11:12:15,843 adals.validate INFO: iter: 520/1004  seg_loss_2d_point: 1.1429 (0.7251)  seg_loss_2d_pixel: 1.0673 (0.7702)  seg_loss_3d: 0.6888 (0.3851)  time: 1.9578 (1.7337)  data: 0.0279 (0.0302)  max mem: 4687
2022-11-07 11:13:04,205 adals.validate INFO: iter: 540/1004  seg_loss_2d_point: 0.9266 (0.7326)  seg_loss_2d_pixel: 0.9892 (0.7784)  seg_loss_3d: 0.5329 (0.3906)  time: 2.4181 (1.7591)  data: 0.0277 (0.0301)  max mem: 4687
2022-11-07 11:13:56,668 adals.validate INFO: iter: 560/1004  seg_loss_2d_point: 1.0788 (0.7449)  seg_loss_2d_pixel: 0.9024 (0.7828)  seg_loss_3d: 0.2886 (0.3870)  time: 2.6231 (1.7899)  data: 0.0273 (0.0300)  max mem: 4687
2022-11-07 11:14:48,433 adals.validate INFO: iter: 580/1004  seg_loss_2d_point: 1.0876 (0.7568)  seg_loss_2d_pixel: 0.8265 (0.7843)  seg_loss_3d: 0.1894 (0.3801)  time: 2.5882 (1.8174)  data: 0.0286 (0.0299)  max mem: 4687
2022-11-07 11:15:29,814 adals.validate INFO: iter: 600/1004  seg_loss_2d_point: 0.6691 (0.7538)  seg_loss_2d_pixel: 0.6218 (0.7789)  seg_loss_3d: 0.2185 (0.3748)  time: 2.0691 (1.8258)  data: 0.0269 (0.0298)  max mem: 4687
2022-11-07 11:16:14,842 adals.validate INFO: iter: 620/1004  seg_loss_2d_point: 0.7111 (0.7525)  seg_loss_2d_pixel: 0.7271 (0.7772)  seg_loss_3d: 0.3351 (0.3735)  time: 2.2514 (1.8396)  data: 0.0266 (0.0297)  max mem: 4687
2022-11-07 11:16:44,185 adals.validate INFO: iter: 640/1004  seg_loss_2d_point: 0.7468 (0.7523)  seg_loss_2d_pixel: 0.7396 (0.7760)  seg_loss_3d: 0.3934 (0.3741)  time: 1.4671 (1.8279)  data: 0.0273 (0.0296)  max mem: 4687
2022-11-07 11:17:07,518 adals.validate INFO: iter: 660/1004  seg_loss_2d_point: 0.7644 (0.7526)  seg_loss_2d_pixel: 0.8216 (0.7774)  seg_loss_3d: 0.4589 (0.3767)  time: 1.1666 (1.8079)  data: 0.0271 (0.0296)  max mem: 4687
2022-11-07 11:17:35,156 adals.validate INFO: iter: 680/1004  seg_loss_2d_point: 0.7425 (0.7523)  seg_loss_2d_pixel: 0.8242 (0.7788)  seg_loss_3d: 0.3443 (0.3757)  time: 1.3819 (1.7954)  data: 0.0280 (0.0295)  max mem: 4687
2022-11-07 11:18:09,538 adals.validate INFO: iter: 700/1004  seg_loss_2d_point: 0.8228 (0.7544)  seg_loss_2d_pixel: 0.8234 (0.7801)  seg_loss_3d: 0.3370 (0.3746)  time: 1.7191 (1.7932)  data: 0.0283 (0.0295)  max mem: 4687
2022-11-07 11:18:33,241 adals.validate INFO: iter: 720/1004  seg_loss_2d_point: 0.7389 (0.7539)  seg_loss_2d_pixel: 0.8241 (0.7813)  seg_loss_3d: 0.3385 (0.3736)  time: 1.1852 (1.7763)  data: 0.0267 (0.0294)  max mem: 4687
2022-11-07 11:18:58,704 adals.validate INFO: iter: 740/1004  seg_loss_2d_point: 0.9433 (0.7590)  seg_loss_2d_pixel: 1.0189 (0.7877)  seg_loss_3d: 0.8116 (0.3854)  time: 1.2731 (1.7627)  data: 0.0273 (0.0294)  max mem: 4687
