Add pretrained models

Pretrained_Models/PN++_CLA_fractal/PN++_CLA_fractal20251203-181926-TWsWjMM996MGy2bdWx6Awd.log

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+[12/03 18:19:26] ModelNet40Ply2048 INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 7271
+epoch: 0
+epochs: 250
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: SmoothCrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 1
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-ModelNet40Ply2048
+  tags: ['test']
+  name: PN++_CLA_fractal
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 10
+save_freq: -1
+root_dir: log/modelnet40ply2048
+pretrained_path: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/checkpoint/modelnet40_pointnet++_ckpt_best_9056.pth
+datatransforms:
+  train: ['PointsToTensor', 'PointCloudScaleAndTranslate']
+  val: ['PointsToTensor']
+  vote: ['PointCloudScaleAndTranslate']
+  kwargs:
+    shift: [0.2, 0.2, 0.2]
+feature_keys: pos
+num_points: 1024
+dataset:
+  common:
+    NAME: ModelNet40Ply2048
+    data_dir: /workspace/PointNeXt/data/ModelNet40Ply2048
+  train:
+    split: train
+    num_points: 1024
+  val:
+    split: test
+    num_points: 1024
+batch_size: 32
+dataloader:
+  num_workers: 8
+num_classes: 40
+sched: cosine
+warmup_epochs: 0
+min_lr: None
+lr: 0.001
+optimizer:
+  NAME: adamw
+  weight_decay: 0.05
+log_dir: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal
+val_batch_size: 64
+model:
+  NAME: BaseCls
+  encoder_args:
+    NAME: PointNet2Encoder
+    in_channels: 3
+    width: None
+    layers: 3
+    use_res: False
+    strides: [2, 4, 1]
+    stage: [1, 2]
+    mlps: [[[64, 64, 128]], [[128, 128, 256]], [[256, 512, 1024]]]
+    radius: [0.2, 0.4, None]
+    num_samples: [32, 64, None]
+    sampler: fps
+    aggr_args:
+      NAME: convpool
+      feature_type: dp_fj
+      anisotropic: False
+      reduction: max
+    group_args:
+      NAME: ballquery
+      use_xyz: True
+      normalize_dp: False
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  cls_args:
+    NAME: ClsHead
+    num_classes: 40
+    mlps: [512, 256]
+    norm_args:
+      norm: bn1d
+rank: 0
+distributed: False
+mp: False
+task_name: modelnet40ply2048
+exp_name: pointnet++
+opts: mode=test
+run_dir: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal
+run_name: PN++_CLA_fractal
+ckpt_dir: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/code
+log_path: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/PN++_CLA_fractal20251203-181926-TWsWjMM996MGy2bdWx6Awd.log
+cfg_path: /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/cfg.yaml
+[12/03 18:19:26] ModelNet40Ply2048 WARNING: kwargs: {'stage': [1, 2]} are not used in PointNet2Encoder
+[12/03 18:19:26] ModelNet40Ply2048 INFO: radius is modified to [[0.2], [0.4], [None]]
+[12/03 18:19:26] ModelNet40Ply2048 INFO: num_samples is modified to [[32], [64], [None]]
+[12/03 18:19:26] ModelNet40Ply2048 INFO: NAME: ballquery
+use_xyz: True
+normalize_dp: False
+radius: 0.2
+nsample: 32
+[12/03 18:19:26] ModelNet40Ply2048 INFO: NAME: ballquery
+use_xyz: True
+normalize_dp: False
+radius: 0.4
+nsample: 64
+[12/03 18:19:26] ModelNet40Ply2048 INFO: NAME: ballquery
+use_xyz: True
+normalize_dp: False
+radius: None
+nsample: None
+[12/03 18:19:30] ModelNet40Ply2048 INFO: BaseCls(
+  (encoder): PointNet2Encoder(
+    (SA_modules): ModuleList(
+      (0): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(6, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (1): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (2): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): GroupAll()
+            )
+          )
+        )
+      )
+    )
+  )
+  (prediction): ClsHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Linear(in_features=1024, out_features=512, bias=False)
+        (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Linear(in_features=512, out_features=256, bias=False)
+        (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (3): Dropout(p=0.5, inplace=False)
+      (4): Sequential(
+        (0): Linear(in_features=256, out_features=40, bias=True)
+      )
+    )
+  )
+  (criterion): SmoothCrossEntropy()
+)
+[12/03 18:19:30] ModelNet40Ply2048 INFO: Number of params: 1.4726 M
+[12/03 18:19:30] ModelNet40Ply2048 INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.05,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "prediction.head.0.0.weight",
+      "prediction.head.2.0.weight",
+      "prediction.head.4.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "prediction.head.0.1.weight",
+      "prediction.head.0.1.bias",
+      "prediction.head.2.1.weight",
+      "prediction.head.2.1.bias",
+      "prediction.head.4.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/03 18:19:30] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/03 18:19:30] ModelNet40Ply2048 INFO: length of validation dataset: 2468
+[12/03 18:19:31] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/03 18:19:31] ModelNet40Ply2048 INFO: number of classes of the dataset: 40, number of points sampled from dataset: 1024, number of points as model input: 1024
+[12/03 18:19:31] ModelNet40Ply2048 INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PN++_CLA_fractal/checkpoint/modelnet40_pointnet++_ckpt_best_9056.pth
+[12/03 18:19:31] ModelNet40Ply2048 INFO: ckpts @ 15 epoch( {'best_val': 90.55915832519531} )
+[12/03 18:24:33] ModelNet40Ply2048 INFO: 
+Classes	Acc
+airplane  : 100.00%
+bathtub   : 90.00%
+bed       : 100.00%
+bench     : 75.00%
+bookshelf : 95.00%
+bottle    : 99.00%
+bowl      : 95.00%
+car       : 99.00%
+chair     : 100.00%
+cone      : 90.00%
+cup       : 75.00%
+curtain   : 80.00%
+desk      : 84.88%
+door      : 80.00%
+dresser   : 89.53%
+flower_pot: 10.00%
+glass_box : 96.00%
+guitar    : 100.00%
+keyboard  : 95.00%
+lamp      : 80.00%
+laptop    : 100.00%
+mantel    : 96.00%
+monitor   : 100.00%
+night_stand: 73.26%
+person    : 80.00%
+piano     : 91.00%
+plant     : 90.00%
+radio     : 70.00%
+range_hood: 94.00%
+sink      : 75.00%
+sofa      : 100.00%
+stairs    : 80.00%
+stool     : 75.00%
+table     : 75.00%
+tent      : 95.00%
+toilet    : 99.00%
+tv_stand  : 88.00%
+vase      : 82.00%
+wardrobe  : 50.00%
+xbox      : 60.00%
+E@15	OA: 90.56	mAcc: 85.17
+

Pretrained_Models/PN++_CLA_fractal/checkpoint/modelnet40_pointnet++_ckpt_best_9056.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c24eccd2f1f0fba55983561a698a57fe394b0824e2fc020eb6ffcb2a4e873252
+size 17748141

Pretrained_Models/PN++_SEG_fractal/PN++_SEG_fractal20251203-092212-fGQFtQWEMHgdndwERcQSVa.log

@@ -0,0 +1,709 @@
+[12/03 09:22:12] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 2279
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PN++_SEG_fractal
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/checkpoint/s3dis-pointnet++_ckpt_best_618.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 32
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointNet2Encoder
+    in_channels: 4
+    width: None
+    strides: [4, 4, 4, 4]
+    layers: 3
+    use_res: False
+    mlps: [[[32, 32, 64]], [[64, 64, 128]], [[128, 128, 256]], [[256, 256, 512]]]
+    radius: 0.1
+    num_samples: 32
+    sampler: fps
+    aggr_args:
+      NAME: convpool
+      feature_type: dp_fj
+      anisotropic: False
+      reduction: max
+    group_args:
+      NAME: ballquery
+      use_xyz: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNet2Decoder
+    fp_mlps: [[128, 128, 128], [256, 128], [256, 256], [256, 256]]
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointnet++
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal
+run_name: PN++_SEG_fractal
+ckpt_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/code
+log_path: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/PN++_SEG_fractal20251203-092212-fGQFtQWEMHgdndwERcQSVa.log
+cfg_path: /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/cfg.yaml
+[12/03 09:22:12] S3DIS INFO: radius is modified to [[0.1], [0.2], [0.4], [0.8]]
+[12/03 09:22:12] S3DIS INFO: num_samples is modified to [[32], [32], [32], [32]]
+[12/03 09:22:12] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.1
+nsample: 32
+[12/03 09:22:12] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.2
+nsample: 32
+[12/03 09:22:12] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.4
+nsample: 32
+[12/03 09:22:12] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.8
+nsample: 32
+[12/03 09:22:19] S3DIS INFO: BaseSeg(
+  (encoder): PointNet2Encoder(
+    (SA_modules): ModuleList(
+      (0): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(7, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (1): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (2): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (3): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+    )
+  )
+  (decoder): PointNet2Decoder(
+    (FP_modules): ModuleList(
+      (0): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(132, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (2): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (1): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(320, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (2): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(384, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (3): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(128, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/03 09:22:19] S3DIS INFO: Number of params: 0.9648 M
+[12/03 09:22:19] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "decoder.FP_modules.0.convs.0.0.weight",
+      "decoder.FP_modules.0.convs.1.0.weight",
+      "decoder.FP_modules.0.convs.2.0.weight",
+      "decoder.FP_modules.1.convs.0.0.weight",
+      "decoder.FP_modules.1.convs.1.0.weight",
+      "decoder.FP_modules.2.convs.0.0.weight",
+      "decoder.FP_modules.2.convs.1.0.weight",
+      "decoder.FP_modules.3.convs.0.0.weight",
+      "decoder.FP_modules.3.convs.1.0.weight",
+      "head.head.0.0.weight",
+      "head.head.2.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "decoder.FP_modules.0.convs.0.1.weight",
+      "decoder.FP_modules.0.convs.0.1.bias",
+      "decoder.FP_modules.0.convs.1.1.weight",
+      "decoder.FP_modules.0.convs.1.1.bias",
+      "decoder.FP_modules.0.convs.2.1.weight",
+      "decoder.FP_modules.0.convs.2.1.bias",
+      "decoder.FP_modules.1.convs.0.1.weight",
+      "decoder.FP_modules.1.convs.0.1.bias",
+      "decoder.FP_modules.1.convs.1.1.weight",
+      "decoder.FP_modules.1.convs.1.1.bias",
+      "decoder.FP_modules.2.convs.0.1.weight",
+      "decoder.FP_modules.2.convs.0.1.bias",
+      "decoder.FP_modules.2.convs.1.1.weight",
+      "decoder.FP_modules.2.convs.1.1.bias",
+      "decoder.FP_modules.3.convs.0.1.weight",
+      "decoder.FP_modules.3.convs.0.1.bias",
+      "decoder.FP_modules.3.convs.1.1.weight",
+      "decoder.FP_modules.3.convs.1.1.bias",
+      "head.head.0.1.weight",
+      "head.head.0.1.bias",
+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/03 09:22:19] S3DIS INFO: 
+Totally 68 samples in val set
+[12/03 09:22:19] S3DIS INFO: length of validation dataset: 68
+[12/03 09:22:19] S3DIS INFO: number of classes of the dataset: 13
+[12/03 09:22:20] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PN++_SEG_fractal/checkpoint/s3dis-pointnet++_ckpt_best_618.pth
+[12/03 09:22:20] S3DIS INFO: ckpts @ 20 epoch( {'best_val': 60.01229476928711} )
+[12/03 09:22:20] S3DIS INFO: length of test dataset: 68
+[12/03 09:22:20] S3DIS INFO: Test [0]/[68] cloud
+[12/03 09:28:42] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 91.90 96.86 72.18, 
+iou per cls is: [ 96.75  99.35  80.02   0.     0.   100.    96.13   0.   100.   100.
+ 100.   100.    66.14]
+[12/03 09:28:42] S3DIS INFO: Test [1]/[68] cloud
+[12/03 09:33:29] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 89.28 96.23 55.62, 
+iou per cls is: [ 95.82  99.37  74.74   0.     0.     0.    96.96   0.   100.   100.
+   0.   100.    56.2 ]
+[12/03 09:33:29] S3DIS INFO: Test [2]/[68] cloud
+[12/03 09:42:01] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 84.45 84.67 63.77, 
+iou per cls is: [ 96.05  99.57  71.46   0.    31.31  44.66  70.17  93.78  92.73 100.
+   0.    84.51  44.81]
+[12/03 09:42:01] S3DIS INFO: Test [3]/[68] cloud
+[12/03 10:24:36] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 88.49 85.20 71.29, 
+iou per cls is: [ 94.84  97.03  78.99   0.    47.39 100.    76.67  92.7   91.3   97.89
+  73.88  15.12  60.97]
+[12/03 10:24:36] S3DIS INFO: Test [4]/[68] cloud
+[12/03 10:43:03] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 89.34 84.63 57.62, 
+iou per cls is: [93.62 99.28 76.99  0.   51.26 75.17 84.37 67.34 91.2   0.    0.   60.02
+ 49.86]
+[12/03 10:43:03] S3DIS INFO: Test [5]/[68] cloud
+[12/03 13:33:09] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 74.62 68.51 27.84, 
+iou per cls is: [81.59 96.96 53.72  0.    1.51  0.08 17.81  0.    0.   54.03 52.81  0.
+  3.45]
+[12/03 13:33:09] S3DIS INFO: Test [6]/[68] cloud
+[12/03 13:42:09] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 97.34 96.85 80.73, 
+iou per cls is: [ 98.03  99.6   95.34 100.     0.   100.    59.67 100.   100.   100.
+ 100.     0.    96.9 ]
+[12/03 13:42:09] S3DIS INFO: Test [7]/[68] cloud
+[12/03 13:47:04] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 96.83 96.51 80.70, 
+iou per cls is: [ 96.55  99.41  95.01 100.     0.   100.    58.14 100.   100.   100.
+ 100.   100.     0.  ]
+[12/03 13:47:04] S3DIS INFO: Test [8]/[68] cloud
+[12/03 13:52:08] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 97.90 97.14 88.16, 
+iou per cls is: [ 97.14  99.62  96.39 100.     0.   100.    74.48 100.   100.   100.
+ 100.   100.    78.47]
+[12/03 13:52:08] S3DIS INFO: Test [9]/[68] cloud
+[12/03 14:03:10] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 87.87 88.28 43.20, 
+iou per cls is: [ 97.03  99.55  90.68 100.     0.     2.2   16.3    0.     0.   100.
+   0.     0.    55.85]
+[12/03 14:03:10] S3DIS INFO: Test [10]/[68] cloud
+[12/03 14:06:18] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 91.96 94.10 54.42, 
+iou per cls is: [ 96.2   99.36  88.61 100.     0.   100.    43.46   0.   100.     0.
+   0.     0.    79.85]
+[12/03 14:06:18] S3DIS INFO: Test [11]/[68] cloud
+[12/03 14:18:26] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 84.46 79.46 34.40, 
