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  1. README.md +132 -0
  2. config.json +144 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +23 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: other
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+ base_model: nvidia/mit-b0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b0-finetuned-segments-sidewalk-2
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # segformer-b0-finetuned-segments-sidewalk-2
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.2724
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+ - Mean Iou: 0.1495
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+ - Mean Accuracy: 0.1960
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+ - Overall Accuracy: 0.7256
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+ - Accuracy Unlabeled: nan
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+ - Accuracy Flat-road: 0.8070
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+ - Accuracy Flat-sidewalk: 0.9392
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+ - Accuracy Flat-crosswalk: 0.0
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+ - Accuracy Flat-cyclinglane: 0.0002
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+ - Accuracy Flat-parkingdriveway: 0.0009
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+ - Accuracy Flat-railtrack: nan
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+ - Accuracy Flat-curb: 0.0
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+ - Accuracy Human-person: 0.0
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+ - Accuracy Human-rider: 0.0
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+ - Accuracy Vehicle-car: 0.8879
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+ - Accuracy Vehicle-truck: 0.0
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+ - Accuracy Vehicle-bus: 0.0
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+ - Accuracy Vehicle-tramtrain: nan
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+ - Accuracy Vehicle-motorcycle: 0.0
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+ - Accuracy Vehicle-bicycle: 0.0
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+ - Accuracy Vehicle-caravan: 0.0
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+ - Accuracy Vehicle-cartrailer: 0.0
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+ - Accuracy Construction-building: 0.8974
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+ - Accuracy Construction-door: 0.0
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+ - Accuracy Construction-wall: 0.0000
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+ - Accuracy Construction-fenceguardrail: 0.0
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+ - Accuracy Construction-bridge: 0.0
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+ - Accuracy Construction-tunnel: nan
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+ - Accuracy Construction-stairs: 0.0
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+ - Accuracy Object-pole: 0.0
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+ - Accuracy Object-trafficsign: 0.0
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+ - Accuracy Object-trafficlight: 0.0
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+ - Accuracy Nature-vegetation: 0.9038
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+ - Accuracy Nature-terrain: 0.7460
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+ - Accuracy Sky: 0.8949
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+ - Accuracy Void-ground: 0.0
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+ - Accuracy Void-dynamic: 0.0
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+ - Accuracy Void-static: 0.0
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+ - Accuracy Void-unclear: 0.0
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+ - Iou Unlabeled: nan
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+ - Iou Flat-road: 0.4433
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+ - Iou Flat-sidewalk: 0.7724
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+ - Iou Flat-crosswalk: 0.0
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+ - Iou Flat-cyclinglane: 0.0002
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+ - Iou Flat-parkingdriveway: 0.0009
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+ - Iou Flat-railtrack: nan
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+ - Iou Flat-curb: 0.0
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+ - Iou Human-person: 0.0
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+ - Iou Human-rider: 0.0
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+ - Iou Vehicle-car: 0.6650
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+ - Iou Vehicle-truck: 0.0
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+ - Iou Vehicle-bus: 0.0
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+ - Iou Vehicle-tramtrain: nan
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+ - Iou Vehicle-motorcycle: 0.0
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+ - Iou Vehicle-bicycle: 0.0
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+ - Iou Vehicle-caravan: 0.0
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+ - Iou Vehicle-cartrailer: 0.0
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+ - Iou Construction-building: 0.5726
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+ - Iou Construction-door: 0.0
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+ - Iou Construction-wall: 0.0000
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+ - Iou Construction-fenceguardrail: 0.0
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+ - Iou Construction-bridge: 0.0
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+ - Iou Construction-tunnel: nan
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+ - Iou Construction-stairs: 0.0
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+ - Iou Object-pole: 0.0
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+ - Iou Object-trafficsign: 0.0
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+ - Iou Object-trafficlight: 0.0
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+ - Iou Nature-vegetation: 0.7664