2022-11-07 11:19:29,146 adals.validate INFO: iter: 760/1004  seg_loss_2d_point: 0.7399 (0.7585)  seg_loss_2d_pixel: 0.7689 (0.7872)  seg_loss_3d: 0.4946 (0.3883)  time: 1.5221 (1.7564)  data: 0.0274 (0.0293)  max mem: 4687
2022-11-07 11:19:57,682 adals.validate INFO: iter: 780/1004  seg_loss_2d_point: 0.7586 (0.7585)  seg_loss_2d_pixel: 0.8351 (0.7884)  seg_loss_3d: 0.5129 (0.3915)  time: 1.4268 (1.7479)  data: 0.0284 (0.0293)  max mem: 4687
2022-11-07 11:20:19,090 adals.validate INFO: iter: 800/1004  seg_loss_2d_point: 0.7032 (0.7572)  seg_loss_2d_pixel: 0.7950 (0.7886)  seg_loss_3d: 0.4458 (0.3929)  time: 1.0704 (1.7310)  data: 0.0278 (0.0292)  max mem: 4687
2022-11-07 11:20:51,763 adals.validate INFO: iter: 820/1004  seg_loss_2d_point: 0.8640 (0.7598)  seg_loss_2d_pixel: 0.9260 (0.7920)  seg_loss_3d: 0.5449 (0.3966)  time: 1.6337 (1.7286)  data: 0.0281 (0.0292)  max mem: 4687
2022-11-07 11:21:20,292 adals.validate INFO: iter: 840/1004  seg_loss_2d_point: 0.8554 (0.7620)  seg_loss_2d_pixel: 0.9529 (0.7958)  seg_loss_3d: 0.5468 (0.4002)  time: 1.4264 (1.7214)  data: 0.0260 (0.0291)  max mem: 4687
2022-11-07 11:21:51,705 adals.validate INFO: iter: 860/1004  seg_loss_2d_point: 0.7719 (0.7623)  seg_loss_2d_pixel: 0.8635 (0.7974)  seg_loss_3d: 0.4562 (0.4015)  time: 1.5706 (1.7179)  data: 0.0272 (0.0291)  max mem: 4687
2022-11-07 11:22:34,113 adals.validate INFO: iter: 880/1004  seg_loss_2d_point: 0.6643 (0.7600)  seg_loss_2d_pixel: 0.7663 (0.7967)  seg_loss_3d: 0.3577 (0.4005)  time: 2.1204 (1.7270)  data: 0.0278 (0.0291)  max mem: 4687
2022-11-07 11:23:07,819 adals.validate INFO: iter: 900/1004  seg_loss_2d_point: 0.6269 (0.7571)  seg_loss_2d_pixel: 0.7291 (0.7952)  seg_loss_3d: 0.4233 (0.4010)  time: 1.6853 (1.7261)  data: 0.0276 (0.0290)  max mem: 4687
2022-11-07 11:23:34,604 adals.validate INFO: iter: 920/1004  seg_loss_2d_point: 0.7714 (0.7574)  seg_loss_2d_pixel: 0.8773 (0.7969)  seg_loss_3d: 0.6413 (0.4062)  time: 1.3393 (1.7177)  data: 0.0279 (0.0290)  max mem: 4687
2022-11-07 11:24:04,195 adals.validate INFO: iter: 940/1004  seg_loss_2d_point: 0.7814 (0.7579)  seg_loss_2d_pixel: 0.8504 (0.7981)  seg_loss_3d: 0.5364 (0.4090)  time: 1.4795 (1.7126)  data: 0.0288 (0.0290)  max mem: 4687
2022-11-07 11:24:27,847 adals.validate INFO: iter: 960/1004  seg_loss_2d_point: 0.6647 (0.7560)  seg_loss_2d_pixel: 0.7574 (0.7972)  seg_loss_3d: 0.4380 (0.4096)  time: 1.1826 (1.7016)  data: 0.0280 (0.0290)  max mem: 4687
2022-11-07 11:24:59,260 adals.validate INFO: iter: 980/1004  seg_loss_2d_point: 0.7154 (0.7551)  seg_loss_2d_pixel: 0.7548 (0.7964)  seg_loss_3d: 0.4069 (0.4095)  time: 1.5707 (1.6989)  data: 0.0270 (0.0289)  max mem: 4687
2022-11-07 11:25:27,814 adals.validate INFO: iter: 1000/1004  seg_loss_2d_point: 0.7947 (0.7559)  seg_loss_2d_pixel: 0.8198 (0.7968)  seg_loss_3d: 0.4858 (0.4110)  time: 1.4277 (1.6935)  data: 0.0269 (0.0289)  max mem: 4687