+iou per cls is: [ 96.42  98.9   81.25   0.     0.     0.    16.75   0.     0.   100.
+   0.     0.    53.93]
+[12/03 14:18:26] S3DIS INFO: Test [12]/[68] cloud
+[12/03 16:07:25] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 90.14 93.96 38.61, 
+iou per cls is: [ 94.1   98.8   83.31   0.     0.     0.    41.84   0.     0.   100.
+   0.     0.    83.85]
+[12/03 16:07:25] S3DIS INFO: Test [13]/[68] cloud
+[12/03 16:14:38] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 95.68 95.58 56.23, 
+iou per cls is: [ 95.08  97.49  94.53   0.     0.   100.    60.98   0.   100.   100.
+   0.     0.    82.9 ]
+[12/03 16:14:38] S3DIS INFO: Test [14]/[68] cloud
+[12/03 16:19:47] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 91.20 76.59 37.43, 
+iou per cls is: [ 96.93  99.58  94.29 100.     0.     0.    67.07   0.     0.     5.2
+  23.57   0.     0.  ]
+[12/03 16:19:47] S3DIS INFO: Test [15]/[68] cloud
+[12/03 16:56:58] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 94.75 88.74 38.31, 
+iou per cls is: [98.57 99.28 90.57  0.    0.    0.   55.61  0.    0.   18.67 85.97  0.
+ 49.37]
+[12/03 16:56:58] S3DIS INFO: Test [16]/[68] cloud
+[12/03 17:01:22] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 92.70 94.00 76.80, 
+iou per cls is: [ 97.24  99.55  88.63 100.   100.     0.    55.14 100.   100.   100.
+ 100.     0.    57.89]
+[12/03 17:01:22] S3DIS INFO: Test [17]/[68] cloud
+[12/03 17:09:13] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 92.18 94.75 55.39, 
+iou per cls is: [ 98.59  99.46  86.55 100.     0.   100.    58.79   0.   100.     0.
+   0.     0.    76.69]
+[12/03 17:09:13] S3DIS INFO: Test [18]/[68] cloud
+[12/03 17:11:07] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 92.57 88.25 63.33, 
+iou per cls is: [ 96.6   99.44  87.95 100.   100.     0.    21.06 100.   100.   100.
+   0.     0.    18.28]
+[12/03 17:11:07] S3DIS INFO: Test [19]/[68] cloud
+[12/03 17:20:13] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 95.85 81.57 63.69, 
+iou per cls is: [ 96.08  98.45  94.48 100.     0.01   0.54  53.41   0.   100.   100.
+   0.   100.    85.03]
+[12/03 17:20:13] S3DIS INFO: Test [20]/[68] cloud
+[12/03 17:27:49] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 94.90 94.03 54.57, 
+iou per cls is: [ 99.68  98.47  85.86 100.     0.     0.     0.    90.6   94.79 100.
+   0.     0.    39.96]
+[12/03 17:27:49] S3DIS INFO: Test [21]/[68] cloud
+[12/03 17:31:36] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 82.73 79.94 64.54, 
+iou per cls is: [ 97.21  98.51  49.01   0.    25.66  53.1   95.74  87.01  93.31 100.
+  89.05   3.57  46.84]
+[12/03 17:31:36] S3DIS INFO: Test [22]/[68] cloud
+[12/03 17:35:17] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 92.76 90.04 77.62, 
+iou per cls is: [ 98.47  99.4   80.59   0.    54.31  82.99  75.54  79.86  97.48 100.
+  91.03  93.27  56.07]
+[12/03 17:35:17] S3DIS INFO: Test [23]/[68] cloud
+[12/03 17:39:19] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 94.40 89.57 76.30, 
+iou per cls is: [ 96.78  98.8   77.58   0.    23.78  70.77  94.57  79.29  94.56 100.
+  95.62  86.24  73.93]
+[12/03 17:39:19] S3DIS INFO: Test [24]/[68] cloud
+[12/03 17:43:24] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 90.01 90.15 68.81, 
+iou per cls is: [ 97.7   97.68  77.85   0.    57.7   80.89  81.53  75.99  82.18 100.
+  82.32   0.    60.71]
+[12/03 17:43:24] S3DIS INFO: Test [25]/[68] cloud
+[12/03 17:49:03] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 87.02 85.13 70.43, 
+iou per cls is: [ 98.17  98.6   62.23   0.    32.14  63.73  61.02  84.26  93.21 100.
+  94.32  76.83  51.03]
+[12/03 17:49:03] S3DIS INFO: Test [26]/[68] cloud
+[12/03 17:58:10] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 84.50 83.54 68.52, 
+iou per cls is: [ 96.3   98.57  72.66   0.    10.37  52.55  91.88  60.81  86.87 100.
+  72.41  90.37  58.01]
+[12/03 17:58:10] S3DIS INFO: Test [27]/[68] cloud
+[12/03 18:08:01] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 83.94 80.21 56.58, 
+iou per cls is: [96.09 98.1  64.84  0.   29.77 51.08 83.68 82.2  69.49  0.   75.19 33.48
+ 51.67]
+[12/03 18:08:01] S3DIS INFO: Test [28]/[68] cloud
+[12/03 18:11:58] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 89.75 78.03 65.43, 
+iou per cls is: [ 98.    98.39  86.47   0.    35.33 100.    95.71  86.97  89.79 100.
+   8.57   2.26  49.14]
+[12/03 18:11:58] S3DIS INFO: Test [29]/[68] cloud
+[12/03 18:16:52] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 83.83 87.85 52.79, 
+iou per cls is: [ 97.05  97.66  88.61   0.     0.     0.    73.91  35.9    0.   100.
+  49.99 100.    43.19]
+[12/03 18:16:52] S3DIS INFO: Test [30]/[68] cloud
+[12/03 18:25:29] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 92.72 83.64 56.85, 
+iou per cls is: [98.8  98.69 87.42  0.    0.63  0.   87.16 91.07 91.21  0.   92.89 29.84
+ 61.3 ]
+[12/03 18:25:29] S3DIS INFO: Test [31]/[68] cloud
+[12/03 18:40:17] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 87.22 86.71 66.13, 
+iou per cls is: [ 93.65  98.78  76.46   0.     0.   100.    76.08  84.05  89.01 100.
+  59.13  35.04  47.44]
+[12/03 18:40:17] S3DIS INFO: Test [32]/[68] cloud
+[12/03 18:44:29] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 92.93 87.72 75.23, 
+iou per cls is: [ 96.99  97.88  77.36   0.    53.38  86.41  95.45  75.21  91.1  100.
+  94.42  36.51  73.22]
+[12/03 18:44:29] S3DIS INFO: Test [33]/[68] cloud
+[12/03 18:46:29] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 84.87 83.35 62.17, 
+iou per cls is: [ 96.89  98.22  73.32   0.    26.62 100.    31.23  91.73  89.57 100.
+  52.6    0.    48.  ]
+[12/03 18:46:29] S3DIS INFO: Test [34]/[68] cloud
+[12/03 19:05:42] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 89.17 87.64 65.57, 
+iou per cls is: [ 98.25  99.12  80.02   0.    37.26 100.    94.85  88.61  89.09   0.
+  28.3   95.79  41.08]
+[12/03 19:05:42] S3DIS INFO: Test [35]/[68] cloud
+[12/03 19:09:22] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 91.03 87.40 74.32, 
+iou per cls is: [ 96.65  98.6   81.85   0.    28.93  62.45  88.03  84.36  92.43 100.
+  87.24  91.98  53.66]
+[12/03 19:09:22] S3DIS INFO: Test [36]/[68] cloud
+[12/03 19:13:56] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 90.85 90.11 74.89, 
+iou per cls is: [ 96.94  98.88  79.03   0.    41.41  63.04  85.63  85.93  82.89 100.
+  88.98  84.15  66.72]
+[12/03 19:13:56] S3DIS INFO: Test [37]/[68] cloud
+[12/03 19:27:09] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 81.26 79.59 63.66, 
+iou per cls is: [93.71 95.23 54.08  0.   51.06 74.27 72.38 73.62 81.06 74.07 60.33 51.79
+ 46.  ]
+[12/03 19:27:09] S3DIS INFO: Test [38]/[68] cloud
+[12/03 19:29:36] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 88.66 88.33 67.59, 
+iou per cls is: [ 95.7   96.38  78.2    0.     0.    84.84  64.13  68.88  98.28 100.
+  86.02  47.82  58.46]
+[12/03 19:29:36] S3DIS INFO: Test [39]/[68] cloud
+[12/03 19:33:02] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 81.41 76.33 61.76, 
+iou per cls is: [ 91.27  97.81  75.4    0.    56.02  70.75  47.08  71.86  84.36 100.
+  58.04  10.98  39.26]
+[12/03 19:33:02] S3DIS INFO: Test [40]/[68] cloud
+[12/03 19:36:36] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 92.18 90.47 78.84, 
+iou per cls is: [ 94.98  99.63  85.04   0.    52.34  87.67  94.58  88.22  91.28 100.
+  85.49  90.4   55.31]
+[12/03 19:36:36] S3DIS INFO: Test [41]/[68] cloud
+[12/03 19:40:11] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 92.76 91.91 79.97, 
+iou per cls is: [ 94.58  99.55  86.53   0.    89.48  90.56  84.01  75.89  91.69 100.
+  88.82  86.93  51.57]
+[12/03 19:40:11] S3DIS INFO: Test [42]/[68] cloud
+[12/03 19:54:40] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 77.03 80.26 62.93, 
+iou per cls is: [ 95.45  98.21  56.49   0.    48.03  63.1   72.54  82.73  67.04 100.
+  23.67  76.52  34.32]
+[12/03 19:54:40] S3DIS INFO: Test [43]/[68] cloud
+[12/03 19:57:42] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 92.63 93.66 74.48, 
+iou per cls is: [ 96.42  99.05  75.35   0.     0.    84.79  95.28  86.35  98.07 100.
+  91.64  82.84  58.46]
+[12/03 19:57:42] S3DIS INFO: Test [44]/[68] cloud
+[12/03 19:59:14] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.05 95.91 93.08, 
+iou per cls is: [ 94.96  98.22  93.4  100.   100.   100.    90.82  85.85  94.12 100.
+  93.86  86.64  72.25]
+[12/03 19:59:14] S3DIS INFO: Test [45]/[68] cloud
+[12/03 20:03:51] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 84.45 85.57 63.57, 
+iou per cls is: [ 94.79  99.1   54.84   0.    29.73  72.51  83.35  85.66  72.43 100.
+  82.59   0.    51.41]
+[12/03 20:03:51] S3DIS INFO: Test [46]/[68] cloud
+[12/03 20:07:18] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 88.58 86.62 65.39, 
+iou per cls is: [ 92.24  99.91  80.53   0.    29.57  92.6   84.87  75.11  61.82 100.
+  74.79   0.    58.67]
+[12/03 20:07:18] S3DIS INFO: Test [47]/[68] cloud
+[12/03 20:12:29] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 91.00 87.51 74.92, 
+iou per cls is: [ 93.41  99.57  81.85   0.    24.18  84.66  92.92  87.2   89.71 100.
+  83.56  90.48  46.44]
+[12/03 20:12:29] S3DIS INFO: Test [48]/[68] cloud
+[12/03 20:17:44] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 79.40 81.31 57.13, 
+iou per cls is: [93.3  95.75 58.75  0.   46.8  45.28 74.19 72.01 93.95  0.   65.81 58.
+ 38.91]
+[12/03 20:17:44] S3DIS INFO: Test [49]/[68] cloud
+[12/03 20:22:25] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 95.76 94.46 76.77, 
+iou per cls is: [ 98.01  96.76  89.31   0.     0.   100.    91.38  88.8   94.65 100.
+  91.89  59.23  88.  ]
+[12/03 20:22:25] S3DIS INFO: Test [50]/[68] cloud
+[12/03 20:30:35] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 91.46 91.41 69.90, 
+iou per cls is: [ 97.97  96.2   93.93   0.   100.   100.    90.28  74.83  91.26   0.
+  38.55  90.18  35.56]
+[12/03 20:30:35] S3DIS INFO: Test [51]/[68] cloud
+[12/03 21:06:07] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 80.25 76.35 52.95, 
+iou per cls is: [ 66.38  98.26  76.14   0.    11.25 100.    66.62  72.72  82.54   0.
+  65.43   2.81  46.18]
+[12/03 21:06:07] S3DIS INFO: Test [52]/[68] cloud
+[12/03 21:48:06] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 69.15 78.33 43.57, 
+iou per cls is: [61.43 97.2  57.87  0.   20.77  0.   72.48 50.25 65.06 53.75 53.06  0.
+ 34.5 ]
+[12/03 21:48:06] S3DIS INFO: Test [53]/[68] cloud
+[12/03 21:52:42] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 84.66 82.24 52.92, 
+iou per cls is: [92.74 99.08 74.52  0.11  0.    0.   80.45 81.01 86.92  0.   49.31 88.14
+ 35.65]
+[12/03 21:52:42] S3DIS INFO: Test [54]/[68] cloud
+[12/03 21:56:17] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 93.76 92.67 79.01, 
+iou per cls is: [ 97.02  98.13  78.92   0.    60.54  83.42  93.7   93.62  92.31 100.
+  94.2   75.63  59.68]
+[12/03 21:56:17] S3DIS INFO: Test [55]/[68] cloud
+[12/03 22:34:22] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 82.47 84.24 49.34, 
+iou per cls is: [93.56 97.83 76.78  0.   36.02  0.   33.5  61.05 63.45  0.   52.98 77.51
+ 48.74]
+[12/03 22:34:22] S3DIS INFO: Test [56]/[68] cloud
+[12/03 22:46:00] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 86.44 82.29 65.02, 
+iou per cls is: [ 94.82  97.99  75.52   0.    51.34  77.48  83.38  83.72  65.41 100.
+  59.31   4.54  51.7 ]
+[12/03 22:46:00] S3DIS INFO: Test [57]/[68] cloud
+[12/03 22:50:52] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 91.01 89.85 77.16, 
+iou per cls is: [ 97.3   98.3   77.9    0.    50.62  60.98  76.62  88.97  95.25 100.
+  87.15 100.    70.06]
+[12/03 22:50:52] S3DIS INFO: Test [58]/[68] cloud
+[12/03 22:53:43] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 95.17 96.34 69.75, 
+iou per cls is: [ 94.59  98.27  89.47   0.     0.    83.92  92.55  93.26  96.78 100.
+  91.85   0.    65.99]
+[12/03 22:53:43] S3DIS INFO: Test [59]/[68] cloud
+[12/03 22:56:53] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 92.39 92.36 73.09, 
+iou per cls is: [ 97.71  98.95  76.61   0.     0.    63.29  93.6   87.27  88.94 100.
+  89.96  91.09  62.7 ]
+[12/03 22:56:53] S3DIS INFO: Test [60]/[68] cloud
+[12/03 23:01:25] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 91.72 85.18 73.48, 
+iou per cls is: [ 98.56  98.71  70.67   0.     2.98  71.96  82.07  86.5   98.37 100.
+  91.82  86.97  66.57]
+[12/03 23:01:25] S3DIS INFO: Test [61]/[68] cloud
+[12/03 23:06:09] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 95.00 93.39 79.29, 
+iou per cls is: [ 97.09  97.74  86.48   0.    58.81  68.81  95.59  93.51  96.91 100.
+  96.53  86.8   52.49]
+[12/03 23:06:09] S3DIS INFO: Test [62]/[68] cloud
+[12/03 23:09:43] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 92.93 92.79 65.63, 
+iou per cls is: [96.07 97.67 86.51  0.    0.   77.32 77.87 76.52 97.73 81.79 92.12  0.
+ 69.53]
+[12/03 23:09:43] S3DIS INFO: Test [63]/[68] cloud
+[12/03 23:12:12] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 72.80 92.80 37.43, 
+iou per cls is: [ 93.83  98.86  74.02   0.     0.     0.     0.     0.     0.   100.
+   0.   100.    19.86]
+[12/03 23:12:12] S3DIS INFO: Test [64]/[68] cloud
+[12/03 23:14:33] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 68.96 70.03 33.34, 
+iou per cls is: [ 46.62  97.69  66.12   0.     4.6    0.    38.13   0.     0.   100.
+  65.07   0.    15.14]
+[12/03 23:14:33] S3DIS INFO: Test [65]/[68] cloud
+[12/03 23:18:37] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 64.46 83.61 39.43, 
+iou per cls is: [ 46.09  97.47  66.28 100.     0.     0.    39.1    0.     0.   100.
+  30.65   0.    33.06]
+[12/03 23:18:37] S3DIS INFO: Test [66]/[68] cloud
+[12/03 23:18:59] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 79.80 88.25 39.39, 
+iou per cls is: [  2.9   99.09  72.2  100.   100.     0.    84.52   0.     0.     0.
+   0.     0.    53.32]
+[12/03 23:18:59] S3DIS INFO: Test [67]/[68] cloud
+[12/03 23:21:48] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 82.01 84.97 50.80, 
+iou per cls is: [ 80.73  98.39  88.71 100.     0.     0.    32.7   48.37  75.22 100.
+   0.     0.    36.32]
+[12/03 23:21:48] S3DIS INFO: Best ckpt @E20,  test_oa , test_macc, test_miou: 87.23 69.38 61.78, 
+iou per cls is: [91.53 98.43 80.46  0.   27.33 53.27 62.91 78.65 83.81 57.19 69.27 51.75
+ 48.55]