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+ - Iou Nature-terrain: 0.5795
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+ - Iou Sky: 0.8338
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+ - Iou Void-ground: 0.0
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+ - Iou Void-dynamic: 0.0
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+ - Iou Void-static: 0.0
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+ - Iou Void-unclear: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Flat-road | Accuracy Flat-sidewalk | Accuracy Flat-crosswalk | Accuracy Flat-cyclinglane | Accuracy Flat-parkingdriveway | Accuracy Flat-railtrack | Accuracy Flat-curb | Accuracy Human-person | Accuracy Human-rider | Accuracy Vehicle-car | Accuracy Vehicle-truck | Accuracy Vehicle-bus | Accuracy Vehicle-tramtrain | Accuracy Vehicle-motorcycle | Accuracy Vehicle-bicycle | Accuracy Vehicle-caravan | Accuracy Vehicle-cartrailer | Accuracy Construction-building | Accuracy Construction-door | Accuracy Construction-wall | Accuracy Construction-fenceguardrail | Accuracy Construction-bridge | Accuracy Construction-tunnel | Accuracy Construction-stairs | Accuracy Object-pole | Accuracy Object-trafficsign | Accuracy Object-trafficlight | Accuracy Nature-vegetation | Accuracy Nature-terrain | Accuracy Sky | Accuracy Void-ground | Accuracy Void-dynamic | Accuracy Void-static | Accuracy Void-unclear | Iou Unlabeled | Iou Flat-road | Iou Flat-sidewalk | Iou Flat-crosswalk | Iou Flat-cyclinglane | Iou Flat-parkingdriveway | Iou Flat-railtrack | Iou Flat-curb | Iou Human-person | Iou Human-rider | Iou Vehicle-car | Iou Vehicle-truck | Iou Vehicle-bus | Iou Vehicle-tramtrain | Iou Vehicle-motorcycle | Iou Vehicle-bicycle | Iou Vehicle-caravan | Iou Vehicle-cartrailer | Iou Construction-building | Iou Construction-door | Iou Construction-wall | Iou Construction-fenceguardrail | Iou Construction-bridge | Iou Construction-tunnel | Iou Construction-stairs | Iou Object-pole | Iou Object-trafficsign | Iou Object-trafficlight | Iou Nature-vegetation | Iou Nature-terrain | Iou Sky | Iou Void-ground | Iou Void-dynamic | Iou Void-static | Iou Void-unclear |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:------------------:|:----------------------:|:-----------------------:|:-------------------------:|:-----------------------------:|:-----------------------:|:------------------:|:---------------------:|:--------------------:|:--------------------:|:----------------------:|:--------------------:|:--------------------------:|:---------------------------:|:------------------------:|:------------------------:|:---------------------------:|:------------------------------:|:--------------------------:|:--------------------------:|:------------------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|:--------------------:|:---------------------------:|:----------------------------:|:--------------------------:|:-----------------------:|:------------:|:--------------------:|:---------------------:|:--------------------:|:---------------------:|:-------------:|:-------------:|:-----------------:|:------------------:|:--------------------:|:------------------------:|:------------------:|:-------------:|:----------------:|:---------------:|:---------------:|:-----------------:|:---------------:|:---------------------:|:----------------------:|:-------------------:|:-------------------:|:----------------------:|:-------------------------:|:---------------------:|:---------------------:|:-------------------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:---------------:|:----------------------:|:-----------------------:|:---------------------:|:------------------:|:-------:|:---------------:|:----------------:|:---------------:|:----------------:|
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+ | 1.4413 | 0.5 | 200 | 1.4848 | 0.1418 | 0.1882 | 0.7099 | nan | 0.7601 | 0.9256 | 0.0 | 0.0000 | 0.0008 | nan | 0.0 | 0.0 | 0.0 | 0.9123 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8325 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9495 | 0.6045 | 0.8493 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4216 | 0.7513 | 0.0 | 0.0000 | 0.0008 | nan | 0.0 | 0.0 | 0.0 | 0.5842 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5625 | 0.0 | 0.0003 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7323 | 0.5296 | 0.8122 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.6008 | 1.0 | 400 | 1.2724 | 0.1495 | 0.1960 | 0.7256 | nan | 0.8070 | 0.9392 | 0.0 | 0.0002 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.8879 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.8974 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.9038 | 0.7460 | 0.8949 | 0.0 | 0.0 | 0.0 | 0.0 | nan | 0.4433 | 0.7724 | 0.0 | 0.0002 | 0.0009 | nan | 0.0 | 0.0 | 0.0 | 0.6650 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.5726 | 0.0 | 0.0000 | 0.0 | 0.0 | nan | 0.0 | 0.0 | 0.0 | 0.0 | 0.7664 | 0.5795 | 0.8338 | 0.0 | 0.0 | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
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+ "2": "flat-sidewalk",
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+ "3": "flat-crosswalk",
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+ "4": "flat-cyclinglane",
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+ "5": "flat-parkingdriveway",
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+ "6": "flat-railtrack",
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+ "7": "flat-curb",
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+ "8": "human-person",
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+ "9": "human-rider",
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+ "13": "vehicle-tramtrain",
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+ "17": "vehicle-cartrailer",
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+ "19": "construction-door",
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+ "20": "construction-wall",
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+ "21": "construction-fenceguardrail",
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+ "24": "construction-stairs",
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