2022-11-07 11:25:33,027 adals.validate INFO: 2D Point overall accuracy=74.29%
2022-11-07 11:25:33,027 adals.validate INFO: 2D Point overall IOU=51.61
2022-11-07 11:25:33,041 adals.validate INFO: 2D Point class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      75.59 | 47.98 | 10205497 |
| driveable_surface |      85.44 | 77.11 | 56047567 |
| sidewalk          |      31.64 | 24.07 | 12630603 |
| manmade           |      79.92 | 58.79 | 31666701 |
| terrain           |      63.96 | 47.14 | 13619746 |
| vegetation        |      68.07 | 54.59 | 21948012 |
+-------------------+------------+-------+----------+
2022-11-07 11:25:33,042 adals.validate INFO: 2D Pixel overall accuracy=71.97%
2022-11-07 11:25:33,042 adals.validate INFO: 2D Pixel overall IOU=49.61
2022-11-07 11:25:33,042 adals.validate INFO: 2D Pixel class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      75.17 | 37.22 | 10677430 |
| driveable_surface |      79.56 | 73.54 | 54844581 |
| sidewalk          |      40.39 | 28.10 | 12171662 |
| manmade           |      70.94 | 57.05 | 34481419 |
| terrain           |      60.56 | 43.85 | 13108653 |
| vegetation        |      76.37 | 57.92 | 27021702 |
+-------------------+------------+-------+----------+
2022-11-07 11:25:33,042 adals.validate INFO: 3D overall accuracy=86.11%
2022-11-07 11:25:33,042 adals.validate INFO: 3D overall IOU=70.38
2022-11-07 11:25:33,043 adals.validate INFO: 3D class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      80.82 | 79.08 | 10205497 |
| driveable_surface |      93.70 | 89.59 | 56047567 |
| sidewalk          |      76.01 | 53.25 | 12630603 |
| manmade           |      94.98 | 76.44 | 31666701 |
| terrain           |      64.32 | 53.43 | 13619746 |
| vegetation        |      75.75 | 70.47 | 21948012 |
+-------------------+------------+-------+----------+
2022-11-07 11:25:33,043 adals.validate INFO: 2D+3D overall accuracy=86.75%
2022-11-07 11:25:33,043 adals.validate INFO: 2D+3D overall IOU=71.02
2022-11-07 11:25:33,044 adals.validate INFO: 2D+3D class-wise segmentation accuracy and IoU.
+-------------------+------------+-------+----------+
| Class             |   Accuracy |   IOU |    Total |
|-------------------+------------+-------+----------|
| vehicle           |      82.60 | 76.25 | 10205497 |
| driveable_surface |      94.70 | 90.02 | 56047567 |
| sidewalk          |      68.86 | 53.03 | 12630603 |
| manmade           |      94.78 | 77.04 | 31666701 |
| terrain           |      69.96 | 57.96 | 13619746 |
| vegetation        |      77.49 | 71.85 | 21948012 |
+-------------------+------------+-------+----------+