Pretrained_Models/PN++_SEG_fractal/PN++_SEG_fractal_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointnet++,5,87.23,69.38,61.78,91.53,98.43,80.46,0.00,27.33,53.27,62.91,78.65,83.81,57.19,69.27,51.75,48.55,20,/workspace/FractalCloud/Model_logs/PN++_SEG_fractal,-

Pretrained_Models/PN++_SEG_fractal/checkpoint/s3dis-pointnet++_ckpt_best_618.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:38c35c343903782e9dcd493474194dd7f5e64489f2dd87ff174f690729f09c6d
+size 11704549

Pretrained_Models/PN++_SEG_original/PN++_SEG_original20251202-225336-cjYUX2cjCSXoiJ5N7iEyWe.log

@@ -0,0 +1,709 @@
+[12/02 22:53:36] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 5139
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PN++_SEG_original
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PN++_SEG_original/checkpoint/s3dis-pointnet++_ckpt_best_616.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 32
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_original
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointNet2Encoder
+    in_channels: 4
+    width: None
+    strides: [4, 4, 4, 4]
+    layers: 3
+    use_res: False
+    mlps: [[[32, 32, 64]], [[64, 64, 128]], [[128, 128, 256]], [[256, 256, 512]]]
+    radius: 0.1
+    num_samples: 32
+    sampler: fps
+    aggr_args:
+      NAME: convpool
+      feature_type: dp_fj
+      anisotropic: False
+      reduction: max
+    group_args:
+      NAME: ballquery
+      use_xyz: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNet2Decoder
+    fp_mlps: [[128, 128, 128], [256, 128], [256, 256], [256, 256]]
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointnet++
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_original
+run_name: PN++_SEG_original
+ckpt_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_original/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PN++_SEG_original/code
+log_path: /workspace/FractalCloud/Model_logs/PN++_SEG_original/PN++_SEG_original20251202-225336-cjYUX2cjCSXoiJ5N7iEyWe.log
+cfg_path: /workspace/FractalCloud/Model_logs/PN++_SEG_original/cfg.yaml
+[12/02 22:53:36] S3DIS INFO: radius is modified to [[0.1], [0.2], [0.4], [0.8]]
+[12/02 22:53:36] S3DIS INFO: num_samples is modified to [[32], [32], [32], [32]]
+[12/02 22:53:36] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.1
+nsample: 32
+[12/02 22:53:36] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.2
+nsample: 32
+[12/02 22:53:36] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.4
+nsample: 32
+[12/02 22:53:36] S3DIS INFO: NAME: ballquery
+use_xyz: True
+radius: 0.8
+nsample: 32
+[12/02 22:53:42] S3DIS INFO: BaseSeg(
+  (encoder): PointNet2Encoder(
+    (SA_modules): ModuleList(
+      (0): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(7, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (1): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (2): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+      (3): PointNetSAModuleMSG(
+        (local_aggregations): ModuleList(
+          (0): LocalAggregation(
+            (SA_CONFIG_operator): ConvPool(
+              (act): ReLU(inplace=True)
+              (convs): Sequential(
+                (0): Sequential(
+                  (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (1): Sequential(
+                  (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+                (2): Sequential(
+                  (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                  (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                  (2): ReLU(inplace=True)
+                )
+              )
+              (grouper): QueryAndGroup()
+            )
+          )
+        )
+      )
+    )
+  )
+  (decoder): PointNet2Decoder(
+    (FP_modules): ModuleList(
+      (0): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(132, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (2): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (1): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(320, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 128, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (2): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(384, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+      (3): PointNetFPModule(
+        (convs): Sequential(
+          (0): Sequential(
+            (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+          (1): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+            (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (2): ReLU(inplace=True)
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(128, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/02 22:53:42] S3DIS INFO: Number of params: 0.9648 M
+[12/02 22:53:42] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.0.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.0.weight",
+      "decoder.FP_modules.0.convs.0.0.weight",
+      "decoder.FP_modules.0.convs.1.0.weight",
+      "decoder.FP_modules.0.convs.2.0.weight",
+      "decoder.FP_modules.1.convs.0.0.weight",
+      "decoder.FP_modules.1.convs.1.0.weight",
+      "decoder.FP_modules.2.convs.0.0.weight",
+      "decoder.FP_modules.2.convs.1.0.weight",
+      "decoder.FP_modules.3.convs.0.0.weight",
+      "decoder.FP_modules.3.convs.1.0.weight",
+      "head.head.0.0.weight",
+      "head.head.2.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.0.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.1.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.2.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.0.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.1.1.bias",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.1.weight",
+      "encoder.SA_modules.3.local_aggregations.0.SA_CONFIG_operator.convs.2.1.bias",
+      "decoder.FP_modules.0.convs.0.1.weight",
+      "decoder.FP_modules.0.convs.0.1.bias",
+      "decoder.FP_modules.0.convs.1.1.weight",
+      "decoder.FP_modules.0.convs.1.1.bias",
+      "decoder.FP_modules.0.convs.2.1.weight",
+      "decoder.FP_modules.0.convs.2.1.bias",
+      "decoder.FP_modules.1.convs.0.1.weight",
+      "decoder.FP_modules.1.convs.0.1.bias",
+      "decoder.FP_modules.1.convs.1.1.weight",
+      "decoder.FP_modules.1.convs.1.1.bias",
+      "decoder.FP_modules.2.convs.0.1.weight",
+      "decoder.FP_modules.2.convs.0.1.bias",
+      "decoder.FP_modules.2.convs.1.1.weight",
+      "decoder.FP_modules.2.convs.1.1.bias",
+      "decoder.FP_modules.3.convs.0.1.weight",
+      "decoder.FP_modules.3.convs.0.1.bias",
+      "decoder.FP_modules.3.convs.1.1.weight",
+      "decoder.FP_modules.3.convs.1.1.bias",
+      "head.head.0.1.weight",
+      "head.head.0.1.bias",
+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/02 22:53:42] S3DIS INFO: 
+Totally 68 samples in val set
+[12/02 22:53:42] S3DIS INFO: length of validation dataset: 68
+[12/02 22:53:42] S3DIS INFO: number of classes of the dataset: 13
+[12/02 22:53:42] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PN++_SEG_original/checkpoint/s3dis-pointnet++_ckpt_best_616.pth
+[12/02 22:53:42] S3DIS INFO: ckpts @ 83 epoch( {'best_val': 59.950157165527344} )
+[12/02 22:53:42] S3DIS INFO: length of test dataset: 68
+[12/02 22:53:42] S3DIS INFO: Test [0]/[68] cloud
+[12/02 22:54:08] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 90.72 95.16 55.02, 
+iou per cls is: [ 96.98  99.39  78.1    0.     0.     0.    76.46   0.   100.   100.
+   0.   100.    64.33]
+[12/02 22:54:08] S3DIS INFO: Test [1]/[68] cloud
+[12/02 22:54:25] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 89.91 96.00 55.34, 
+iou per cls is: [ 96.22  99.46  76.49 100.     0.     0.    87.8    0.   100.   100.
+   0.     0.    59.48]
+[12/02 22:54:25] S3DIS INFO: Test [2]/[68] cloud
+[12/02 22:55:04] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 82.93 81.55 61.28, 
+iou per cls is: [ 96.35  99.59  69.51   0.    19.5   37.39  45.17  94.31  93.57 100.
+   0.    93.91  47.42]
+[12/02 22:55:04] S3DIS INFO: Test [3]/[68] cloud
+[12/02 22:59:06] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 88.92 85.55 80.07, 
+iou per cls is: [ 90.88  97.    80.41 100.    47.46 100.    78.74  89.5   91.75  99.03
+  79.84  28.15  58.2 ]
+[12/02 22:59:06] S3DIS INFO: Test [4]/[68] cloud
+[12/02 23:00:38] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 88.40 80.43 53.11, 
+iou per cls is: [95.12 98.9  72.63  0.   52.05 64.25 87.84 69.14 93.1   0.    0.    3.2
+ 54.26]
+[12/02 23:00:38] S3DIS INFO: Test [5]/[68] cloud
+[12/02 23:09:18] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 76.41 65.24 26.47, 
+iou per cls is: [87.32 97.85 48.69  0.    6.83  0.   19.24  0.    0.   59.89 19.42  0.
+  4.88]
+[12/02 23:09:18] S3DIS INFO: Test [6]/[68] cloud
+[12/02 23:10:22] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 97.47 96.92 80.71, 
+iou per cls is: [ 97.99  99.51  95.88 100.     0.     0.    61.27 100.   100.   100.
+ 100.   100.    94.63]
+[12/02 23:10:22] S3DIS INFO: Test [7]/[68] cloud
+[12/02 23:10:52] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 96.66 95.21 87.07, 
+iou per cls is: [ 97.55  99.31  94.75 100.   100.   100.    40.29 100.   100.   100.
+ 100.   100.     0.  ]
+[12/02 23:10:52] S3DIS INFO: Test [8]/[68] cloud
+[12/02 23:11:25] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.40 97.63 96.67, 
+iou per cls is: [ 97.96  99.7   97.28 100.   100.   100.    79.19 100.   100.   100.
+ 100.   100.    82.56]
+[12/02 23:11:25] S3DIS INFO: Test [9]/[68] cloud
+[12/02 23:12:37] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 89.36 89.81 37.49, 
+iou per cls is: [ 98.03  99.46  90.35   0.     0.     3.45  16.59   0.     0.   100.
+   0.     0.    79.47]
+[12/02 23:12:37] S3DIS INFO: Test [10]/[68] cloud
+[12/02 23:12:57] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 93.93 95.17 55.24, 
+iou per cls is: [ 90.89  99.29  91.27   0.     0.   100.    52.62   0.   100.   100.
+   0.     0.    84.  ]
+[12/02 23:12:57] S3DIS INFO: Test [11]/[68] cloud
+[12/02 23:14:17] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 85.16 81.66 43.87, 
+iou per cls is: [ 97.46  99.42  75.78   0.     8.62   0.09  26.72   0.     0.   100.
+   0.   100.    62.27]
+[12/02 23:14:17] S3DIS INFO: Test [12]/[68] cloud
+[12/02 23:27:52] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 91.01 93.96 30.62, 
+iou per cls is: [97.53 96.06 84.99  0.    0.    0.   35.72  0.    0.    0.    0.    0.
+ 83.71]
+[12/02 23:27:52] S3DIS INFO: Test [13]/[68] cloud
+[12/02 23:28:46] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 95.96 92.91 46.10, 
+iou per cls is: [ 96.26  97.57  94.09   0.     0.   100.    23.63   0.   100.     0.
+   0.     0.    87.81]
+[12/02 23:28:46] S3DIS INFO: Test [14]/[68] cloud
+[12/02 23:29:21] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 93.42 81.82 42.43, 
+iou per cls is: [ 98.19  99.48  94.79   0.     0.   100.    74.1    0.     0.    35.08
+  49.93   0.     0.  ]
+[12/02 23:29:21] S3DIS INFO: Test [15]/[68] cloud
+[12/02 23:34:03] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 95.81 90.49 48.67, 
+iou per cls is: [ 97.99  99.19  93.97   0.     0.   100.    59.99   0.     0.    63.87
+  67.71   0.    50.  ]
+[12/02 23:34:03] S3DIS INFO: Test [16]/[68] cloud
+[12/02 23:34:36] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 95.37 96.59 79.32, 
+iou per cls is: [ 98.18  99.48  91.42 100.   100.     0.    70.88 100.   100.   100.
+ 100.     0.    71.13]
+[12/02 23:34:36] S3DIS INFO: Test [17]/[68] cloud
+[12/02 23:35:38] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 94.01 93.61 54.14, 
+iou per cls is: [ 98.38  99.47  88.63 100.     0.   100.    35.83   0.   100.     0.
+   0.     0.    81.56]
+[12/02 23:35:38] S3DIS INFO: Test [18]/[68] cloud
+[12/02 23:35:50] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 91.99 85.80 69.31, 
+iou per cls is: [ 97.14  99.41  87.03 100.   100.     0.    15.73 100.   100.   100.
+ 100.     0.     1.77]
+[12/02 23:35:50] S3DIS INFO: Test [19]/[68] cloud
+[12/02 23:36:55] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 95.94 82.09 72.38, 
+iou per cls is: [ 96.43  98.27  93.81 100.     0.38   1.78  65.4  100.   100.   100.
+   0.   100.    84.91]
+[12/02 23:36:55] S3DIS INFO: Test [20]/[68] cloud
+[12/02 23:37:45] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 95.38 94.64 54.91, 
+iou per cls is: [ 98.74  98.43  92.2  100.     0.   100.     0.    89.22  94.66   0.
+   0.     0.    40.55]
+[12/02 23:37:45] S3DIS INFO: Test [21]/[68] cloud
+[12/02 23:38:13] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 81.20 81.30 57.76, 
+iou per cls is: [97.6  98.11 47.16  0.   29.55 38.18 94.75 86.96 93.6   0.   86.56 33.99
+ 44.39]
+[12/02 23:38:13] S3DIS INFO: Test [22]/[68] cloud
+[12/02 23:38:38] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 91.99 87.41 75.02, 
+iou per cls is: [ 98.51  99.35  78.33   0.    43.45  71.9   77.35  80.2   94.91 100.
+  91.45  79.75  60.04]
+[12/02 23:38:38] S3DIS INFO: Test [23]/[68] cloud
+[12/02 23:39:08] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 94.52 88.83 75.88, 
+iou per cls is: [ 97.47  98.9   76.68   0.    23.43  66.72  90.68  73.85  92.69 100.
+  96.64  88.62  80.75]
+[12/02 23:39:08] S3DIS INFO: Test [24]/[68] cloud
+[12/02 23:39:37] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 88.75 87.99 66.51, 
+iou per cls is: [ 97.79  97.87  74.58   0.    57.83  74.39  57.15  83.52  79.83 100.
+  83.76   0.    57.92]
+[12/02 23:39:37] S3DIS INFO: Test [25]/[68] cloud
+[12/02 23:40:19] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 86.17 83.27 61.12, 
+iou per cls is: [98.2  98.48 58.27  0.   34.06 64.08 39.17 85.65 93.46  0.   93.02 77.81
+ 52.38]
+[12/02 23:40:19] S3DIS INFO: Test [26]/[68] cloud
+[12/02 23:41:27] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 84.19 82.89 67.94, 
+iou per cls is: [ 97.09  98.46  67.3    0.     7.58  45.97  89.87  63.55  91.82 100.
+  73.61  88.88  59.15]
+[12/02 23:41:27] S3DIS INFO: Test [27]/[68] cloud
+[12/02 23:42:39] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 85.35 82.50 60.74, 
+iou per cls is: [97.2  98.5  67.88  0.   25.11 31.2  83.9  83.99 88.7   0.   76.42 79.18
+ 57.54]
+[12/02 23:42:39] S3DIS INFO: Test [28]/[68] cloud
+[12/02 23:43:06] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 90.69 79.44 59.30, 
+iou per cls is: [ 98.51  97.77  86.86   0.    41.02 100.    96.33  88.7   88.51   0.
+  19.68   0.01  53.54]
+[12/02 23:43:06] S3DIS INFO: Test [29]/[68] cloud
+[12/02 23:43:43] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 83.85 88.09 44.71, 
+iou per cls is: [ 96.99  97.38  83.16   0.     0.     0.    51.68  55.32   0.   100.
+  50.47   0.    46.27]
+[12/02 23:43:43] S3DIS INFO: Test [30]/[68] cloud
+[12/02 23:44:46] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 92.07 81.67 55.04, 
+iou per cls is: [98.55 98.28 84.29  0.   17.39  0.   41.19 92.32 92.54  0.   92.77 29.82
+ 68.41]
+[12/02 23:44:46] S3DIS INFO: Test [31]/[68] cloud
+[12/02 23:46:47] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 86.37 83.38 62.69, 
+iou per cls is: [ 94.29  98.44  72.75   0.     0.   100.    54.38  85.55  88.98 100.
+  60.17  14.28  46.14]
+[12/02 23:46:47] S3DIS INFO: Test [32]/[68] cloud
+[12/02 23:47:19] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 90.69 80.73 60.69, 
+iou per cls is: [97.14 98.02 70.42  0.    5.09 84.04 80.13 82.05 98.05  0.   92.66 12.23
+ 69.1 ]
+[12/02 23:47:19] S3DIS INFO: Test [33]/[68] cloud
+[12/02 23:47:32] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 84.37 82.69 61.11, 
+iou per cls is: [ 97.29  98.66  73.07   0.    18.46 100.    31.47  91.85  90.13 100.
+  51.37   0.    42.12]
+[12/02 23:47:32] S3DIS INFO: Test [34]/[68] cloud
+[12/02 23:50:23] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 89.33 87.02 65.62, 
+iou per cls is: [ 98.53  98.94  78.78   0.    18.44 100.    96.75  92.07  91.39   0.
+  34.69  95.26  48.2 ]
+[12/02 23:50:23] S3DIS INFO: Test [35]/[68] cloud
+[12/02 23:50:50] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 87.15 79.96 58.45, 
+iou per cls is: [96.39 98.68 70.1   0.   26.06 37.14 32.93 82.53 91.11  0.   89.33 80.49
+ 55.07]
+[12/02 23:50:50] S3DIS INFO: Test [36]/[68] cloud
+[12/02 23:51:26] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 89.63 86.18 71.09, 
+iou per cls is: [ 97.48  99.07  74.76   0.    30.35  64.09  48.01  86.01  81.81 100.
+  91.47  84.96  66.12]
+[12/02 23:51:26] S3DIS INFO: Test [37]/[68] cloud
+[12/02 23:53:15] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 80.26 79.93 63.20, 
+iou per cls is: [93.74 95.78 52.81  0.   52.88 75.86 41.15 77.22 84.79 74.41 58.08 74.04
+ 40.81]
+[12/02 23:53:15] S3DIS INFO: Test [38]/[68] cloud
+[12/02 23:53:33] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 85.20 83.35 62.44, 
+iou per cls is: [ 96.33  96.56  70.01   0.     0.    84.79  34.77  67.63  98.8  100.
+  82.77  24.7   55.4 ]
+[12/02 23:53:33] S3DIS INFO: Test [39]/[68] cloud
+[12/02 23:53:58] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 83.09 76.88 54.84, 
+iou per cls is: [92.55 98.49 77.39  0.   49.75 67.61 59.63 73.58 90.88  0.   61.36  0.57
+ 41.16]
+[12/02 23:53:58] S3DIS INFO: Test [40]/[68] cloud
+[12/02 23:54:25] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 89.99 87.25 75.61, 
+iou per cls is: [ 94.36  99.64  80.72   0.    43.    84.9   74.02  90.4   97.24 100.
+  81.68  85.71  51.2 ]
+[12/02 23:54:25] S3DIS INFO: Test [41]/[68] cloud
+[12/02 23:54:51] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 92.71 91.42 79.71, 
+iou per cls is: [ 93.88  99.53  86.4    0.    85.38  91.69  82.92  79.69  92.02 100.
+  90.21  84.08  50.46]
+[12/02 23:54:51] S3DIS INFO: Test [42]/[68] cloud
+[12/02 23:56:52] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 76.14 77.32 60.83, 
+iou per cls is: [ 95.16  98.11  51.08   0.    43.93  65.55  40.45  86.1   78.5  100.
+  21.06  73.5   37.31]
+[12/02 23:56:52] S3DIS INFO: Test [43]/[68] cloud
+[12/02 23:57:16] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 89.97 89.10 69.18, 
+iou per cls is: [ 97.14  99.13  67.84   0.     0.    72.62  92.6   85.68  97.39 100.
+  90.    40.41  56.56]
+[12/02 23:57:16] S3DIS INFO: Test [44]/[68] cloud
+[12/02 23:57:28] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.25 95.85 93.55, 
+iou per cls is: [ 94.95  98.6   93.38 100.   100.   100.    81.53  88.87  95.13 100.
+  94.31  93.4   75.99]
+[12/02 23:57:28] S3DIS INFO: Test [45]/[68] cloud
+[12/02 23:58:04] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 82.77 85.45 63.23, 
+iou per cls is: [ 95.94  99.35  48.83   0.    24.34  61.44  85.15  85.96  81.48 100.
+  81.87   0.    57.68]
+[12/02 23:58:04] S3DIS INFO: Test [46]/[68] cloud
+[12/02 23:58:30] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 87.19 86.02 72.06, 
+iou per cls is: [ 92.83  99.79  77.44   0.    18.06  89.98  85.64  76.95  69.77 100.
+  69.54 100.    56.74]
+[12/02 23:58:30] S3DIS INFO: Test [47]/[68] cloud
+[12/02 23:59:11] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 91.82 88.26 68.60, 
+iou per cls is: [93.25 99.41 82.43  0.   20.23 86.41 87.52 93.03 92.14  0.   85.78 92.23
+ 59.35]
+[12/02 23:59:11] S3DIS INFO: Test [48]/[68] cloud
+[12/02 23:59:50] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 79.09 80.86 57.10, 
+iou per cls is: [92.94 95.58 57.31  0.   43.76 36.68 80.26 74.84 92.34  0.   64.36 60.69
+ 43.52]
+[12/02 23:59:50] S3DIS INFO: Test [49]/[68] cloud
+[12/03 00:00:27] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 95.69 94.72 77.13, 
+iou per cls is: [ 98.58  96.73  89.66   0.     0.   100.    91.43  88.08  93.36 100.
+  91.04  68.22  85.55]
+[12/03 00:00:27] S3DIS INFO: Test [50]/[68] cloud
+[12/03 00:01:32] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.22 92.10 63.35, 
+iou per cls is: [ 98.46  94.96  92.75   0.     0.   100.    93.85  78.75  93.15   0.
+  40.83  88.06  42.69]
+[12/03 00:01:32] S3DIS INFO: Test [51]/[68] cloud
+[12/03 00:06:39] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 80.79 79.09 49.18, 
+iou per cls is: [65.16 98.21 78.94  0.   19.26  0.   45.88 72.48 83.19  0.   69.21 63.9
+ 43.13]
+[12/03 00:06:39] S3DIS INFO: Test [52]/[68] cloud
+[12/03 00:12:51] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 69.14 79.08 44.46, 
+iou per cls is: [60.31 96.56 58.28  0.   28.83  0.   71.91 49.99 70.33 53.54 52.68  0.
+ 35.59]
+[12/03 00:12:51] S3DIS INFO: Test [53]/[68] cloud
+[12/03 00:13:28] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 86.26 82.09 52.53, 
+iou per cls is: [93.21 99.12 78.98  0.    0.    0.   70.99 82.21 85.9   0.   46.39 84.56
+ 41.58]
+[12/03 00:13:28] S3DIS INFO: Test [54]/[68] cloud
+[12/03 00:13:56] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 92.15 86.45 66.01, 
+iou per cls is: [96.82 98.28 74.94  0.   45.61 86.99 90.87 92.54 94.94  0.   93.56 30.65
+ 53.  ]
+[12/03 00:13:56] S3DIS INFO: Test [55]/[68] cloud
+[12/03 00:19:40] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 83.29 78.70 44.33, 
+iou per cls is: [95.41 97.8  77.62  0.   26.17  0.   31.07 66.67 70.47  0.   56.87  0.04
+ 54.2 ]
+[12/03 00:19:40] S3DIS INFO: Test [56]/[68] cloud
+[12/03 00:21:22] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 85.81 80.16 57.17, 
+iou per cls is: [94.89 98.16 71.65  0.   64.53 74.96 56.4  85.28 74.68  0.   58.88 11.95
+ 51.84]
+[12/03 00:21:22] S3DIS INFO: Test [57]/[68] cloud
+[12/03 00:21:59] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 91.42 90.04 62.76, 
+iou per cls is: [97.87 98.42 76.47  0.   55.03 59.56 78.29 91.44 96.11  0.   88.45  0.
+ 74.31]
+[12/03 00:21:59] S3DIS INFO: Test [58]/[68] cloud
+[12/03 00:22:21] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 93.38 92.73 57.96, 
+iou per cls is: [95.34 98.26 85.83  0.    0.   80.78 55.54 93.19 98.85  0.   89.77  0.
+ 55.88]
+[12/03 00:22:21] S3DIS INFO: Test [59]/[68] cloud
+[12/03 00:22:46] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 91.94 91.86 64.78, 
+iou per cls is: [98.08 98.61 74.58  0.    0.   61.47 92.11 84.99 85.11  0.   90.17 93.45
+ 63.58]
+[12/03 00:22:46] S3DIS INFO: Test [60]/[68] cloud
+[12/03 00:23:23] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 90.71 82.28 70.63, 
+iou per cls is: [ 98.66  98.79  67.02   0.     1.58  79.36  61.3   86.62  97.59 100.
+  90.8   69.22  67.18]
+[12/03 00:23:23] S3DIS INFO: Test [61]/[68] cloud
+[12/03 00:24:03] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 92.86 88.70 73.80, 
+iou per cls is: [ 98.37  97.93  81.17   0.    32.01  61.73  91.34  92.65  81.83 100.
+  95.04  89.41  37.88]
+[12/03 00:24:03] S3DIS INFO: Test [62]/[68] cloud
+[12/03 00:24:32] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 90.75 87.95 68.47, 
+iou per cls is: [ 96.    97.76  81.38   0.     0.    72.69  48.02  78.31  94.54  59.21
+  93.62 100.    68.63]
+[12/03 00:24:32] S3DIS INFO: Test [63]/[68] cloud
+[12/03 00:24:50] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 73.39 92.92 37.57, 
+iou per cls is: [ 93.52  98.5   80.02   0.     0.   100.     0.     0.     0.     0.
+   0.   100.    16.37]
+[12/03 00:24:50] S3DIS INFO: Test [64]/[68] cloud
+[12/03 00:25:09] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 69.46 69.27 24.41, 
+iou per cls is: [50.56 97.5  67.46  0.    3.67  0.   18.53  0.    0.    0.   57.03  0.
+ 22.57]
+[12/03 00:25:09] S3DIS INFO: Test [65]/[68] cloud
+[12/03 00:25:43] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 62.91 82.29 30.58, 
+iou per cls is: [ 39.54  97.44  65.21   0.     0.     0.    32.43   0.     0.   100.
+  32.15   0.    30.79]
+[12/03 00:25:43] S3DIS INFO: Test [66]/[68] cloud
+[12/03 00:25:46] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 78.84 88.55 39.87, 
+iou per cls is: [ 29.74  99.28  70.65 100.   100.     0.    58.92   0.     0.     0.
+   0.     0.    59.76]
+[12/03 00:25:46] S3DIS INFO: Test [67]/[68] cloud
+[12/03 00:26:08] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 80.09 83.89 42.05, 
+iou per cls is: [ 79.73  98.23  84.29 100.     0.     0.    26.77  55.59  62.5    0.
+   0.     0.    39.48]
+[12/03 00:26:08] S3DIS INFO: Best ckpt @E83,  test_oa , test_macc, test_miou: 87.22 68.54 61.62, 
+iou per cls is: [92.18 98.24 79.55  0.   25.79 49.25 55.36 80.57 86.73 61.55 69.52 51.95
+ 50.38]

Pretrained_Models/PN++_SEG_original/PN++_SEG_original_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointnet++,5,87.22,68.54,61.62,92.18,98.24,79.55,0.00,25.79,49.25,55.36,80.57,86.73,61.55,69.52,51.95,50.38,83,/workspace/FractalCloud/Model_logs/PN++_SEG_original,-

Pretrained_Models/PN++_SEG_original/checkpoint/s3dis-pointnet++_ckpt_best_616.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4c9f36b7dbfa62b82209ea7cac4edb0ac2ae849849d836a817549a054bd822e9
+size 11704549

Pretrained_Models/PNT_CLA_fractal/PNT_CLA_fractal20251202-130044-hiBZaBw9ZjnDx6CQ52vVak.log

@@ -0,0 +1,383 @@
+[12/02 13:00:44] ModelNet40Ply2048 INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 7271
+epoch: 0
+epochs: 600
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: SmoothCrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 1
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-ModelNet40Ply2048
+  tags: ['test']
+  name: PNT_CLA_fractal
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 10
+save_freq: -1
+root_dir: log/modelnet40ply2048
+pretrained_path: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/checkpoint/modelnet40_pointnext-s_ckpt_best_9238.pth
+datatransforms:
+  train: ['PointsToTensor', 'PointCloudScaleAndTranslate']
+  val: ['PointsToTensor']
+  vote: ['PointCloudScaleAndTranslate']
+  kwargs:
+    shift: [0.2, 0.2, 0.2]
+feature_keys: pos
+num_points: 1024
+dataset:
+  common:
+    NAME: ModelNet40Ply2048
+    data_dir: /workspace/PointNeXt/data/ModelNet40Ply2048
+  train:
+    split: train
+    num_points: 1024
+  val:
+    split: test
+    num_points: 1024
+batch_size: 32
+dataloader:
+  num_workers: 8
+num_classes: 40
+sched: cosine
+warmup_epochs: 0
+min_lr: None
+lr: 0.001
+optimizer:
+  NAME: adamw
+  weight_decay: 0.05
+log_dir: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal
+val_batch_size: 64
+model:
+  NAME: BaseCls
+  encoder_args:
+    NAME: PointNextEncoder
+    stage: [0, 1, 2, 3, 4, 5]
+    blocks: [1, 1, 1, 1, 1, 1]
+    strides: [1, 2, 2, 2, 2, 1]
+    width: 32
+    in_channels: 3
+    radius: 0.15
+    radius_scaling: 1.5
+    sa_layers: 2
+    sa_use_res: True
+    nsample: 32
+    expansion: 4
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  cls_args:
+    NAME: ClsHead
+    num_classes: 40
+    mlps: [512, 256]
+    norm_args:
+      norm: bn1d
+rank: 0
+distributed: False
+mp: False
+task_name: modelnet40ply2048
+exp_name: pointnext-s
+opts: mode=test
+run_dir: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal
+run_name: PNT_CLA_fractal
+ckpt_dir: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/code
+log_path: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/PNT_CLA_fractal20251202-130044-hiBZaBw9ZjnDx6CQ52vVak.log
+cfg_path: /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/cfg.yaml
+[12/02 13:00:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.15
+nsample: 32
+[12/02 13:00:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.22499999999999998
+nsample: 32
+[12/02 13:00:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.33749999999999997
+nsample: 32
+[12/02 13:00:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.50625
+nsample: 32
+[12/02 13:00:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: None
+nsample: None
+[12/02 13:00:50] ModelNet40Ply2048 INFO: BaseCls(
+  (encoder): PointNextEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(3, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(32, 64, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(128, 256, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (5): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(515, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): GroupAll()
+        )
+      )
+    )
+  )
+  (prediction): ClsHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Linear(in_features=512, out_features=512, bias=False)
+        (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Linear(in_features=512, out_features=256, bias=False)
+        (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (3): Dropout(p=0.5, inplace=False)
+      (4): Sequential(
+        (0): Linear(in_features=256, out_features=40, bias=True)
+      )
+    )
+  )
+  (criterion): SmoothCrossEntropy()
+)
+[12/02 13:00:50] ModelNet40Ply2048 INFO: Number of params: 1.3735 M
+[12/02 13:00:50] ModelNet40Ply2048 INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.05,
+    "params": [
+      "encoder.encoder.0.0.convs.0.0.weight",
+      "encoder.encoder.1.0.skipconv.0.weight",
+      "encoder.encoder.1.0.convs.0.0.weight",
+      "encoder.encoder.1.0.convs.1.0.weight",
+      "encoder.encoder.2.0.skipconv.0.weight",
+      "encoder.encoder.2.0.convs.0.0.weight",
+      "encoder.encoder.2.0.convs.1.0.weight",
+      "encoder.encoder.3.0.skipconv.0.weight",
+      "encoder.encoder.3.0.convs.0.0.weight",
+      "encoder.encoder.3.0.convs.1.0.weight",
+      "encoder.encoder.4.0.skipconv.0.weight",
+      "encoder.encoder.4.0.convs.0.0.weight",
+      "encoder.encoder.4.0.convs.1.0.weight",
+      "encoder.encoder.5.0.convs.0.0.weight",
+      "encoder.encoder.5.0.convs.1.0.weight",
+      "prediction.head.0.0.weight",
+      "prediction.head.2.0.weight",
+      "prediction.head.4.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
+      "encoder.encoder.0.0.convs.0.0.bias",
+      "encoder.encoder.1.0.skipconv.0.bias",
+      "encoder.encoder.1.0.convs.0.1.weight",
+      "encoder.encoder.1.0.convs.0.1.bias",
+      "encoder.encoder.1.0.convs.1.1.weight",
+      "encoder.encoder.1.0.convs.1.1.bias",
+      "encoder.encoder.2.0.skipconv.0.bias",
+      "encoder.encoder.2.0.convs.0.1.weight",
+      "encoder.encoder.2.0.convs.0.1.bias",
+      "encoder.encoder.2.0.convs.1.1.weight",
+      "encoder.encoder.2.0.convs.1.1.bias",
+      "encoder.encoder.3.0.skipconv.0.bias",
+      "encoder.encoder.3.0.convs.0.1.weight",
+      "encoder.encoder.3.0.convs.0.1.bias",
+      "encoder.encoder.3.0.convs.1.1.weight",
+      "encoder.encoder.3.0.convs.1.1.bias",
+      "encoder.encoder.4.0.skipconv.0.bias",
+      "encoder.encoder.4.0.convs.0.1.weight",
+      "encoder.encoder.4.0.convs.0.1.bias",
+      "encoder.encoder.4.0.convs.1.1.weight",
+      "encoder.encoder.4.0.convs.1.1.bias",
+      "encoder.encoder.5.0.convs.0.1.weight",
+      "encoder.encoder.5.0.convs.0.1.bias",
+      "encoder.encoder.5.0.convs.1.1.weight",
+      "encoder.encoder.5.0.convs.1.1.bias",
+      "prediction.head.0.1.weight",
+      "prediction.head.0.1.bias",
+      "prediction.head.2.1.weight",
+      "prediction.head.2.1.bias",
+      "prediction.head.4.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/02 13:00:51] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/02 13:00:51] ModelNet40Ply2048 INFO: length of validation dataset: 2468
+[12/02 13:00:51] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/02 13:00:51] ModelNet40Ply2048 INFO: number of classes of the dataset: 40, number of points sampled from dataset: 1024, number of points as model input: 1024
+[12/02 13:00:52] ModelNet40Ply2048 INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PNT_CLA_fractal/checkpoint/modelnet40_pointnext-s_ckpt_best_9238.pth
+[12/02 13:00:52] ModelNet40Ply2048 INFO: ckpts @ 142 epoch( {'best_val': 92.38249969482422} )
+[12/02 13:08:53] ModelNet40Ply2048 INFO: 
+Classes	Acc
+airplane  : 100.00%
+bathtub   : 94.00%
+bed       : 99.00%
+bench     : 80.00%
+bookshelf : 98.00%
+bottle    : 97.00%
+bowl      : 90.00%
+car       : 98.00%
+chair     : 100.00%
+cone      : 100.00%
+cup       : 85.00%
+curtain   : 95.00%
+desk      : 91.86%
+door      : 95.00%
+dresser   : 83.72%
+flower_pot: 0.00%
+glass_box : 96.00%
+guitar    : 100.00%
+keyboard  : 95.00%
+lamp      : 80.00%
+laptop    : 100.00%
+mantel    : 96.00%
+monitor   : 99.00%
+night_stand: 74.42%
+person    : 90.00%
+piano     : 96.00%
+plant     : 91.00%
+radio     : 70.00%
+range_hood: 96.00%
+sink      : 90.00%
+sofa      : 100.00%
+stairs    : 95.00%
+stool     : 80.00%
+table     : 85.00%
+tent      : 95.00%
+toilet    : 99.00%
+tv_stand  : 87.00%
+vase      : 81.00%
+wardrobe  : 75.00%
+xbox      : 85.00%
+E@142	OA: 92.38	mAcc: 89.05
+

Pretrained_Models/PNT_CLA_fractal/checkpoint/modelnet40_pointnext-s_ckpt_best_9238.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4dc059825506d560b9c6b9686acba8cdf4863c2b06786184101800226d4ad32
+size 16568345

Pretrained_Models/PNt_CLA_original/PNt_CLA_original20251204-104544-UEin34nSWnF7tLTWYmqAYy.log

@@ -0,0 +1,383 @@
+[12/04 10:45:44] ModelNet40Ply2048 INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 7271
+epoch: 0
+epochs: 600
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: SmoothCrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 1
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-ModelNet40Ply2048
+  tags: ['test']
+  name: PNt_CLA_original
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 10
+save_freq: -1
+root_dir: log/modelnet40ply2048
+pretrained_path: /workspace/FractalCloud/Model_logs/PNt_CLA_original/checkpoint/modelnet40_pointnext-s_ckpt_best_9311.pth
+datatransforms:
+  train: ['PointsToTensor', 'PointCloudScaleAndTranslate']
+  val: ['PointsToTensor']
+  vote: ['PointCloudScaleAndTranslate']
+  kwargs:
+    shift: [0.2, 0.2, 0.2]
+feature_keys: pos
+num_points: 1024
+dataset:
+  common:
+    NAME: ModelNet40Ply2048
+    data_dir: /workspace/PointNeXt/data/ModelNet40Ply2048
+  train:
+    split: train
+    num_points: 1024
+  val:
+    split: test
+    num_points: 1024
+batch_size: 32
+dataloader:
+  num_workers: 8
+num_classes: 40
+sched: cosine
+warmup_epochs: 0
+min_lr: None
+lr: 0.001
+optimizer:
+  NAME: adamw
+  weight_decay: 0.05
+log_dir: /workspace/FractalCloud/Model_logs/PNt_CLA_original
+val_batch_size: 64
+model:
+  NAME: BaseCls
+  encoder_args:
+    NAME: PointNextEncoder
+    stage: [0, 1, 2, 3, 4, 5]
+    blocks: [1, 1, 1, 1, 1, 1]
+    strides: [1, 2, 2, 2, 2, 1]
+    width: 32
+    in_channels: 3
+    radius: 0.15
+    radius_scaling: 1.5
+    sa_layers: 2
+    sa_use_res: True
+    nsample: 32
+    expansion: 4
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  cls_args:
+    NAME: ClsHead
+    num_classes: 40
+    mlps: [512, 256]
+    norm_args:
+      norm: bn1d
+rank: 0
+distributed: False
+mp: False
+task_name: modelnet40ply2048
+exp_name: pointnext-s
+opts: mode=test
+run_dir: /workspace/FractalCloud/Model_logs/PNt_CLA_original
+run_name: PNt_CLA_original
+ckpt_dir: /workspace/FractalCloud/Model_logs/PNt_CLA_original/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PNt_CLA_original/code
+log_path: /workspace/FractalCloud/Model_logs/PNt_CLA_original/PNt_CLA_original20251204-104544-UEin34nSWnF7tLTWYmqAYy.log
+cfg_path: /workspace/FractalCloud/Model_logs/PNt_CLA_original/cfg.yaml
+[12/04 10:45:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.15
+nsample: 32
+[12/04 10:45:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.22499999999999998
+nsample: 32
+[12/04 10:45:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.33749999999999997
+nsample: 32
+[12/04 10:45:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.50625
+nsample: 32
+[12/04 10:45:44] ModelNet40Ply2048 INFO: NAME: ballquery
+normalize_dp: True
+radius: None
+nsample: None
+[12/04 10:45:48] ModelNet40Ply2048 INFO: BaseCls(
+  (encoder): PointNextEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(3, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(32, 64, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(128, 256, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (5): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(515, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): GroupAll()
+        )
+      )
+    )
+  )
+  (prediction): ClsHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Linear(in_features=512, out_features=512, bias=False)
+        (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Linear(in_features=512, out_features=256, bias=False)
+        (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (3): Dropout(p=0.5, inplace=False)
+      (4): Sequential(
+        (0): Linear(in_features=256, out_features=40, bias=True)
+      )
+    )
+  )
+  (criterion): SmoothCrossEntropy()
+)
+[12/04 10:45:48] ModelNet40Ply2048 INFO: Number of params: 1.3735 M
+[12/04 10:45:48] ModelNet40Ply2048 INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.05,
+    "params": [
+      "encoder.encoder.0.0.convs.0.0.weight",
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+      "encoder.encoder.1.0.convs.0.0.weight",
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+  }
+}
+[12/04 10:45:49] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/04 10:45:49] ModelNet40Ply2048 INFO: length of validation dataset: 2468
+[12/04 10:45:50] ModelNet40Ply2048 INFO: ==> sucessfully loaded test data
+[12/04 10:45:50] ModelNet40Ply2048 INFO: number of classes of the dataset: 40, number of points sampled from dataset: 1024, number of points as model input: 1024
+[12/04 10:45:51] ModelNet40Ply2048 INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PNt_CLA_original/checkpoint/modelnet40_pointnext-s_ckpt_best_9311.pth
+[12/04 10:45:51] ModelNet40Ply2048 INFO: ckpts @ 419 epoch( {'best_val': 93.11183166503906} )
+[12/04 10:45:56] ModelNet40Ply2048 INFO: 
+Classes	Acc
+airplane  : 100.00%
+bathtub   : 98.00%
+bed       : 99.00%
+bench     : 80.00%
+bookshelf : 99.00%
+bottle    : 96.00%
+bowl      : 100.00%
+car       : 100.00%
+chair     : 100.00%
+cone      : 100.00%
+cup       : 75.00%
+curtain   : 90.00%
+desk      : 89.53%
+door      : 100.00%
+dresser   : 91.86%
+flower_pot: 15.00%
+glass_box : 95.00%
+guitar    : 99.00%
+keyboard  : 100.00%
+lamp      : 85.00%
+laptop    : 100.00%
+mantel    : 95.00%
+monitor   : 99.00%
+night_stand: 72.09%
+person    : 100.00%
+piano     : 97.00%
+plant     : 85.00%
+radio     : 85.00%
+range_hood: 94.00%
+sink      : 95.00%
+sofa      : 100.00%
+stairs    : 95.00%
+stool     : 80.00%
+table     : 91.00%
+tent      : 95.00%
+toilet    : 100.00%
+tv_stand  : 86.00%
+vase      : 83.00%
+wardrobe  : 80.00%
+xbox      : 90.00%
+E@419	OA: 93.11	mAcc: 90.86
+

Pretrained_Models/PNt_CLA_original/checkpoint/modelnet40_pointnext-s_ckpt_best_9311.pth

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Pretrained_Models/PNt_SEG_fractal/PNt_SEG_fractal20251202-141500-BYuZJg8u7nYVoBWEGzA6Qu.log

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+[12/02 14:15:00] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 8203
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PNt_SEG_fractal
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/checkpoint/s3dis-pointnext-s_ckpt_best-623.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 32
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointNextEncoder
+    stage: [0, 1, 2, 3, 4]
+    blocks: [1, 1, 1, 1, 1]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 2
+    sa_use_res: True
+    width: 32
+    in_channels: 4
+    expansion: 4
+    radius: 0.1
+    nsample: 32
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNextDecoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
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+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointnext-s
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal
+run_name: PNt_SEG_fractal
+ckpt_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/code
+log_path: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/PNt_SEG_fractal20251202-141500-BYuZJg8u7nYVoBWEGzA6Qu.log
+cfg_path: /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/cfg.yaml
+[12/02 14:15:00] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+[12/02 14:15:00] S3DIS INFO: NAME: ballquery
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+radius: 0.2
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+[12/02 14:15:00] S3DIS INFO: NAME: ballquery
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+[12/02 14:15:00] S3DIS INFO: NAME: ballquery
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+radius: 0.8
+nsample: 32
+[12/02 14:15:04] S3DIS INFO: BaseSeg(
+  (encoder): PointNextEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
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+        (0): SetAbstraction(
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+            (0): Conv1d(32, 64, kernel_size=(1,), stride=(1,))
+          )
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+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
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+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
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+          (act): ReLU(inplace=True)
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+            (0): Sequential(
+              (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
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+          (grouper): QueryAndGroup()
+        )
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+      (4): Sequential(
+        (0): SetAbstraction(
+          (skipconv): Sequential(
+            (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+    )
+  )
+  (decoder): PointNextDecoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/02 14:15:04] S3DIS INFO: Number of params: 0.7922 M
+[12/02 14:15:04] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
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+    "params": [
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+    "lr_scale": 1.0
+  }
+}
+[12/02 14:15:04] S3DIS INFO: 
+Totally 68 samples in val set
+[12/02 14:15:04] S3DIS INFO: length of validation dataset: 68
+[12/02 14:15:04] S3DIS INFO: number of classes of the dataset: 13
+[12/02 14:15:04] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PNt_SEG_fractal/checkpoint/s3dis-pointnext-s_ckpt_best-623.pth
+[12/02 14:15:04] S3DIS INFO: ckpts @ 19 epoch( {'best_val': 60.23859786987305} )
+[12/02 14:15:04] S3DIS INFO: length of test dataset: 68
+[12/02 14:15:04] S3DIS INFO: Test [0]/[68] cloud
+[12/02 14:18:28] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 89.76 96.58 48.83, 
+iou per cls is: [ 96.93  98.7   74.01   0.     0.     0.    97.17   0.   100.   100.
+   0.     0.    68.04]
+[12/02 14:18:28] S3DIS INFO: Test [1]/[68] cloud
+[12/02 14:20:55] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 91.07 96.79 47.63, 
+iou per cls is: [ 95.86  99.21  79.61   0.     0.     0.    76.44   0.   100.   100.
+   0.     0.    68.09]
+[12/02 14:20:55] S3DIS INFO: Test [2]/[68] cloud
+[12/02 14:25:33] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 83.95 83.82 60.59, 
+iou per cls is: [ 96.24  99.4   71.71   0.     8.96  51.62  46.38  94.74  94.82 100.
+   0.    72.8   51.02]
+[12/02 14:25:33] S3DIS INFO: Test [3]/[68] cloud
+[12/02 14:53:32] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 90.13 89.86 76.57, 
+iou per cls is: [ 96.65  97.33  80.6    0.    41.84 100.    95.45  92.35  91.33  99.71
+  77.14  61.75  61.27]
+[12/02 14:53:32] S3DIS INFO: Test [4]/[68] cloud
+[12/02 15:05:16] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 85.97 78.93 58.49, 
+iou per cls is: [ 95.17  99.39  70.19   0.    48.98  71.04  39.28  68.77  94.69 100.
+   0.    28.02  44.83]
+[12/02 15:05:16] S3DIS INFO: Test [5]/[68] cloud
+[12/02 16:07:33] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 77.63 71.84 28.46, 
+iou per cls is: [87.15 97.29 50.46  0.    0.31  0.17 24.28  0.    0.   29.3  67.86  0.
+ 13.14]
+[12/02 16:07:33] S3DIS INFO: Test [6]/[68] cloud
+[12/02 16:15:14] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 97.28 96.67 72.94, 
+iou per cls is: [ 97.95  99.15  95.38   0.     0.   100.    58.86 100.   100.   100.
+ 100.     0.    96.87]
+[12/02 16:15:14] S3DIS INFO: Test [7]/[68] cloud
+[12/02 16:19:13] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 95.99 94.18 70.62, 
+iou per cls is: [ 97.24  99.39  93.94 100.     0.   100.    27.53 100.   100.   100.
+ 100.     0.     0.  ]
+[12/02 16:19:13] S3DIS INFO: Test [8]/[68] cloud
+[12/02 16:23:23] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.24 98.09 88.51, 
+iou per cls is: [ 97.61  99.42  97.04 100.   100.   100.    82.42 100.   100.   100.
+ 100.     0.    74.12]
+[12/02 16:23:23] S3DIS INFO: Test [9]/[68] cloud
+[12/02 16:32:12] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 88.16 89.78 52.73, 
+iou per cls is: [ 97.64  99.26  88.02   0.     0.     6.6   16.63 100.   100.   100.
+   0.     0.    77.33]
+[12/02 16:32:12] S3DIS INFO: Test [10]/[68] cloud
+[12/02 16:34:49] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 92.54 94.48 70.50, 
+iou per cls is: [ 98.8   99.2   90.76 100.     0.   100.    53.58 100.   100.   100.
+   0.     0.    74.13]
+[12/02 16:34:49] S3DIS INFO: Test [11]/[68] cloud
+[12/02 16:44:29] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 84.69 80.93 35.27, 
+iou per cls is: [ 97.73  99.33  77.9    0.     0.     0.03  16.98   0.     0.   100.
+   0.     0.    66.55]
+[12/02 16:44:29] S3DIS INFO: Test [12]/[68] cloud
+[12/02 18:13:55] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 89.79 94.60 39.60, 
+iou per cls is: [ 95.49  98.11  82.41   0.     0.     0.    48.05   0.     0.   100.
+   0.     0.    90.77]
+[12/02 18:13:55] S3DIS INFO: Test [13]/[68] cloud
+[12/02 18:20:02] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 95.13 94.63 63.39, 
+iou per cls is: [ 98.75  97.05  93.94   0.     0.   100.    52.85 100.   100.   100.
+   0.     0.    81.53]
+[12/02 18:20:02] S3DIS INFO: Test [14]/[68] cloud
+[12/02 18:24:27] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 91.95 82.14 48.81, 
+iou per cls is: [ 98.26  99.26  94.65 100.     0.   100.    75.02   0.     0.     1.03
+  25.46   0.    40.79]
+[12/02 18:24:27] S3DIS INFO: Test [15]/[68] cloud
+[12/02 18:56:47] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 95.62 89.42 39.63, 
+iou per cls is: [98.61 98.51 93.12  0.    0.    0.   58.97  0.    0.   45.38 63.84  0.
+ 56.71]
+[12/02 18:56:47] S3DIS INFO: Test [16]/[68] cloud
+[12/02 19:00:41] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 94.82 96.16 79.00, 
+iou per cls is: [ 98.13  99.15  90.21 100.   100.   100.    70.32 100.   100.   100.
+   0.     0.    69.23]
+[12/02 19:00:41] S3DIS INFO: Test [17]/[68] cloud
+[12/02 19:07:40] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 92.97 94.10 54.52, 
+iou per cls is: [ 98.68  99.28  88.42   0.     0.   100.    45.31   0.   100.   100.
+   0.     0.    77.11]
+[12/02 19:07:40] S3DIS INFO: Test [18]/[68] cloud
+[12/02 19:09:21] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 91.03 87.38 55.17, 
+iou per cls is: [ 97.29  99.07  85.77   0.     0.     0.    20.32 100.   100.   100.
+ 100.     0.    14.79]
+[12/02 19:09:21] S3DIS INFO: Test [19]/[68] cloud
+[12/02 19:17:25] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 95.40 82.11 48.59, 
+iou per cls is: [ 96.7   97.71  93.6    0.     0.03   2.6   55.88   0.   100.   100.
+   0.     0.    85.14]
+[12/02 19:17:25] S3DIS INFO: Test [20]/[68] cloud
+[12/02 19:23:59] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 95.36 94.05 62.41, 
+iou per cls is: [ 99.71  98.64  90.61 100.   100.     0.     0.    91.72  95.94 100.
+   0.     0.    34.65]
+[12/02 19:23:59] S3DIS INFO: Test [21]/[68] cloud
+[12/02 19:27:27] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 84.33 81.04 66.00, 
+iou per cls is: [ 97.01  97.49  50.82   0.    41.66  53.78  90.01  89.4   93.21 100.
+  90.05   0.8   53.79]
+[12/02 19:27:27] S3DIS INFO: Test [22]/[68] cloud
+[12/02 19:30:43] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 90.83 87.36 74.08, 
+iou per cls is: [ 98.32  99.32  71.98   0.    27.94  62.47  86.7   79.08  92.5  100.
+  92.32  91.88  60.57]
+[12/02 19:30:43] S3DIS INFO: Test [23]/[68] cloud
+[12/02 19:34:14] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 93.72 90.66 76.24, 
+iou per cls is: [ 97.27  98.25  75.29   0.    45.8   55.3   94.05  69.18  86.89 100.
+  96.13  93.93  79.03]
+[12/02 19:34:14] S3DIS INFO: Test [24]/[68] cloud
+[12/02 19:37:50] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 89.08 88.61 74.42, 
+iou per cls is: [ 97.33  98.13  73.15   0.    32.3   76.08  92.16  76.63  75.68 100.
+  87.93 100.    58.14]
+[12/02 19:37:50] S3DIS INFO: Test [25]/[68] cloud
+[12/02 19:42:50] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 88.17 85.01 71.67, 
+iou per cls is: [ 98.35  98.18  64.58   0.    41.71  73.91  69.68  80.39  91.59 100.
+  92.27  73.4   47.63]
+[12/02 19:42:50] S3DIS INFO: Test [26]/[68] cloud
+[12/02 19:50:42] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 85.04 84.74 69.95, 
+iou per cls is: [ 94.31  98.31  68.36   0.    26.49  55.63  86.42  66.41  90.52 100.
+  75.47  86.91  60.51]
+[12/02 19:50:42] S3DIS INFO: Test [27]/[68] cloud
+[12/02 19:59:17] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 84.50 82.21 67.65, 
+iou per cls is: [ 95.24  98.27  68.14   0.    22.17  31.31  87.08  88.95  93.23 100.
+  74.8   68.03  52.19]
+[12/02 19:59:17] S3DIS INFO: Test [28]/[68] cloud
+[12/02 20:02:47] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 89.44 80.76 67.65, 
+iou per cls is: [ 98.52  96.78  85.01   0.    60.52 100.    92.61  89.06  89.93 100.
+  10.55   6.15  50.38]
+[12/02 20:02:47] S3DIS INFO: Test [29]/[68] cloud
+[12/02 20:07:20] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 84.29 90.79 47.04, 
+iou per cls is: [ 97.68  96.28  87.96   0.     0.     0.    86.53  47.24 100.     0.
+  49.72   0.    46.09]
+[12/02 20:07:20] S3DIS INFO: Test [30]/[68] cloud
+[12/02 20:15:10] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 92.62 84.80 65.66, 
+iou per cls is: [ 99.03  98.21  87.32   0.     8.59   0.    93.11  96.14  92.57 100.
+  87.08  28.63  62.86]
+[12/02 20:15:10] S3DIS INFO: Test [31]/[68] cloud
+[12/02 20:28:51] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 87.12 89.19 68.31, 
+iou per cls is: [ 94.06  98.52  78.46   0.     0.   100.    76.27  87.66  93.08 100.
+  56.83  62.06  41.1 ]
+[12/02 20:28:51] S3DIS INFO: Test [32]/[68] cloud
+[12/02 20:32:45] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 92.42 88.89 76.79, 
+iou per cls is: [ 95.84  98.26  76.3    0.    70.42  75.89  96.73  84.97  97.26 100.
+  93.11  43.73  65.76]
+[12/02 20:32:45] S3DIS INFO: Test [33]/[68] cloud
+[12/02 20:34:39] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 88.16 88.66 59.82, 
+iou per cls is: [ 97.97  97.85  79.89   0.    38.12   0.    84.77  94.72  93.07 100.
+  50.21   0.    41.04]
+[12/02 20:34:39] S3DIS INFO: Test [34]/[68] cloud
+[12/02 20:53:13] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 90.62 88.97 74.84, 
+iou per cls is: [ 98.59  98.81  82.65   0.    32.46 100.    96.46  92.15  93.48 100.
+  42.01  94.28  42.09]
+[12/02 20:53:13] S3DIS INFO: Test [35]/[68] cloud
+[12/02 20:56:48] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 89.62 84.28 71.51, 
+iou per cls is: [ 96.55  98.05  72.19   0.    28.38  31.4   96.3   77.6   80.54 100.
+  94.96  82.38  71.23]
+[12/02 20:56:48] S3DIS INFO: Test [36]/[68] cloud
+[12/02 21:01:18] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 90.56 92.15 76.73, 
+iou per cls is: [ 97.17  98.64  77.94   0.    39.63  71.43  98.26  84.72  92.61 100.
+  87.22  87.74  62.19]
+[12/02 21:01:18] S3DIS INFO: Test [37]/[68] cloud
+[12/02 21:14:35] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 81.26 79.42 63.61, 
+iou per cls is: [96.   96.   54.12  0.   44.82 76.18 77.69 76.1  85.81 42.41 60.47 72.74
+ 44.61]
+[12/02 21:14:35] S3DIS INFO: Test [38]/[68] cloud
+[12/02 21:17:05] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 88.60 88.99 68.81, 
+iou per cls is: [ 96.28  95.71  77.4    0.     0.    83.86  93.3   68.27  98.43 100.
+  86.41  36.16  58.77]
+[12/02 21:17:05] S3DIS INFO: Test [39]/[68] cloud
+[12/02 21:20:34] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 83.60 80.40 66.33, 
+iou per cls is: [ 93.74  97.57  79.9    0.    66.2   80.02  75.05  77.05  94.05 100.
+  60.5    0.    38.2 ]
+[12/02 21:20:34] S3DIS INFO: Test [40]/[68] cloud
+[12/02 21:24:25] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 90.74 88.59 76.97, 
+iou per cls is: [ 95.88  99.31  80.42   0.    52.65  83.78  92.45  87.21  96.28 100.
+  87.05  71.71  53.84]
+[12/02 21:24:25] S3DIS INFO: Test [41]/[68] cloud
+[12/02 21:28:16] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 92.72 91.90 80.34, 
+iou per cls is: [ 96.63  98.82  85.12   0.    88.08  89.02  95.83  79.    90.67 100.
+  88.52  79.92  52.85]
+[12/02 21:28:16] S3DIS INFO: Test [42]/[68] cloud
+[12/02 21:43:03] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 76.87 80.56 64.71, 
+iou per cls is: [ 96.51  97.46  53.36   0.    55.86  57.47  87.97  83.95  80.28 100.
+  23.59  70.06  34.68]
+[12/02 21:43:03] S3DIS INFO: Test [43]/[68] cloud
+[12/02 21:46:22] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 89.08 88.20 68.23, 
+iou per cls is: [ 97.47  99.22  67.66   0.     0.    75.21  56.57  85.27  96.36 100.
+  85.9   72.45  50.85]
+[12/02 21:46:22] S3DIS INFO: Test [44]/[68] cloud
+[12/02 21:48:10] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.96 97.11 94.78, 
+iou per cls is: [ 94.38  97.89  95.63 100.   100.   100.    94.46  89.35  96.88 100.
+  95.24  92.23  76.08]
+[12/02 21:48:10] S3DIS INFO: Test [45]/[68] cloud
+[12/02 21:53:21] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 86.00 87.27 65.40, 
+iou per cls is: [ 96.04  99.    59.35   0.    36.06  67.12  82.54  85.53  82.16 100.
+  80.96   0.    61.41]
+[12/02 21:53:21] S3DIS INFO: Test [46]/[68] cloud
+[12/02 21:57:05] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 88.71 87.98 67.40, 
+iou per cls is: [ 96.02  99.54  81.05   0.    51.13  92.23  92.55  73.83  62.98 100.
+  69.59   0.    57.28]
+[12/02 21:57:05] S3DIS INFO: Test [47]/[68] cloud
+[12/02 22:03:00] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 91.95 88.36 76.45, 
+iou per cls is: [ 93.85  98.77  83.58   0.    25.11  89.68  98.02  87.3   86.97 100.
+  84.42  88.3   57.82]
+[12/02 22:03:00] S3DIS INFO: Test [48]/[68] cloud
+[12/02 22:09:02] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 83.28 81.82 58.26, 
+iou per cls is: [94.18 94.33 63.19  0.   57.98 41.2  56.06 72.31 91.04  0.   82.02 53.04
+ 52.1 ]
+[12/02 22:09:02] S3DIS INFO: Test [49]/[68] cloud
+[12/02 22:14:57] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 95.49 94.15 68.96, 
+iou per cls is: [ 98.37  95.95  90.7    0.     0.   100.    96.7   89.81  91.17   0.
+  90.94  72.61  70.2 ]
+[12/02 22:14:57] S3DIS INFO: Test [50]/[68] cloud
+[12/02 22:24:07] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.19 92.59 71.92, 
+iou per cls is: [ 98.67  95.13  91.97   0.     0.   100.    95.6   72.19  93.01 100.
+  59.39  87.56  41.42]
+[12/02 22:24:07] S3DIS INFO: Test [51]/[68] cloud
+[12/02 23:03:43] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 81.85 80.42 51.18, 
+iou per cls is: [66.29 97.9  80.95  0.    6.58  0.   92.47 75.36 77.37  0.   72.95 47.75
+ 47.76]
+[12/02 23:03:43] S3DIS INFO: Test [52]/[68] cloud
+[12/02 23:47:41] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 75.53 79.03 53.44, 
+iou per cls is: [ 65.63  96.25  64.06   0.    22.66   0.    80.9   48.56  67.84  35.76
+  66.35 100.    46.74]
+[12/02 23:47:41] S3DIS INFO: Test [53]/[68] cloud
+[12/02 23:52:34] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 81.42 80.70 56.46, 
+iou per cls is: [ 92.54  98.7   70.68   2.54   0.     0.    44.54  84.05  93.7  100.
+  33.45  80.36  33.41]
+[12/02 23:52:34] S3DIS INFO: Test [54]/[68] cloud
+[12/02 23:56:37] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 93.95 92.22 79.80, 
+iou per cls is: [ 96.68  98.17  80.52   0.    68.37  79.6   95.15  94.15  96.67 100.
+  94.79  78.25  55.08]
+[12/02 23:56:37] S3DIS INFO: Test [55]/[68] cloud
+[12/03 00:37:02] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 84.82 81.97 46.03, 
+iou per cls is: [96.76 97.85 81.31  0.   43.29  0.   31.37 72.19 62.6   0.   58.69  0.06
+ 54.28]
+[12/03 00:37:02] S3DIS INFO: Test [56]/[68] cloud
+[12/03 00:49:23] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 87.08 83.96 68.50, 
+iou per cls is: [ 96.17  97.54  70.2    0.    29.33  75.27  91.68  79.08  80.65 100.
+  59.54  50.68  60.31]
+[12/03 00:49:23] S3DIS INFO: Test [57]/[68] cloud
+[12/03 00:54:34] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 90.16 90.78 77.30, 
+iou per cls is: [ 97.65  98.13  71.16   0.    41.05  61.62  93.47  87.36  93.4  100.
+  89.22 100.    71.87]
+[12/03 00:54:34] S3DIS INFO: Test [58]/[68] cloud
+[12/03 00:57:37] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 93.72 95.60 67.83, 
+iou per cls is: [ 96.8   98.72  86.03   0.     0.    69.7   93.32  92.39  99.45 100.
+  90.1    0.    55.23]
+[12/03 00:57:37] S3DIS INFO: Test [59]/[68] cloud
+[12/03 01:01:02] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 90.33 89.97 70.53, 
+iou per cls is: [ 97.76  98.75  68.31   0.     0.    58.33  93.82  79.85  77.27 100.
+  90.18  89.07  63.6 ]
+[12/03 01:01:02] S3DIS INFO: Test [60]/[68] cloud
+[12/03 01:05:58] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 90.83 84.45 72.94, 
+iou per cls is: [ 98.36  98.69  66.71   0.     1.21  78.56  84.55  84.83  95.87 100.
+  89.78  82.24  67.38]
+[12/03 01:05:58] S3DIS INFO: Test [61]/[68] cloud
+[12/03 01:11:00] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 94.10 91.39 78.97, 
+iou per cls is: [ 98.32  98.07  81.19   0.    56.91  54.63  95.42  90.05  90.41 100.
+  96.89  92.27  72.39]
+[12/03 01:11:00] S3DIS INFO: Test [62]/[68] cloud
+[12/03 01:14:50] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 91.66 92.85 72.70, 
+iou per cls is: [ 95.69  97.32  84.2    0.     0.    71.45  98.49  72.37  88.56  75.67
+  92.4  100.    68.93]
+[12/03 01:14:50] S3DIS INFO: Test [63]/[68] cloud
+[12/03 01:17:30] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 74.03 93.08 38.45, 
+iou per cls is: [ 93.43  98.83  87.54   0.     0.     0.     0.     0.     0.   100.
+   0.   100.    20.  ]
+[12/03 01:17:30] S3DIS INFO: Test [64]/[68] cloud
+[12/03 01:20:11] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 68.12 72.33 27.69, 
+iou per cls is: [50.23 94.91 64.6   0.   16.76  0.   56.51  0.    0.    0.   57.3   0.
+ 19.62]
+[12/03 01:20:11] S3DIS INFO: Test [65]/[68] cloud
+[12/03 01:24:50] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 65.93 85.86 49.33, 
+iou per cls is: [ 37.93  96.23  81.13   0.     0.     0.    65.41   0.   100.   100.
+  33.89 100.    26.76]
+[12/03 01:24:50] S3DIS INFO: Test [66]/[68] cloud
+[12/03 01:25:19] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 80.16 87.70 47.15, 
+iou per cls is: [  3.03  98.53  87.95   0.     0.   100.    68.12 100.     0.   100.
+   0.     0.    55.38]
+[12/03 01:25:19] S3DIS INFO: Test [67]/[68] cloud
+[12/03 01:28:34] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 84.69 85.89 44.72, 
+iou per cls is: [ 87.84  97.33  88.96   0.     0.     0.    37.63  50.75  72.22 100.
+   0.     0.    46.65]
+[12/03 01:28:34] S3DIS INFO: Best ckpt @E19,  test_oa , test_macc, test_miou: 87.77 69.44 62.03, 
+iou per cls is: [92.82 98.12 80.72  0.07 26.78 50.47 64.93 80.12 85.8  44.99 71.09 58.
+ 52.43]

Pretrained_Models/PNt_SEG_fractal/PNt_SEG_fractal_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointnext-s,5,87.77,69.44,62.03,92.82,98.12,80.72,0.07,26.78,50.47,64.93,80.12,85.80,44.99,71.09,58.00,52.43,19,/workspace/FractalCloud/Model_logs/PNt_SEG_fractal,-

Pretrained_Models/PNt_SEG_fractal/checkpoint/s3dis-pointnext-s_ckpt_best-620.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6c98111783d326d4626af0edcdd25b35f324337bb24927af679de7e74b91869
+size 9606497

Pretrained_Models/PNt_SEG_original/PNt_SEG_original20251202-141038-mbRpETout6SaSAV7Knibvu.log

@@ -0,0 +1,686 @@
+[12/02 14:10:38] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 183
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PNt_SEG_original
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PNt_SEG_original/checkpoint/s3dis-train-pointnext-s_ckpt_best_626.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 32
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_original
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointNextEncoder
+    stage: [0, 1, 2, 3, 4]
+    blocks: [1, 1, 1, 1, 1]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 2
+    sa_use_res: True
+    width: 32
+    in_channels: 4
+    expansion: 4
+    radius: 0.1
+    nsample: 32
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNextDecoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
+      norm: bn
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointnext-s
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_original
+run_name: PNt_SEG_original
+ckpt_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_original/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PNt_SEG_original/code
+log_path: /workspace/FractalCloud/Model_logs/PNt_SEG_original/PNt_SEG_original20251202-141038-mbRpETout6SaSAV7Knibvu.log
+cfg_path: /workspace/FractalCloud/Model_logs/PNt_SEG_original/cfg.yaml
+[12/02 14:10:38] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+[12/02 14:10:38] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+[12/02 14:10:38] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+[12/02 14:10:38] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+[12/02 14:10:45] S3DIS INFO: BaseSeg(
+  (encoder): PointNextEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
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+            (0): Sequential(
+              (0): Conv1d(4, 32, kernel_size=(1,), stride=(1,))
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+            (0): Conv1d(32, 64, kernel_size=(1,), stride=(1,))
+          )
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+          (convs): Sequential(
+            (0): Sequential(
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+              (1): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
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+              (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
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+            (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,))
+          )
+          (act): ReLU(inplace=True)
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
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+            (1): Sequential(
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+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
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+        )
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+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
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+              (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
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+        (0): SetAbstraction(
+          (skipconv): Sequential(
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+          )
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+          (convs): Sequential(
+            (0): Sequential(
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+              (2): ReLU(inplace=True)
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+            (1): Sequential(
+              (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+      )
+    )
+  )
+  (decoder): PointNextDecoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/02 14:10:45] S3DIS INFO: Number of params: 0.7922 M
+[12/02 14:10:45] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
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+      "head.head.2.0.weight"
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+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
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+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/02 14:10:45] S3DIS INFO: 
+Totally 68 samples in val set
+[12/02 14:10:45] S3DIS INFO: length of validation dataset: 68
+[12/02 14:10:45] S3DIS INFO: number of classes of the dataset: 13
+[12/02 14:10:45] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PNt_SEG_original/checkpoint/s3dis-train-pointnext-s_ckpt_best_626.pth
+[12/02 14:10:45] S3DIS INFO: ckpts @ 52 epoch( {'best_val': 60.69001770019531} )
+[12/02 14:10:45] S3DIS INFO: length of test dataset: 68
+[12/02 14:10:45] S3DIS INFO: Test [0]/[68] cloud
+[12/02 14:11:16] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 84.22 93.81 53.08, 
+iou per cls is: [ 96.66  98.83  65.15 100.     0.     0.    90.     0.   100.   100.
+   0.     0.    39.35]
+[12/02 14:11:16] S3DIS INFO: Test [1]/[68] cloud
+[12/02 14:11:36] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 90.67 96.53 47.98, 
+iou per cls is: [ 97.11  98.7   77.21 100.     0.     0.    86.66   0.     0.   100.
+   0.     0.    64.08]
+[12/02 14:11:36] S3DIS INFO: Test [2]/[68] cloud
+[12/02 14:12:22] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 84.65 82.61 61.88, 
+iou per cls is: [ 96.38  98.84  72.34   0.    29.86  53.51  29.53  94.07  93.49 100.
+   0.    82.83  53.56]
+[12/02 14:12:22] S3DIS INFO: Test [3]/[68] cloud
+[12/02 14:17:09] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 88.20 87.14 63.37, 
+iou per cls is: [90.99 97.25 79.44  0.   57.87  0.   80.48 91.9  87.   87.99 63.81 28.86
+ 58.24]
+[12/02 14:17:09] S3DIS INFO: Test [4]/[68] cloud
+[12/02 14:19:00] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 89.39 83.70 56.28, 
+iou per cls is: [95.82 99.47 76.93  0.   58.87 82.22 67.09 70.29 92.16  0.    0.   35.41
+ 53.41]
+[12/02 14:19:00] S3DIS INFO: Test [5]/[68] cloud
+[12/02 14:29:35] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 73.24 76.67 33.40, 
+iou per cls is: [72.23 97.89 42.84  0.    4.07  2.89 61.15  0.    0.   69.06 71.91  0.
+ 12.24]
+[12/02 14:29:35] S3DIS INFO: Test [6]/[68] cloud
+[12/02 14:30:49] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 96.76 96.20 80.23, 
+iou per cls is: [ 98.11  99.33  94.7    0.     0.   100.    53.07 100.   100.   100.
+ 100.   100.    97.78]
+[12/02 14:30:49] S3DIS INFO: Test [7]/[68] cloud
+[12/02 14:31:27] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 95.76 94.10 62.80, 
+iou per cls is: [ 96.79  98.8   93.79   0.     0.   100.    27.07 100.   100.   100.
+ 100.     0.     0.  ]
+[12/02 14:31:27] S3DIS INFO: Test [8]/[68] cloud
+[12/02 14:32:05] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.00 97.00 88.62, 
+iou per cls is: [ 97.95  99.04  96.64 100.     0.   100.    72.86 100.   100.   100.
+ 100.   100.    85.56]
+[12/02 14:32:05] S3DIS INFO: Test [9]/[68] cloud
+[12/02 14:33:34] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 88.07 90.33 45.33, 
+iou per cls is: [ 98.3   98.81  86.16   0.     0.    16.7   22.82   0.   100.   100.
+   0.     0.    66.47]
+[12/02 14:33:34] S3DIS INFO: Test [10]/[68] cloud
+[12/02 14:33:58] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 90.55 93.31 61.55, 
+iou per cls is: [ 97.27  98.68  88.43   0.     0.   100.    46.99 100.   100.   100.
+   0.     0.    68.78]
+[12/02 14:33:58] S3DIS INFO: Test [11]/[68] cloud
+[12/02 14:35:39] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 84.60 80.29 43.40, 
+iou per cls is: [ 97.57  97.99  74.43   0.     0.06   2.59  32.18   0.     0.   100.
+   0.   100.    59.33]
+[12/02 14:35:39] S3DIS INFO: Test [12]/[68] cloud
+[12/02 14:52:17] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 87.48 93.79 38.51, 
+iou per cls is: [ 94.52  98.83  77.93   0.     0.     0.    43.48   0.     0.   100.
+   0.     0.    85.88]
+[12/02 14:52:17] S3DIS INFO: Test [13]/[68] cloud
+[12/02 14:53:22] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 94.30 91.40 44.75, 
+iou per cls is: [ 97.63  98.11  92.91 100.     0.   100.    11.62   0.     0.     0.
+   0.     0.    81.51]
+[12/02 14:53:22] S3DIS INFO: Test [14]/[68] cloud
+[12/02 14:54:08] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 94.29 83.96 52.79, 
+iou per cls is: [ 97.95  99.3   95.18   0.   100.   100.    76.07   0.     0.    25.65
+  92.17   0.     0.  ]
+[12/02 14:54:08] S3DIS INFO: Test [15]/[68] cloud
+[12/02 14:59:55] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 95.84 86.05 44.08, 
+iou per cls is: [ 98.81  99.75  94.22   0.     0.   100.    67.16   0.     0.     3.13
+  55.63   0.    54.33]
+[12/02 14:59:55] S3DIS INFO: Test [16]/[68] cloud
+[12/02 15:00:35] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 95.20 96.59 71.75, 
+iou per cls is: [ 97.43  98.96  90.87   0.   100.     0.    73.76 100.   100.   100.
+ 100.     0.    71.79]
+[12/02 15:00:35] S3DIS INFO: Test [17]/[68] cloud
+[12/02 15:01:51] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 93.02 91.90 44.66, 
+iou per cls is: [ 98.36  99.13  89.43   0.     0.   100.    17.43   0.   100.     0.
+   0.     0.    76.29]
+[12/02 15:01:51] S3DIS INFO: Test [18]/[68] cloud
+[12/02 15:02:06] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 90.87 85.16 53.36, 
+iou per cls is: [ 96.96  99.38  85.79   0.     0.     0.    10.89 100.   100.   100.
+ 100.     0.     0.68]
+[12/02 15:02:06] S3DIS INFO: Test [19]/[68] cloud
+[12/02 15:03:27] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 94.52 82.21 65.03, 
+iou per cls is: [ 89.28  98.74  91.13   0.     0.03   6.    68.98 100.   100.   100.
+   0.   100.    91.28]
+[12/02 15:03:27] S3DIS INFO: Test [20]/[68] cloud
+[12/02 15:04:26] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 93.68 92.92 37.43, 
+iou per cls is: [98.32 97.8  90.78  0.    0.    0.    0.   84.05 88.63  0.    0.    0.
+ 27.07]
+[12/02 15:04:26] S3DIS INFO: Test [21]/[68] cloud
+[12/02 15:04:59] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 85.78 85.19 62.87, 
+iou per cls is: [97.05 98.41 52.66  0.   31.61 62.13 84.11 91.78 95.42  0.   91.88 58.02
+ 54.19]
+[12/02 15:04:59] S3DIS INFO: Test [22]/[68] cloud
+[12/02 15:05:30] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 90.91 88.18 75.15, 
+iou per cls is: [ 98.53  98.45  70.1    0.    37.22  85.47  72.53  77.94  95.28 100.
+  92.42  91.39  57.58]
+[12/02 15:05:30] S3DIS INFO: Test [23]/[68] cloud
+[12/02 15:06:06] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 93.62 91.44 68.32, 
+iou per cls is: [96.44 97.87 77.26  0.   28.67 62.62 97.1  76.34 90.64  0.   94.23 85.44
+ 81.5 ]
+[12/02 15:06:06] S3DIS INFO: Test [24]/[68] cloud
+[12/02 15:06:42] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 87.93 88.51 65.85, 
+iou per cls is: [ 97.25  96.15  68.18   0.    50.7   67.42  57.18  85.98  85.63 100.
+  87.9    0.    59.63]
+[12/02 15:06:42] S3DIS INFO: Test [25]/[68] cloud
+[12/02 15:07:34] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 84.64 82.90 60.03, 
+iou per cls is: [98.23 97.83 53.63  0.   30.2  63.38 38.78 83.99 93.3   0.   88.12 81.74
+ 51.24]
+[12/02 15:07:34] S3DIS INFO: Test [26]/[68] cloud
+[12/02 15:08:56] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 83.25 82.95 59.45, 
+iou per cls is: [96.15 97.01 61.2   0.   26.99 41.56 78.19 65.88 88.53  0.   74.17 82.64
+ 60.57]
+[12/02 15:08:56] S3DIS INFO: Test [27]/[68] cloud
+[12/02 15:10:23] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 87.77 85.82 72.38, 
+iou per cls is: [ 96.82  98.19  68.4    0.    39.43  30.08  83.74  88.88  94.82 100.
+  87.52  82.23  70.79]
+[12/02 15:10:23] S3DIS INFO: Test [28]/[68] cloud
+[12/02 15:10:56] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 92.30 87.92 67.75, 
+iou per cls is: [ 98.61  98.23  87.88   0.    70.84 100.    96.2   82.13  89.45   0.
+  36.98  56.66  63.73]
+[12/02 15:10:56] S3DIS INFO: Test [29]/[68] cloud
+[12/02 15:11:42] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 84.34 89.25 53.97, 
+iou per cls is: [ 97.23  98.48  78.4    0.     0.     0.    71.44  45.51 100.   100.
+  56.89   0.    53.6 ]
+[12/02 15:11:42] S3DIS INFO: Test [30]/[68] cloud
+[12/02 15:13:01] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 92.94 87.75 67.97, 
+iou per cls is: [ 99.1   98.55  86.48   0.    33.48 100.    87.32  94.74  91.72   0.
+  87.92  37.01  67.28]
+[12/02 15:13:01] S3DIS INFO: Test [31]/[68] cloud
+[12/02 15:15:27] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 87.05 86.91 66.75, 
+iou per cls is: [ 94.17  98.97  76.13   0.     0.   100.    48.83  86.62  93.68 100.
+  62.39  62.15  44.82]
+[12/02 15:15:27] S3DIS INFO: Test [32]/[68] cloud
+[12/02 15:16:07] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 93.03 88.63 76.89, 
+iou per cls is: [ 97.26  98.    77.15   0.    27.91  79.65  93.7   84.45  95.45 100.
+  92.54  77.49  75.98]
+[12/02 15:16:07] S3DIS INFO: Test [33]/[68] cloud
+[12/02 15:16:22] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 84.62 84.16 46.38, 
+iou per cls is: [97.75 96.75 75.85  0.   44.13  0.   24.52 88.13 87.96  0.   53.59  0.
+ 34.2 ]
+[12/02 15:16:22] S3DIS INFO: Test [34]/[68] cloud
+[12/02 15:19:48] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 90.74 89.33 66.58, 
+iou per cls is: [ 98.52  99.39  83.97   0.    67.89   0.    77.06  92.6   92.31 100.
+  33.67  84.6   35.56]
+[12/02 15:19:48] S3DIS INFO: Test [35]/[68] cloud
+[12/02 15:20:22] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 88.91 86.17 72.15, 
+iou per cls is: [ 96.1   97.96  73.31   0.    28.22  51.7   92.05  81.54  90.65 100.
+  86.45  81.25  58.74]
+[12/02 15:20:22] S3DIS INFO: Test [36]/[68] cloud
+[12/02 15:21:06] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 90.55 90.81 65.55, 
+iou per cls is: [97.06 96.69 80.14  0.   24.45 72.72 67.95 86.78 88.68  0.   90.69 68.5
+ 78.5 ]
+[12/02 15:21:06] S3DIS INFO: Test [37]/[68] cloud
+[12/02 15:23:22] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 80.77 80.26 62.25, 
+iou per cls is: [94.73 93.73 53.42  0.   44.57 66.51 62.11 78.06 85.04 57.18 61.12 68.75
+ 43.98]
+[12/02 15:23:22] S3DIS INFO: Test [38]/[68] cloud
+[12/02 15:23:42] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 87.13 87.71 66.82, 
+iou per cls is: [ 96.3   95.58  75.16   0.     0.    83.65  65.66  66.13  98.12 100.
+  83.33  49.55  55.14]
+[12/02 15:23:42] S3DIS INFO: Test [39]/[68] cloud
+[12/02 15:24:13] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 82.65 78.24 55.82, 
+iou per cls is: [92.53 96.88 78.58  0.   65.06 56.74 60.11 75.69 90.05  0.   59.61 10.56
+ 39.8 ]
+[12/02 15:24:13] S3DIS INFO: Test [40]/[68] cloud
+[12/02 15:24:45] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 91.04 88.92 69.68, 
+iou per cls is: [96.08 98.89 81.71  0.   55.33 83.45 79.56 86.89 97.36  0.   86.74 85.18
+ 54.66]
+[12/02 15:24:45] S3DIS INFO: Test [41]/[68] cloud
+[12/02 15:25:17] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 92.66 91.55 79.64, 
+iou per cls is: [ 96.13  99.04  85.55   0.    88.93  91.81  75.71  80.27  94.27 100.
+  88.62  81.66  53.37]
+[12/02 15:25:17] S3DIS INFO: Test [42]/[68] cloud
+[12/02 15:27:46] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 77.86 81.50 63.72, 
+iou per cls is: [ 96.2   97.68  53.39   0.    58.71  60.73  72.74  83.97  65.38 100.
+  27.61  74.45  37.45]
+[12/02 15:27:46] S3DIS INFO: Test [43]/[68] cloud
+[12/02 15:28:16] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 89.56 89.86 61.94, 
+iou per cls is: [97.34 98.15 64.71  0.    0.   78.03 66.49 84.69 95.66  0.   90.19 80.9
+ 49.1 ]
+[12/02 15:28:16] S3DIS INFO: Test [44]/[68] cloud
+[12/02 15:28:30] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.46 96.36 85.96, 
+iou per cls is: [ 94.74  97.07  94.54 100.     0.   100.    94.25  87.38  91.13 100.
+  94.83  88.26  75.26]
+[12/02 15:28:30] S3DIS INFO: Test [45]/[68] cloud
+[12/02 15:29:14] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 85.86 87.23 58.70, 
+iou per cls is: [95.03 99.22 56.47  0.   31.81 74.61 83.54 88.6  94.87  0.   83.9   0.
+ 55.1 ]
+[12/02 15:29:14] S3DIS INFO: Test [46]/[68] cloud
+[12/02 15:29:46] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 86.96 86.70 58.27, 
+iou per cls is: [95.43 98.89 72.68  0.   36.44 88.5  76.96 81.91 78.38  0.   65.33  0.
+ 62.94]
+[12/02 15:29:46] S3DIS INFO: Test [47]/[68] cloud
+[12/02 15:30:34] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 90.99 87.14 67.56, 
+iou per cls is: [95.3  99.67 80.33  0.   22.15 84.36 82.87 92.19 94.17  0.   82.98 93.33
+ 50.95]
+[12/02 15:30:34] S3DIS INFO: Test [48]/[68] cloud
+[12/02 15:31:25] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 79.74 81.82 57.96, 
+iou per cls is: [95.   97.85 53.25  0.   41.59 60.27 66.41 65.68 84.13  0.   69.5  74.89
+ 44.91]
+[12/02 15:31:25] S3DIS INFO: Test [49]/[68] cloud
+[12/02 15:32:10] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 95.78 95.69 70.16, 
+iou per cls is: [ 98.12  96.22  92.09   0.     0.   100.    90.76  88.45  91.25   0.
+  90.09  87.01  78.02]
+[12/02 15:32:10] S3DIS INFO: Test [50]/[68] cloud
+[12/02 15:33:29] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.33 93.05 64.64, 
+iou per cls is: [ 98.6   96.97  90.88   0.     0.   100.    92.21  79.37  95.78   0.
+  48.25  92.26  45.98]
+[12/02 15:33:29] S3DIS INFO: Test [51]/[68] cloud
+[12/02 15:39:45] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 81.25 80.58 51.04, 
+iou per cls is: [71.68 98.25 77.85  0.   35.31  0.   49.5  73.91 80.55  0.   63.04 65.02
+ 48.36]
+[12/02 15:39:45] S3DIS INFO: Test [52]/[68] cloud
+[12/02 15:47:21] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 69.51 80.04 43.29, 
+iou per cls is: [67.32 96.99 51.68  0.   27.83  0.   70.38 50.83 65.13 40.09 51.65  0.
+ 40.9 ]
+[12/02 15:47:21] S3DIS INFO: Test [53]/[68] cloud
+[12/02 15:48:06] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 83.72 80.51 51.46, 
+iou per cls is: [93.33 97.68 74.67  0.    0.    0.   71.07 79.15 82.57  0.   43.25 87.43
+ 39.85]
+[12/02 15:48:06] S3DIS INFO: Test [54]/[68] cloud
+[12/02 15:48:41] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 93.78 90.51 70.22, 
+iou per cls is: [97.19 98.   81.18  0.   26.39 79.94 91.98 93.63 95.14  0.   93.71 89.06
+ 66.6 ]
+[12/02 15:48:41] S3DIS INFO: Test [55]/[68] cloud
+[12/02 15:55:44] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 83.10 85.19 49.24, 
+iou per cls is: [94.73 96.52 77.15  0.   34.85  0.   48.13 67.76 70.54  0.   55.36 44.72
+ 50.31]
+[12/02 15:55:44] S3DIS INFO: Test [56]/[68] cloud
+[12/02 15:57:47] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 89.04 89.90 65.66, 
+iou per cls is: [95.79 97.83 74.06  0.   56.29 73.42 86.38 82.36 75.23  0.   64.14 83.12
+ 64.9 ]
+[12/02 15:57:47] S3DIS INFO: Test [57]/[68] cloud
+[12/02 15:58:35] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 89.77 89.43 68.64, 
+iou per cls is: [ 97.44  97.07  72.71   0.    46.18  62.93  77.17  87.13  95.82 100.
+  86.54   0.    69.26]
+[12/02 15:58:35] S3DIS INFO: Test [58]/[68] cloud
+[12/02 15:59:02] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 93.46 94.66 67.95, 
+iou per cls is: [ 96.52  97.75  84.93   0.     0.    80.48  78.26  93.59  97.93 100.
+  85.06   0.    68.88]
+[12/02 15:59:02] S3DIS INFO: Test [59]/[68] cloud
+[12/02 15:59:32] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 89.90 88.80 61.15, 
+iou per cls is: [97.37 97.54 67.63  0.    0.   56.49 72.22 83.14 80.36  0.   90.45 88.69
+ 61.06]
+[12/02 15:59:32] S3DIS INFO: Test [60]/[68] cloud
+[12/02 16:00:18] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 90.62 82.64 70.73, 
+iou per cls is: [ 98.47  97.65  65.84   0.     1.88  83.41  38.28  86.36  96.52 100.
+  90.76  90.06  70.25]
+[12/02 16:00:18] S3DIS INFO: Test [61]/[68] cloud
+[12/02 16:01:07] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 93.29 89.58 67.26, 
+iou per cls is: [96.71 96.37 82.56  0.   37.86 56.39 91.61 93.48 94.85  0.   95.4  83.99
+ 45.2 ]
+[12/02 16:01:07] S3DIS INFO: Test [62]/[68] cloud
+[12/02 16:01:41] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 91.32 91.73 71.68, 
+iou per cls is: [ 95.92  95.08  85.12   0.     0.    79.51  87.22  67.53  89.29  75.67
+  91.67 100.    64.89]
+[12/02 16:01:41] S3DIS INFO: Test [63]/[68] cloud
+[12/02 16:02:04] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 71.87 92.55 29.78, 
+iou per cls is: [ 94.53  97.19  80.77   0.     0.     0.     0.     0.     0.   100.
+   0.     0.    14.65]
+[12/02 16:02:04] S3DIS INFO: Test [64]/[68] cloud
+[12/02 16:02:28] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 74.07 75.61 38.70, 
+iou per cls is: [ 57.2   95.65  69.06   0.01  38.46   0.    47.84   0.     0.   100.
+  65.42   0.    29.44]
+[12/02 16:02:28] S3DIS INFO: Test [65]/[68] cloud
+[12/02 16:03:10] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 63.91 83.91 39.30, 
+iou per cls is: [ 13.88  96.96  72.12   0.     0.     0.    51.82   0.   100.     0.
+  47.57 100.    28.57]
+[12/02 16:03:10] S3DIS INFO: Test [66]/[68] cloud
+[12/02 16:03:13] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 79.21 87.71 31.38, 
+iou per cls is: [  2.    99.71  72.5  100.     0.     0.    76.06   0.     0.     0.
+   0.     0.    57.69]
+[12/02 16:03:13] S3DIS INFO: Test [67]/[68] cloud
+[12/02 16:03:38] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 80.69 86.01 36.35, 
+iou per cls is: [75.9  98.33 81.53  0.    0.    0.   32.98 73.52 63.25  0.    0.    0.
+ 47.06]
+[12/02 16:03:38] S3DIS INFO: Best ckpt @E52,  test_oa , test_macc, test_miou: 87.03 70.76 62.59, 
+iou per cls is: [91.46 98.19 78.49  0.   29.59 52.06 61.38 80.72 85.57 50.67 70.22 63.92
+ 51.45]

Pretrained_Models/PNt_SEG_original/PNt_SEG_original_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointnext-s,5,87.03,70.76,62.59,91.46,98.19,78.49,0.00,29.59,52.06,61.38,80.72,85.57,50.67,70.22,63.92,51.45,52,/workspace/FractalCloud/Model_logs/PNt_SEG_original,-

Pretrained_Models/PNt_SEG_original/checkpoint/s3dis-pointnext-s_ckpt_best_626.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c63a3a917677edc26dcd8ea65f81c6f3f9b42fc6232a0718ca838d7780bc487
+size 9606497

Pretrained_Models/PVr_SEG_fractal/PVr_SEG_fractal_25620251203-085834-6kzWDEvGCA9ERzfW9aa3qf.log

@@ -0,0 +1,1236 @@
+[12/03 08:58:34] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 4305
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PVr_SEG_fractal_256
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/checkpoint/s3dis-pointvector-l_ckpt_best_7033.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudRotation', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 8
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointVectorEncoder
+    blocks: [1, 3, 5, 3, 3]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 1
+    sa_use_res: False
+    width: 32
+    in_channels: 4
+    expansion: 4
+    radius: 0.1
+    nsample: 32
+    flag: 1
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointVectorDecoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
+      norm: bn
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointvector-l
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256
+run_name: PVr_SEG_fractal_256
+ckpt_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/code
+log_path: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/PVr_SEG_fractal_25620251203-085834-6kzWDEvGCA9ERzfW9aa3qf.log
+cfg_path: /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/cfg.yaml
+[12/03 08:58:35] S3DIS INFO: radius: [[0.1], [0.1, 0.2, 0.2], [0.2, 0.4, 0.4, 0.4, 0.4], [0.4, 0.8, 0.8], [0.8, 1.6, 1.6]],
+ nsample: [[32], [32, 32, 32], [32, 32, 32, 32, 32], [32, 32, 32], [32, 32, 32]]
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 8
+[12/03 08:58:35] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 8
+[12/03 08:58:41] S3DIS INFO: BaseSeg(
+  (encoder): PointVectorEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(4, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), groups=64, bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), groups=64, bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (3): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (4): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(131, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), groups=256, bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), groups=256, bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(1536, 512, kernel_size=(1,), stride=(1,), groups=512, bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(1536, 512, kernel_size=(1,), stride=(1,), groups=512, bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+    )
+  )
+  (decoder): PointVectorDecoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/03 08:58:41] S3DIS INFO: Number of params: 4.2152 M
+[12/03 08:58:41] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
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+      "decoder.decoder.0.0.convs.0.1.weight",
+      "decoder.decoder.0.0.convs.0.1.bias",
+      "decoder.decoder.0.0.convs.1.1.weight",
+      "decoder.decoder.0.0.convs.1.1.bias",
+      "decoder.decoder.1.0.convs.0.1.weight",
+      "decoder.decoder.1.0.convs.0.1.bias",
+      "decoder.decoder.1.0.convs.1.1.weight",
+      "decoder.decoder.1.0.convs.1.1.bias",
+      "decoder.decoder.2.0.convs.0.1.weight",
+      "decoder.decoder.2.0.convs.0.1.bias",
+      "decoder.decoder.2.0.convs.1.1.weight",
+      "decoder.decoder.2.0.convs.1.1.bias",
+      "decoder.decoder.3.0.convs.0.1.weight",
+      "decoder.decoder.3.0.convs.0.1.bias",
+      "decoder.decoder.3.0.convs.1.1.weight",
+      "decoder.decoder.3.0.convs.1.1.bias",
+      "head.head.0.1.weight",
+      "head.head.0.1.bias",
+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[12/03 08:58:41] S3DIS INFO: 
+Totally 68 samples in val set
+[12/03 08:58:41] S3DIS INFO: length of validation dataset: 68
+[12/03 08:58:41] S3DIS INFO: number of classes of the dataset: 13
+[12/03 08:58:42] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256/checkpoint/s3dis-pointvector-l_ckpt_best_704.pth
+[12/03 08:58:42] S3DIS INFO: ckpts @ 71 epoch( {'best_val': 68.80073547363281} )
+[12/03 08:58:42] S3DIS INFO: length of test dataset: 68
+[12/03 08:58:42] S3DIS INFO: Test [0]/[68] cloud
+[12/03 09:04:42] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 92.29 97.24 80.18, 
+iou per cls is: [ 97.64  99.13  81.19 100.   100.     0.    97.79   0.   100.   100.
+ 100.   100.    66.59]
+[12/03 09:04:42] S3DIS INFO: Test [1]/[68] cloud
+[12/03 09:09:19] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 92.53 97.38 87.95, 
+iou per cls is: [ 95.4   99.15  82.14 100.   100.   100.    97.94   0.   100.   100.
+ 100.   100.    68.78]
+[12/03 09:09:19] S3DIS INFO: Test [2]/[68] cloud
+[12/03 09:17:18] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 91.52 90.95 72.16, 
+iou per cls is: [ 96.95  98.72  82.59   0.    55.89  70.35  94.2   94.58  96.08 100.
+   0.    95.98  52.74]
+[12/03 09:17:18] S3DIS INFO: Test [3]/[68] cloud
+[12/03 09:59:16] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 94.66 93.69 90.14, 
+iou per cls is: [ 98.8   97.35  89.89 100.    70.08 100.    95.9   95.22  95.27  99.85
+  76.    83.3   70.18]
+[12/03 09:59:16] S3DIS INFO: Test [4]/[68] cloud
+[12/03 10:17:11] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 91.68 89.68 70.64, 
+iou per cls is: [ 95.65  99.57  79.8    0.    85.05  71.54  79.1   74.6   95.72 100.
+   0.    79.83  57.48]
+[12/03 10:17:11] S3DIS INFO: Test [5]/[68] cloud
+[12/03 12:01:47] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 79.68 76.97 33.52, 
+iou per cls is: [90.4  98.79 48.68  0.    0.45  0.   20.13  0.    0.   87.26 63.15  0.
+ 26.88]
+[12/03 12:01:47] S3DIS INFO: Test [6]/[68] cloud
+[12/03 12:14:49] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 98.78 98.80 90.76, 
+iou per cls is: [ 98.23  99.35  97.82   0.   100.   100.    85.31 100.   100.   100.
+ 100.   100.    99.12]
+[12/03 12:14:49] S3DIS INFO: Test [7]/[68] cloud
+[12/03 12:22:13] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 98.22 98.24 90.26, 
+iou per cls is: [ 96.3   98.81  97.08 100.   100.   100.    81.2  100.   100.   100.
+ 100.   100.     0.  ]
+[12/03 12:22:13] S3DIS INFO: Test [8]/[68] cloud
+[12/03 12:29:58] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.44 97.35 96.89, 
+iou per cls is: [ 97.59  99.17  97.33 100.   100.   100.    83.99 100.   100.   100.
+ 100.   100.    81.54]
+[12/03 12:29:58] S3DIS INFO: Test [9]/[68] cloud
+[12/03 12:45:20] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 87.76 90.84 69.15, 
+iou per cls is: [ 98.56  99.35  86.53   0.     0.     0.64  18.2  100.   100.   100.
+ 100.   100.    95.61]
+[12/03 12:45:20] S3DIS INFO: Test [10]/[68] cloud
+[12/03 12:49:19] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 93.45 94.92 71.10, 
+iou per cls is: [ 99.    98.92  91.32 100.     0.   100.    52.96 100.   100.   100.
+   0.     0.    82.08]
+[12/03 12:49:19] S3DIS INFO: Test [11]/[68] cloud
+[12/03 13:01:08] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 85.99 85.73 46.57, 
+iou per cls is: [ 97.57  99.07  75.26   0.    24.58   0.    28.22   0.     0.   100.
+   0.   100.    80.71]
+[12/03 13:01:08] S3DIS INFO: Test [12]/[68] cloud
+[12/03 14:49:19] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 88.04 94.35 39.77, 
+iou per cls is: [ 94.04  99.02  79.18   0.     0.     0.    50.27   0.     0.   100.
+   0.     0.    94.47]
+[12/03 14:49:19] S3DIS INFO: Test [13]/[68] cloud
+[12/03 14:56:41] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 95.38 92.05 60.72, 
+iou per cls is: [ 98.4   98.12  94.1  100.     0.     0.    14.05 100.   100.   100.
+   0.     0.    84.66]
+[12/03 14:56:41] S3DIS INFO: Test [14]/[68] cloud
+[12/03 15:01:58] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 96.86 91.31 74.16, 
+iou per cls is: [ 97.59  99.4   95.64 100.   100.   100.    80.59   0.     0.    85.01
+  80.15 100.    25.76]
+[12/03 15:01:58] S3DIS INFO: Test [15]/[68] cloud
+[12/03 15:38:57] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 97.76 94.47 76.58, 
+iou per cls is: [ 98.99  99.49  96.59 100.   100.   100.    80.07   0.     0.    82.27
+  70.59 100.    67.48]
+[12/03 15:38:57] S3DIS INFO: Test [16]/[68] cloud
+[12/03 15:43:19] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 95.63 96.58 95.34, 
+iou per cls is: [ 96.02  99.16  92.35 100.   100.   100.    81.08 100.   100.   100.
+ 100.   100.    70.8 ]
+[12/03 15:43:19] S3DIS INFO: Test [17]/[68] cloud
+[12/03 15:51:05] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 93.93 96.11 72.07, 
+iou per cls is: [ 98.73  99.33  89.75 100.     0.   100.    76.16 100.   100.   100.
+   0.     0.    72.99]
+[12/03 15:51:05] S3DIS INFO: Test [18]/[68] cloud
+[12/03 15:52:54] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 97.04 91.49 90.94, 
+iou per cls is: [ 96.75  99.51  94.41 100.   100.   100.    84.9  100.   100.   100.
+ 100.   100.     6.69]
+[12/03 15:52:54] S3DIS INFO: Test [19]/[68] cloud
+[12/03 16:01:46] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 96.06 85.36 67.41, 
+iou per cls is: [ 94.47  98.83  94.19   0.    32.57   0.    76.83 100.   100.   100.
+   0.   100.    79.42]
+[12/03 16:01:46] S3DIS INFO: Test [20]/[68] cloud
+[12/03 16:09:00] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 94.51 93.57 69.38, 
+iou per cls is: [ 98.53  97.92  92.07 100.     0.   100.     0.    90.    94.03 100.
+ 100.     0.    29.43]
+[12/03 16:09:00] S3DIS INFO: Test [21]/[68] cloud
+[12/03 16:12:49] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 93.04 90.43 71.49, 
+iou per cls is: [97.71 98.48 71.52  0.   58.25 83.36 95.24 91.4  96.32  0.   97.8  78.08
+ 61.16]
+[12/03 16:12:49] S3DIS INFO: Test [22]/[68] cloud
+[12/03 16:16:32] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 93.87 89.95 78.38, 
+iou per cls is: [ 98.25  98.76  82.86   0.    29.71  91.07  97.21  70.97  94.98 100.
+  93.57  92.75  68.79]
+[12/03 16:16:32] S3DIS INFO: Test [23]/[68] cloud
+[12/03 16:20:28] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 96.23 88.80 77.48, 
+iou per cls is: [ 97.71  98.32  84.29   0.     4.97  81.73  98.11  76.45  89.43 100.
+  97.51  93.85  84.83]
+[12/03 16:20:28] S3DIS INFO: Test [24]/[68] cloud
+[12/03 16:24:25] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 91.48 90.20 69.94, 
+iou per cls is: [ 97.48  97.01  76.96   0.    39.14  80.47  92.49  85.42  84.1    0.
+  92.76 100.    63.45]
+[12/03 16:24:25] S3DIS INFO: Test [25]/[68] cloud
+[12/03 16:29:55] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 90.76 89.42 76.60, 
+iou per cls is: [ 98.35  98.1   68.24   0.    39.83  82.65  87.03  84.17  94.55 100.
+  93.2   87.35  62.3 ]
+[12/03 16:29:55] S3DIS INFO: Test [26]/[68] cloud
+[12/03 16:38:35] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 86.72 84.66 71.04, 
+iou per cls is: [ 95.9   98.3   72.07   0.     2.18  54.13  94.39  70.29  91.42 100.
+  81.5   96.19  67.17]
+[12/03 16:38:35] S3DIS INFO: Test [27]/[68] cloud
+[12/03 16:47:58] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 89.58 89.19 76.57, 
+iou per cls is: [ 96.39  98.49  73.61   0.    21.68  78.33  91.05  85.99  97.01 100.
+  89.19  94.06  69.54]
+[12/03 16:47:58] S3DIS INFO: Test [28]/[68] cloud
+[12/03 16:51:45] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 90.59 80.66 60.96, 
+iou per cls is: [ 98.41  98.35  87.02   0.    37.     0.    96.67  87.04  94.13 100.
+  16.79  21.34  55.71]
+[12/03 16:51:45] S3DIS INFO: Test [29]/[68] cloud
+[12/03 16:56:40] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 88.76 92.62 65.47, 
+iou per cls is: [ 97.21  98.44  96.23   0.     0.   100.    96.02  49.88   0.   100.
+  61.95 100.    51.34]
+[12/03 16:56:40] S3DIS INFO: Test [30]/[68] cloud
+[12/03 17:05:14] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 97.29 93.69 76.09, 
+iou per cls is: [ 99.26  98.66  95.64   0.    57.62   0.    93.08  97.65  93.31 100.
+  94.82  82.58  76.58]
+[12/03 17:05:14] S3DIS INFO: Test [31]/[68] cloud
+[12/03 17:20:20] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 86.24 92.01 63.50, 
+iou per cls is: [ 94.29  98.89  76.15   0.     0.     0.    91.24  87.8   93.15 100.
+  54.71  87.59  41.63]
+[12/03 17:20:20] S3DIS INFO: Test [32]/[68] cloud
+[12/03 17:24:34] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 94.64 88.84 85.55, 
+iou per cls is: [ 98.28  98.17  81.07 100.     0.02  86.49  96.95  89.72  95.54 100.
+  94.08  89.72  82.15]
+[12/03 17:24:34] S3DIS INFO: Test [33]/[68] cloud
+[12/03 17:26:36] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 89.94 92.40 79.34, 
+iou per cls is: [ 97.84  97.17  82.26   0.    83.4  100.    85.71  92.72  91.05 100.
+  53.14 100.    48.17]
+[12/03 17:26:36] S3DIS INFO: Test [34]/[68] cloud
+[12/03 17:47:00] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 91.10 90.52 76.36, 
+iou per cls is: [ 98.59  99.4   85.48   0.    68.12 100.    98.7   88.67  87.9  100.
+  33.12  95.92  36.76]
+[12/03 17:47:00] S3DIS INFO: Test [35]/[68] cloud
+[12/03 17:50:52] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 93.51 89.02 77.92, 
+iou per cls is: [ 96.57  98.3   80.45   0.    21.46  77.7   96.61  82.75  91.17 100.
+  96.39  89.99  81.64]
+[12/03 17:50:52] S3DIS INFO: Test [36]/[68] cloud
+[12/03 17:55:45] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 93.06 91.75 79.42, 
+iou per cls is: [ 97.42  97.24  81.65   0.    44.29  71.79  97.69  88.28  91.7  100.
+  93.89  91.81  76.77]
+[12/03 17:55:45] S3DIS INFO: Test [37]/[68] cloud
+[12/03 18:09:35] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 81.18 82.18 65.76, 
+iou per cls is: [96.65 94.65 54.    0.   36.74 68.43 87.54 74.   85.49 71.35 60.76 80.62
+ 44.59]
+[12/03 18:09:35] S3DIS INFO: Test [38]/[68] cloud
+[12/03 18:12:12] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 90.23 90.49 78.33, 
+iou per cls is: [ 96.31  95.67  81.47   0.   100.    82.64  96.43  72.67  97.91 100.
+  85.68  46.65  62.84]
+[12/03 18:12:12] S3DIS INFO: Test [39]/[68] cloud
+[12/03 18:15:46] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 86.25 85.35 70.72, 
+iou per cls is: [ 95.46  97.23  85.1    0.    62.49  86.79  87.81  69.27  93.45 100.
+  64.07  34.9   42.76]
+[12/03 18:15:46] S3DIS INFO: Test [40]/[68] cloud
+[12/03 18:19:29] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 92.69 89.99 79.16, 
+iou per cls is: [ 96.07  99.35  83.38   0.    39.23  85.6   95.42  89.27  96.85 100.
+  90.99  89.22  63.7 ]
+[12/03 18:19:29] S3DIS INFO: Test [41]/[68] cloud
+[12/03 18:23:20] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 93.63 91.18 79.91, 
+iou per cls is: [ 97.17  98.95  88.15   0.    66.18  90.62  95.03  77.49  93.94 100.
+  88.66  87.85  54.85]
+[12/03 18:23:20] S3DIS INFO: Test [42]/[68] cloud
+[12/03 18:37:54] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 79.16 82.24 68.39, 
+iou per cls is: [ 96.76  97.71  56.82   0.    35.01  69.38  95.47  86.74  95.42 100.
+  25.99  92.09  37.63]
+[12/03 18:37:54] S3DIS INFO: Test [43]/[68] cloud
+[12/03 18:41:01] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 93.10 93.88 82.62, 
+iou per cls is: [ 97.87  98.71  74.73   0.   100.    84.26  94.22  82.49  95.61 100.
+  93.57  94.78  57.79]
+[12/03 18:41:01] S3DIS INFO: Test [44]/[68] cloud
+[12/03 18:42:41] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.46 96.55 93.80, 
+iou per cls is: [ 94.18  97.07  96.29 100.   100.   100.    96.01  84.52  94.64 100.
+  92.48  96.17  68.08]
+[12/03 18:42:41] S3DIS INFO: Test [45]/[68] cloud
+[12/03 18:47:27] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 88.07 89.77 75.72, 
+iou per cls is: [ 97.62  99.46  64.28   0.    24.39  85.93  92.77  76.23  94.4  100.
+  82.66 100.    66.59]
+[12/03 18:47:27] S3DIS INFO: Test [46]/[68] cloud
+[12/03 18:51:04] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 92.43 90.59 79.50, 
+iou per cls is: [ 96.58  99.36  80.4    0.    28.57  91.88  95.38  84.07  90.66 100.
+  84.36 100.    82.21]
+[12/03 18:51:04] S3DIS INFO: Test [47]/[68] cloud
+[12/03 18:56:29] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 93.33 90.25 78.83, 
+iou per cls is: [ 95.58  99.69  84.18   0.    16.76  90.07  95.43  90.18  94.58 100.
+  90.66  95.45  72.23]
+[12/03 18:56:29] S3DIS INFO: Test [48]/[68] cloud
+[12/03 19:02:05] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 86.94 86.82 73.25, 
+iou per cls is: [ 95.35  97.09  71.61   0.    33.53  76.11  92.49  60.22  93.36 100.
+  80.14  94.35  58.02]
+[12/03 19:02:05] S3DIS INFO: Test [49]/[68] cloud
+[12/03 19:06:57] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 97.01 97.47 87.99, 
+iou per cls is: [ 98.51  96.99  94.88   0.   100.   100.    97.13  87.45  91.94 100.
+  92.6   96.68  87.68]
+[12/03 19:06:57] S3DIS INFO: Test [50]/[68] cloud
+[12/03 19:15:40] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.09 92.78 71.59, 
+iou per cls is: [ 98.47  96.24  94.58   0.   100.     0.    97.49  77.68  94.75 100.
+  41.84  94.71  34.96]
+[12/03 19:15:40] S3DIS INFO: Test [51]/[68] cloud
+[12/03 19:52:13] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 86.26 83.45 62.58, 
+iou per cls is: [ 89.7   98.69  82.15   0.     0.34 100.    86.51  73.06  83.8    0.
+  62.45  70.22  66.56]
+[12/03 19:52:13] S3DIS INFO: Test [52]/[68] cloud
+[12/03 20:36:44] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 79.79 85.25 54.16, 
+iou per cls is: [89.33 97.57 67.07  0.   43.28  0.   81.94 66.72 72.89 71.57 58.58  0.
+ 55.14]
+[12/03 20:36:44] S3DIS INFO: Test [53]/[68] cloud
+[12/03 20:41:22] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 91.40 85.06 80.90, 
+iou per cls is: [ 93.23  97.87  92.67   0.   100.   100.    93.61  89.51  92.97 100.
+  55.21  87.03  49.64]
+[12/03 20:41:22] S3DIS INFO: Test [54]/[68] cloud
+[12/03 20:44:57] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 95.66 92.02 81.51, 
+iou per cls is: [ 97.86  98.49  83.94   0.    31.26  85.02  95.38  93.79  96.48 100.
+  96.83  95.52  85.04]
+[12/03 20:44:57] S3DIS INFO: Test [55]/[68] cloud
+[12/03 21:25:50] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 92.60 91.36 86.31, 
+iou per cls is: [ 97.4   97.05  89.39 100.    80.55 100.    89.59  80.97  81.98 100.
+  81.72  59.04  64.34]
+[12/03 21:25:50] S3DIS INFO: Test [56]/[68] cloud
+[12/03 21:38:40] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 91.82 93.29 77.48, 
+iou per cls is: [ 97.2   98.43  71.02   0.    36.65  83.44  96.99  89.13  85.9  100.
+  83.32  88.08  77.05]
+[12/03 21:38:40] S3DIS INFO: Test [57]/[68] cloud
+[12/03 21:43:59] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 90.45 92.75 78.40, 
+iou per cls is: [ 97.5   97.1   73.02   0.    48.12  66.08  95.77  87.41  96.62 100.
+  86.74 100.    70.89]
+[12/03 21:43:59] S3DIS INFO: Test [58]/[68] cloud
+[12/03 21:46:52] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 95.56 97.03 71.26, 
+iou per cls is: [ 97.29  98.37  88.54   0.     0.    77.74  90.87  92.34  99.01 100.
+  95.51   0.    86.65]
+[12/03 21:46:52] S3DIS INFO: Test [59]/[68] cloud
+[12/03 21:50:05] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 93.90 93.43 74.43, 
+iou per cls is: [ 97.98  98.14  78.53   0.     0.    63.34  92.54  84.16  82.39 100.
+  96.42  95.59  78.57]
+[12/03 21:50:05] S3DIS INFO: Test [60]/[68] cloud
+[12/03 21:54:48] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 93.89 88.44 77.32, 
+iou per cls is: [ 98.48  98.43  75.71   0.     6.79  82.37  93.3   87.31  98.3  100.
+  94.26  93.51  76.7 ]
+[12/03 21:54:48] S3DIS INFO: Test [61]/[68] cloud
+[12/03 22:00:02] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 94.93 90.84 79.30, 
+iou per cls is: [ 98.41  96.41  82.78   0.    31.51  73.72  97.48  93.02  94.45 100.
+  96.1   93.92  73.12]
+[12/03 22:00:02] S3DIS INFO: Test [62]/[68] cloud
+[12/03 22:03:54] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 93.69 94.98 75.80, 
+iou per cls is: [ 96.24  96.64  87.45   0.     0.    79.18  97.58  76.41  96.99  85.51
+  93.14 100.    76.21]
+[12/03 22:03:54] S3DIS INFO: Test [63]/[68] cloud
+[12/03 22:06:38] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 73.16 92.89 45.89, 
+iou per cls is: [ 93.82  97.5   84.83   0.     0.   100.     0.     0.   100.   100.
+   0.     0.    20.44]
+[12/03 22:06:38] S3DIS INFO: Test [64]/[68] cloud
+[12/03 22:09:24] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 77.49 79.13 56.98, 
+iou per cls is: [ 94.44  95.79  74.48   0.     3.68   0.    74.99   0.   100.   100.
+  70.97 100.    26.41]
+[12/03 22:09:24] S3DIS INFO: Test [65]/[68] cloud
+[12/03 22:14:00] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 78.55 89.50 53.74, 
+iou per cls is: [ 40.09  96.94  81.73   0.     0.     0.    55.27 100.   100.   100.
+  75.69   0.    48.85]
+[12/03 22:14:00] S3DIS INFO: Test [66]/[68] cloud
+[12/03 22:14:26] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 84.50 93.87 68.83, 
+iou per cls is: [ 71.04  99.66  87.11 100.   100.   100.    79.11 100.     0.   100.
+   0.     0.    57.86]
+[12/03 22:14:26] S3DIS INFO: Test [67]/[68] cloud
+[12/03 22:17:31] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 83.34 87.60 70.09, 
+iou per cls is: [ 89.33  98.58  91.37 100.   100.   100.    50.13  63.32  86.68 100.
+   0.     0.    31.74]
+[12/03 22:17:31] S3DIS INFO: Best ckpt @E71,  test_oa , test_macc, test_miou: 90.30 76.58 70.33, 
+iou per cls is: [95.43 98.48 83.74  0.   28.55 60.5  74.85 82.3  90.99 82.8  75.69 80.58
+ 60.44]

Pretrained_Models/PVr_SEG_fractal/PVr_SEG_fractal_256_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointvector-l,5,90.30,76.58,70.33,95.43,98.48,83.74,0.00,28.55,60.50,74.85,82.30,90.99,82.80,75.69,80.58,60.44,71,/workspace/FractalCloud/Model_logs/PVr_SEG_fractal_256,-

Pretrained_Models/PVr_SEG_fractal/checkpoint/s3dis-pointvector-l_ckpt_best_7033.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0297a47f9821b62f62abc1949c96171553bc3e678e7e0e62b65a208da2410ec
+size 51014805

Pretrained_Models/PVr_SEG_original/PVr_SEG_original20251202-210507-PDAW9VGM4gPZxmtaxRzEuu.log

@@ -0,0 +1,1236 @@
+[12/02 21:05:07] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 8462
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['test']
+  name: PVr_SEG_original
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: test
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: /workspace/FractalCloud/Model_logs/PVr_SEG_original/checkpoint/s3dis-pointvector-l_ckpt_best_708.pth
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudRotation', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: /workspace/PointNeXt/data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 8
+val_batch_size: 1
+dataloader:
+  num_workers: 8
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 0
+min_lr: 1e-05
+lr: 0.01
+log_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_original
+model:
+  NAME: BaseSeg
+  encoder_args:
+    NAME: PointVectorEncoder
+    blocks: [1, 3, 5, 3, 3]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 1
+    sa_use_res: False
+    width: 32
+    in_channels: 4
+    expansion: 4
+    radius: 0.1
+    nsample: 32
+    flag: 1
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointVectorDecoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
+      norm: bn
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointvector-l
+opts: mode=test
+is_training: False
+run_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_original
+run_name: PVr_SEG_original
+ckpt_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_original/checkpoint
+code_dir: /workspace/FractalCloud/Model_logs/PVr_SEG_original/code
+log_path: /workspace/FractalCloud/Model_logs/PVr_SEG_original/PVr_SEG_original20251202-210507-PDAW9VGM4gPZxmtaxRzEuu.log
+cfg_path: /workspace/FractalCloud/Model_logs/PVr_SEG_original/cfg.yaml
+[12/02 21:05:07] S3DIS INFO: radius: [[0.1], [0.1, 0.2, 0.2], [0.2, 0.4, 0.4, 0.4, 0.4], [0.4, 0.8, 0.8], [0.8, 1.6, 1.6]],
+ nsample: [[32], [32, 32, 32], [32, 32, 32, 32, 32], [32, 32, 32], [32, 32, 32]]
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 8
+[12/02 21:05:07] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 8
+[12/02 21:05:14] S3DIS INFO: BaseSeg(
+  (encoder): PointVectorEncoder(
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(4, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), groups=64, bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), groups=64, bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (3): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (4): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), groups=128, bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(131, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), groups=256, bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), groups=256, bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(1536, 512, kernel_size=(1,), stride=(1,), groups=512, bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (vpsa): VPSA(
+              (theta_x_alpha): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (theta_x_beta): Sequential(
+                (0): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+              (z_x): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (tf_zx): Sequential(
+                (0): Conv1d(1536, 512, kernel_size=(1,), stride=(1,), groups=512, bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (relu): ReLU(inplace=True)
+              (lrlu): ReLU(inplace=True)
+              (bn1): Identity()
+              (result): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (pos_x): Sequential(
+                (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+              (residual): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+        )
+      )
+    )
+  )
+  (decoder): PointVectorDecoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[12/02 21:05:14] S3DIS INFO: Number of params: 4.2152 M
+[12/02 21:05:14] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
+      "encoder.encoder.0.0.convs.0.0.weight",
+      "encoder.encoder.1.0.convs.0.0.weight",
+      "encoder.encoder.1.1.convs.vpsa.theta_x_alpha.0.weight",
+      "encoder.encoder.1.1.convs.vpsa.theta_x_beta.0.weight",
+      "encoder.encoder.1.1.convs.vpsa.z_x.weight",
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+}
+[12/02 21:05:14] S3DIS INFO: 
+Totally 68 samples in val set
+[12/02 21:05:14] S3DIS INFO: length of validation dataset: 68
+[12/02 21:05:14] S3DIS INFO: number of classes of the dataset: 13
+[12/02 21:05:14] S3DIS INFO: Successful Loading the ckpt from /workspace/FractalCloud/Model_logs/PVr_SEG_original/checkpoint/s3dis-pointvector-l_ckpt_best_708.pth
+[12/02 21:05:14] S3DIS INFO: ckpts @ 58 epoch( {'best_val': 69.1866683959961} )
+[12/02 21:05:14] S3DIS INFO: length of test dataset: 68
+[12/02 21:05:14] S3DIS INFO: Test [0]/[68] cloud
+[12/02 21:05:43] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 93.40 97.61 80.69, 
+iou per cls is: [ 97.98  99.15  82.65 100.   100.   100.    97.97   0.   100.   100.
+   0.   100.    71.21]
+[12/02 21:05:43] S3DIS INFO: Test [1]/[68] cloud
+[12/02 21:06:02] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 93.93 97.82 96.36, 
+iou per cls is: [ 95.38  99.18  85.79 100.   100.   100.    98.28 100.   100.   100.
+ 100.   100.    74.  ]
+[12/02 21:06:02] S3DIS INFO: Test [2]/[68] cloud
+[12/02 21:06:43] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 93.27 94.44 74.70, 
+iou per cls is: [ 97.62  99.09  85.3    0.    57.4   77.42  83.15  94.72  95.69 100.
+   0.    97.16  83.54]
+[12/02 21:06:43] S3DIS INFO: Test [3]/[68] cloud
+[12/02 21:10:51] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 94.67 93.54 89.93, 
+iou per cls is: [ 97.23  97.83  90.69 100.    72.2  100.    96.52  94.66  94.9   99.84
+  73.19  86.5   65.56]
+[12/02 21:10:51] S3DIS INFO: Test [4]/[68] cloud
+[12/02 21:12:28] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 91.96 89.46 71.22, 
+iou per cls is: [ 96.15  99.48  79.4    0.    86.59  73.73  94.93  71.36  96.11 100.
+   0.    61.29  66.86]
+[12/02 21:12:28] S3DIS INFO: Test [5]/[68] cloud
+[12/02 21:21:21] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 79.14 80.79 36.43, 
+iou per cls is: [87.2  98.84 48.2   0.    7.63  1.55 15.67  0.    0.   91.79 90.41  0.
+ 32.24]
+[12/02 21:21:21] S3DIS INFO: Test [6]/[68] cloud
+[12/02 21:22:25] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 98.69 98.60 90.55, 
+iou per cls is: [ 98.36  99.43  97.65   0.   100.   100.    82.67 100.   100.   100.
+ 100.   100.    99.1 ]
+[12/02 21:22:25] S3DIS INFO: Test [7]/[68] cloud
+[12/02 21:22:58] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 97.88 97.92 89.93, 
+iou per cls is: [ 96.09  99.11  96.5  100.   100.   100.    77.44 100.   100.   100.
+ 100.   100.     0.  ]
+[12/02 21:22:58] S3DIS INFO: Test [8]/[68] cloud
+[12/02 21:23:33] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.37 97.68 96.93, 
+iou per cls is: [ 97.27  99.42  97.26 100.   100.   100.    80.61 100.   100.   100.
+ 100.   100.    85.51]
+[12/02 21:23:33] S3DIS INFO: Test [9]/[68] cloud
+[12/02 21:24:49] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 88.99 91.48 77.35, 
+iou per cls is: [ 98.72  99.33  88.46 100.     0.     7.44  19.1  100.   100.   100.
+ 100.   100.    92.49]
+[12/02 21:24:49] S3DIS INFO: Test [10]/[68] cloud
+[12/02 21:25:11] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 91.14 93.02 60.85, 
+iou per cls is: [ 98.8   99.03  89.75 100.     0.     0.    30.66 100.   100.   100.
+   0.     0.    72.84]
+[12/02 21:25:11] S3DIS INFO: Test [11]/[68] cloud
+[12/02 21:26:37] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 86.35 87.54 55.51, 
+iou per cls is: [ 97.78  99.38  75.37   0.    35.28   0.57  35.47   0.   100.   100.
+   0.   100.    77.73]
+[12/02 21:26:37] S3DIS INFO: Test [12]/[68] cloud
+[12/02 21:40:23] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 91.57 95.36 47.87, 
+iou per cls is: [ 94.13  98.92  86.12   0.     0.     0.    57.12   0.     0.   100.
+ 100.     0.    86.02]
+[12/02 21:40:23] S3DIS INFO: Test [13]/[68] cloud
+[12/02 21:41:20] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 95.49 92.24 60.78, 
+iou per cls is: [ 98.05  97.79  95.27 100.     0.     0.    19.34   0.   100.   100.
+   0.   100.    79.66]
+[12/02 21:41:20] S3DIS INFO: Test [14]/[68] cloud
+[12/02 21:42:00] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 96.87 95.01 83.89, 
+iou per cls is: [ 97.11  99.34  96.03 100.   100.   100.    87.26 100.     0.    70.83
+  91.84 100.    48.15]
+[12/02 21:42:00] S3DIS INFO: Test [15]/[68] cloud
+[12/02 21:46:47] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 96.48 92.60 65.28, 
+iou per cls is: [ 99.02  99.7   95.1  100.   100.     0.    66.94   0.     0.    77.69
+  58.53 100.    51.69]
+[12/02 21:46:47] S3DIS INFO: Test [16]/[68] cloud
+[12/02 21:47:22] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 96.39 97.72 88.65, 
+iou per cls is: [ 96.68  99.1   93.3  100.   100.   100.    85.48 100.   100.   100.
+ 100.     0.    77.86]
+[12/02 21:47:22] S3DIS INFO: Test [17]/[68] cloud
+[12/02 21:48:27] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 95.73 97.33 65.86, 
+iou per cls is: [ 98.73  99.38  93.78 100.     0.     0.    82.77 100.   100.   100.
+   0.     0.    81.5 ]
+[12/02 21:48:27] S3DIS INFO: Test [18]/[68] cloud
+[12/02 21:48:41] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 96.83 92.86 92.00, 
+iou per cls is: [ 96.39  99.39  94.16 100.   100.   100.    80.25 100.   100.   100.
+ 100.   100.    25.84]
+[12/02 21:48:41] S3DIS INFO: Test [19]/[68] cloud
+[12/02 21:49:51] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 97.19 88.10 70.63, 
+iou per cls is: [ 96.38  98.65  95.84   0.    60.85   0.38  76.96 100.   100.   100.
+   0.   100.    89.1 ]
+[12/02 21:49:51] S3DIS INFO: Test [20]/[68] cloud
+[12/02 21:50:44] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 95.04 93.51 54.04, 
+iou per cls is: [ 99.81  98.4   94.39 100.     0.   100.     0.    90.52  91.72   0.
+   0.     0.    27.67]
+[12/02 21:50:44] S3DIS INFO: Test [21]/[68] cloud
+[12/02 21:51:13] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 93.24 90.46 71.27, 
+iou per cls is: [98.04 98.24 72.22  0.   53.94 86.16 93.7  90.95 96.78  0.   96.34 74.71
+ 65.41]
+[12/02 21:51:13] S3DIS INFO: Test [22]/[68] cloud
+[12/02 21:51:40] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 92.28 87.78 75.49, 
+iou per cls is: [ 98.51  99.03  80.13   0.     7.14  91.05  95.36  62.88  98.09 100.
+  89.15  92.37  67.64]
+[12/02 21:51:40] S3DIS INFO: Test [23]/[68] cloud
+[12/02 21:52:12] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 93.78 85.30 72.35, 
+iou per cls is: [ 97.82  98.57  79.4    0.     0.23  53.61  89.84  79.    93.58 100.
+  95.28  86.93  66.23]
+[12/02 21:52:12] S3DIS INFO: Test [24]/[68] cloud
+[12/02 21:52:40] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 91.10 89.12 68.75, 
+iou per cls is: [ 97.61  97.28  77.15   0.    36.19  71.4   94.63  80.29  83.59 100.
+  94.18   0.    61.44]
+[12/02 21:52:40] S3DIS INFO: Test [25]/[68] cloud
+[12/02 21:53:25] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 90.23 88.43 75.14, 
+iou per cls is: [ 98.27  97.95  70.57   0.    39.43  84.05  80.89  68.84  95.14 100.
+  86.69  90.12  64.9 ]
+[12/02 21:53:25] S3DIS INFO: Test [26]/[68] cloud
+[12/02 21:54:36] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 87.92 85.97 72.59, 
+iou per cls is: [ 97.3   98.43  70.81   0.    10.25  60.77  94.55  69.27  92.4  100.
+  83.52  95.51  70.85]
+[12/02 21:54:36] S3DIS INFO: Test [27]/[68] cloud
+[12/02 21:55:52] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 89.98 88.99 76.76, 
+iou per cls is: [ 97.09  98.67  73.41   0.    13.46  79.84  88.05  89.11  96.85 100.
+  90.62  94.84  75.93]
+[12/02 21:55:52] S3DIS INFO: Test [28]/[68] cloud
+[12/02 21:56:21] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 92.82 86.44 74.71, 
+iou per cls is: [ 98.58  98.1   89.53   0.    79.59 100.    96.86  86.86  92.63 100.
+  37.79  27.11  64.25]
+[12/02 21:56:21] S3DIS INFO: Test [29]/[68] cloud
+[12/02 21:57:01] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 92.49 93.39 59.15, 
+iou per cls is: [ 97.51  98.24  96.83   0.     0.   100.    78.99  59.2    0.   100.
+  78.04   0.    60.13]
+[12/02 21:57:01] S3DIS INFO: Test [30]/[68] cloud
+[12/02 21:58:09] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 97.28 93.97 76.45, 
+iou per cls is: [ 99.32  98.52  95.56   0.    60.94   0.    93.31  97.79  94.35 100.
+  95.72  80.23  78.12]
+[12/02 21:58:09] S3DIS INFO: Test [31]/[68] cloud
+[12/02 22:00:11] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 87.08 88.74 68.05, 
+iou per cls is: [ 94.52  98.81  74.69   0.     0.   100.    90.2   90.22  90.53 100.
+  63.83  32.87  49.03]
+[12/02 22:00:11] S3DIS INFO: Test [32]/[68] cloud
+[12/02 22:00:45] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 93.05 87.72 75.78, 
+iou per cls is: [ 98.56  98.32  78.28   0.     0.04  84.99  96.86  70.8   95.28 100.
+  90.13  82.34  89.53]
+[12/02 22:00:45] S3DIS INFO: Test [33]/[68] cloud
+[12/02 22:00:59] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 90.99 93.34 73.04, 
+iou per cls is: [ 98.09  97.72  83.22   0.    78.75 100.    89.93  95.12  94.19 100.
+  60.99   0.    51.45]
+[12/02 22:00:59] S3DIS INFO: Test [34]/[68] cloud
+[12/02 22:03:54] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 93.09 92.45 71.73, 
+iou per cls is: [ 98.84  99.2   86.85   0.    73.89   0.    98.68  90.2   86.73 100.
+  50.07  95.87  52.19]
+[12/02 22:03:54] S3DIS INFO: Test [35]/[68] cloud
+[12/02 22:04:24] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 93.30 87.51 76.07, 
+iou per cls is: [ 96.83  98.46  80.93   0.     8.11  70.75  95.01  83.36  93.9  100.
+  96.47  86.91  78.18]
+[12/02 22:04:24] S3DIS INFO: Test [36]/[68] cloud
+[12/02 22:05:02] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 94.21 89.97 71.60, 
+iou per cls is: [97.76 97.69 83.34  0.   30.37 74.72 92.59 89.7  91.78  0.   97.4  91.16
+ 84.28]
+[12/02 22:05:02] S3DIS INFO: Test [37]/[68] cloud
+[12/02 22:06:57] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 82.41 83.63 68.26, 
+iou per cls is: [95.96 94.5  58.85  0.   51.29 76.1  89.19 75.18 85.28 68.63 54.26 92.81
+ 45.34]
+[12/02 22:06:57] S3DIS INFO: Test [38]/[68] cloud
+[12/02 22:07:17] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 90.36 91.12 70.81, 
+iou per cls is: [ 96.63  95.76  82.7    0.     0.    86.27  92.04  72.84  97.67 100.
+  84.92  50.12  61.56]
+[12/02 22:07:17] S3DIS INFO: Test [39]/[68] cloud
+[12/02 22:07:42] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 85.68 82.21 68.27, 
+iou per cls is: [ 95.08  97.67  85.71   0.    44.41  84.83  95.21  70.44  92.47 100.
+  61.71  19.45  40.48]
+[12/02 22:07:42] S3DIS INFO: Test [40]/[68] cloud
+[12/02 22:08:10] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 91.97 87.47 68.96, 
+iou per cls is: [96.36 99.39 80.63  0.    7.64 87.23 95.01 89.56 96.05  0.   92.39 87.84
+ 64.36]
+[12/02 22:08:10] S3DIS INFO: Test [41]/[68] cloud
+[12/02 22:08:39] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 93.84 89.09 78.05, 
+iou per cls is: [ 97.1   99.12  88.1    0.    33.9   94.32  95.21  79.71  93.72 100.
+  89.08  88.3   56.03]
+[12/02 22:08:39] S3DIS INFO: Test [42]/[68] cloud
+[12/02 22:10:44] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 82.68 86.14 64.74, 
+iou per cls is: [97.34 97.89 61.27  0.   60.58 82.25 94.38 89.17 94.1   0.   28.73 92.79
+ 43.12]
+[12/02 22:10:44] S3DIS INFO: Test [43]/[68] cloud
+[12/02 22:11:10] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 93.76 94.44 83.58, 
+iou per cls is: [ 98.55  98.93  75.61   0.   100.    88.14  97.1   83.53  96.69 100.
+  95.58  94.66  57.72]
+[12/02 22:11:10] S3DIS INFO: Test [44]/[68] cloud
+[12/02 22:11:23] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.95 96.75 94.48, 
+iou per cls is: [ 94.73  98.06  96.64 100.   100.   100.    96.91  84.84  95.88 100.
+  94.18  95.68  71.31]
+[12/02 22:11:23] S3DIS INFO: Test [45]/[68] cloud
+[12/02 22:12:01] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 86.74 89.18 73.83, 
+iou per cls is: [ 98.    99.55  64.01   0.    20.47  85.95  84.54  61.74  97.16 100.
+  77.38 100.    70.96]
+[12/02 22:12:01] S3DIS INFO: Test [46]/[68] cloud
+[12/02 22:12:29] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 92.02 90.36 78.93, 
+iou per cls is: [ 97.47  99.57  79.32   0.    22.11  86.88  94.4   87.84  94.74 100.
+  85.19 100.    78.61]
+[12/02 22:12:29] S3DIS INFO: Test [47]/[68] cloud
+[12/02 22:13:12] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 93.07 89.50 77.93, 
+iou per cls is: [ 96.09  99.49  85.04   0.    15.47  90.5   95.19  88.78  95.68 100.
+  87.52  96.76  62.56]
+[12/02 22:13:12] S3DIS INFO: Test [48]/[68] cloud
+[12/02 22:13:56] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 86.20 85.83 79.94, 
+iou per cls is: [ 95.22  97.37  70.17 100.    21.61  77.08  93.    61.2   95.88 100.
+  79.9   91.6   56.19]
+[12/02 22:13:56] S3DIS INFO: Test [49]/[68] cloud
+[12/02 22:14:35] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 97.49 97.91 88.52, 
+iou per cls is: [ 98.57  97.35  95.72   0.   100.   100.    97.85  90.16  92.98 100.
+  94.09  96.96  87.02]
+[12/02 22:14:35] S3DIS INFO: Test [50]/[68] cloud
+[12/02 22:15:41] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 93.47 93.93 65.46, 
+iou per cls is: [ 98.47  95.63  94.44   0.     0.     0.    96.89  80.    92.16 100.
+  56.23  92.99  44.21]
+[12/02 22:15:41] S3DIS INFO: Test [51]/[68] cloud
+[12/02 22:20:56] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 88.14 84.96 63.83, 
+iou per cls is: [ 90.79  98.87  82.18   0.     4.88 100.    84.23  73.45  86.59   0.
+  66.77  68.93  73.02]
+[12/02 22:20:56] S3DIS INFO: Test [52]/[68] cloud
+[12/02 22:27:15] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 82.70 80.63 49.72, 
+iou per cls is: [91.91 97.57 65.67  0.   18.95  0.   32.22 67.58 72.08 70.82 65.41  0.
+ 64.17]
+[12/02 22:27:15] S3DIS INFO: Test [53]/[68] cloud
+[12/02 22:27:54] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 92.47 86.29 82.20, 
+iou per cls is: [ 93.27  98.41  92.31   0.   100.   100.    93.12  92.12  93.83 100.
+  58.24  86.4   60.82]
+[12/02 22:27:54] S3DIS INFO: Test [54]/[68] cloud
+[12/02 22:28:24] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 94.47 90.87 78.95, 
+iou per cls is: [ 98.17  98.64  85.15   0.    23.18  85.27  96.09  77.61  98.18 100.
+  91.23  93.98  78.83]
+[12/02 22:28:24] S3DIS INFO: Test [55]/[68] cloud
+[12/02 22:34:17] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 93.13 89.03 84.81, 
+iou per cls is: [ 97.66  97.39  89.26 100.    51.5  100.    94.43  78.57  84.   100.
+  85.4   55.83  68.55]
+[12/02 22:34:17] S3DIS INFO: Test [56]/[68] cloud
+[12/02 22:36:04] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 91.89 92.72 77.49, 
+iou per cls is: [ 97.63  98.24  69.82   0.    31.12  83.61  96.97  90.92  85.1  100.
+  85.61  91.02  77.33]
+[12/02 22:36:04] S3DIS INFO: Test [57]/[68] cloud
+[12/02 22:36:46] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 92.15 92.50 80.51, 
+iou per cls is: [ 97.7   97.95  76.89   0.    68.64  63.42  93.54  90.28  94.51 100.
+  88.58 100.    75.16]
+[12/02 22:36:46] S3DIS INFO: Test [58]/[68] cloud
+[12/02 22:37:09] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 96.05 96.73 78.95, 
+iou per cls is: [ 97.78  98.45  90.15   0.     0.    79.03  87.07  90.92  99.1  100.
+  95.12 100.    88.7 ]
+[12/02 22:37:09] S3DIS INFO: Test [59]/[68] cloud
+[12/02 22:37:36] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 93.89 93.26 74.50, 
+iou per cls is: [ 98.08  98.57  78.01   0.     0.    64.7   78.41  87.52  92.56 100.
+  95.47  96.51  78.73]
+[12/02 22:37:36] S3DIS INFO: Test [60]/[68] cloud
+[12/02 22:38:13] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 92.67 86.64 74.97, 
+iou per cls is: [ 98.52  98.47  74.4    0.     0.53  75.23  92.55  78.25  98.66 100.
+  91.68  91.04  75.32]
+[12/02 22:38:13] S3DIS INFO: Test [61]/[68] cloud
+[12/02 22:38:55] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 93.00 87.72 73.79, 
+iou per cls is: [ 98.56  96.7   78.04   0.    15.34  59.3   90.44  91.06  96.06 100.
+  96.56  93.72  43.52]
+[12/02 22:38:55] S3DIS INFO: Test [62]/[68] cloud
+[12/02 22:39:26] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 94.79 95.39 76.11, 
+iou per cls is: [ 96.38  96.93  90.09   0.     0.    82.37  90.87  74.65  97.93  86.19
+  96.26 100.    77.75]
+[12/02 22:39:26] S3DIS INFO: Test [63]/[68] cloud
+[12/02 22:39:46] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 73.21 92.86 45.90, 
+iou per cls is: [ 93.84  98.24  89.84   0.     0.   100.     0.     0.   100.   100.
+   0.     0.    14.83]
+[12/02 22:39:46] S3DIS INFO: Test [64]/[68] cloud
+[12/02 22:40:07] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 77.90 78.61 48.90, 
+iou per cls is: [ 91.84  96.75  71.61   0.     6.38   0.    62.22 100.     0.   100.
+  77.01   0.    29.89]
+[12/02 22:40:07] S3DIS INFO: Test [65]/[68] cloud
+[12/02 22:40:44] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 78.26 90.22 54.61, 
+iou per cls is: [ 38.6   97.41  83.27 100.     0.     0.    72.58   0.   100.   100.
+  72.24   0.    45.89]
+[12/02 22:40:44] S3DIS INFO: Test [66]/[68] cloud
+[12/02 22:40:48] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 87.19 94.10 54.29, 
+iou per cls is: [ 58.59  99.65  90.92 100.     0.     0.    93.97 100.     0.   100.
+   0.     0.    62.61]
+[12/02 22:40:48] S3DIS INFO: Test [67]/[68] cloud
+[12/02 22:41:12] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 86.10 88.76 63.61, 
+iou per cls is: [ 91.63  98.45  91.49 100.   100.     0.    49.04  65.86  85.06 100.
+   0.     0.    45.44]
+[12/02 22:41:12] S3DIS INFO: Best ckpt @E58,  test_oa , test_macc, test_miou: 90.97 76.75 70.83, 
+iou per cls is: [95.47 98.57 84.7   0.   31.31 61.58 73.35 82.01 91.14 80.71 77.78 80.65
+ 63.46]

Pretrained_Models/PVr_SEG_original/PVr_SEG_original_test.csv

@@ -0,0 +1,2 @@
+method,Area,OA,mACC,mIoU,ceiling,floor,wall,beam,column,window,door,chair,table,bookcase,sofa,board,clutter,best_epoch,log_path,wandb link
+pointvector-l,5,90.97,76.75,70.83,95.47,98.57,84.70,0.00,31.31,61.58,73.35,82.01,91.14,80.71,77.78,80.65,63.46,58,/workspace/FractalCloud/Model_logs/PVr_SEG_original,-

Pretrained_Models/PVr_SEG_original/checkpoint/s3dis-pointvector-l_ckpt_best_708.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a9b4eba5a453a9ba006cbc4aea679c8b1498cf6455c23c5610cdce1130109b18
+size 51014805