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.gitignore

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+checkpoint-*/

README.md

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+---
+license: other
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-segments-sidewalk-2
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# segformer-b0-finetuned-segments-sidewalk-2
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the pixel_values, the label and the {'pixel_values': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1920x1080 at 0x7FCAFB662B60>, 'label': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=1x1 at 0x7FCAFB662B30>} datasets.
+It achieves the following results on the evaluation set:
+- Loss: 3.5116
+- Mean Iou: 0.0268
+- Mean Accuracy: 0.0661
+- Overall Accuracy: 0.2418
+- Accuracy Unlabeled: nan
+- Accuracy Flat-road: 0.0351
+- Accuracy Flat-sidewalk: 0.5938
+- Accuracy Flat-crosswalk: 0.3236
+- Accuracy Flat-cyclinglane: 0.0338
+- Accuracy Flat-parkingdriveway: 0.0555
+- Accuracy Flat-railtrack: nan
+- Accuracy Flat-curb: 0.0006
+- Accuracy Human-person: 0.0
+- Accuracy Human-rider: 0.0003
+- Accuracy Vehicle-car: 0.3388
+- Accuracy Vehicle-truck: 0.0016
+- Accuracy Vehicle-bus: 0.0
+- Accuracy Vehicle-tramtrain: 0.2141
+- Accuracy Vehicle-motorcycle: 0.0053
+- Accuracy Vehicle-bicycle: 0.0
+- Accuracy Vehicle-caravan: 0.0
+- Accuracy Vehicle-cartrailer: 0.0888
+- Accuracy Construction-building: 0.0391
+- Accuracy Construction-door: 0.0
+- Accuracy Construction-wall: 0.0074
+- Accuracy Construction-fenceguardrail: 0.0239
+- Accuracy Construction-bridge: 0.0
+- Accuracy Construction-tunnel: nan
+- Accuracy Construction-stairs: 0.0006
+- Accuracy Object-pole: 0.0593
+- Accuracy Object-trafficsign: 0.0
+- Accuracy Object-trafficlight: 0.0665
+- Accuracy Nature-vegetation: 0.0846
+- Accuracy Nature-terrain: 0.0002
+- Accuracy Sky: 0.0030
+- Accuracy Void-ground: 0.0635
+- Accuracy Void-dynamic: 0.0004
+- Accuracy Void-static: 0.0720
+- Accuracy Void-unclear: 0.0022
+- Iou Unlabeled: 0.0
+- Iou Flat-road: 0.0297
+- Iou Flat-sidewalk: 0.4826
+- Iou Flat-crosswalk: 0.0624
+- Iou Flat-cyclinglane: 0.0279
+- Iou Flat-parkingdriveway: 0.0203
+- Iou Flat-railtrack: 0.0
+- Iou Flat-curb: 0.0005
+- Iou Human-person: 0.0
+- Iou Human-rider: 0.0001
+- Iou Vehicle-car: 0.1389
+- Iou Vehicle-truck: 0.0000
+- Iou Vehicle-bus: 0.0
+- Iou Vehicle-tramtrain: 0.0013
+- Iou Vehicle-motorcycle: 0.0007
+- Iou Vehicle-bicycle: 0.0
+- Iou Vehicle-caravan: 0.0
+- Iou Vehicle-cartrailer: 0.0004
+- Iou Construction-building: 0.0383
+- Iou Construction-door: 0.0
+- Iou Construction-wall: 0.0057
+- Iou Construction-fenceguardrail: 0.0127
+- Iou Construction-bridge: 0.0
+- Iou Construction-tunnel: 0.0
+- Iou Construction-stairs: 0.0001
+- Iou Object-pole: 0.0085
+- Iou Object-trafficsign: 0.0
+- Iou Object-trafficlight: 0.0002
+- Iou Nature-vegetation: 0.0818
+- Iou Nature-terrain: 0.0002
+- Iou Sky: 0.0027
+- Iou Void-ground: 0.0115
+- Iou Void-dynamic: 0.0001
+- Iou Void-static: 0.0102
+- Iou Void-unclear: 0.0021
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 6e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 0.025
+
+### Training results
+
+| 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:------------------:|:----------------------:|:-----------------------:|:-------------------------:|:-----------------------------:|:-----------------------:|:------------------:|:---------------------:|:--------------------:|:--------------------:|:----------------------:|:--------------------:|:--------------------------:|:---------------------------:|:------------------------:|:------------------------:|:---------------------------:|:------------------------------:|:--------------------------:|:--------------------------:|:------------------------------------:|:----------------------------:|:----------------------------:|:----------------------------:|:--------------------:|:---------------------------:|:----------------------------:|:--------------------------:|:-----------------------:|:------------:|:--------------------:|:---------------------:|:--------------------:|:---------------------:|:-------------:|:-------------:|:-----------------:|:------------------:|:--------------------:|:------------------------:|:------------------:|:-------------:|:----------------:|:---------------:|:---------------:|:-----------------:|:---------------:|:---------------------:|:----------------------:|:-------------------:|:-------------------:|:----------------------:|:-------------------------:|:---------------------:|:---------------------:|:-------------------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:---------------:|:----------------------:|:-----------------------:|:---------------------:|:------------------:|:-------:|:---------------:|:----------------:|:---------------:|:----------------:|
+| 3.5028        | 0.01  | 5    | 3.5307          | 0.0194   | 0.0486        | 0.1779           | nan                | 0.0150             | 0.4721                 | 0.2351                  | 0.0249                    | 0.0409                        | nan                     | 0.0003             | 0.0                   | 0.0003               | 0.1461               | 0.0231                 | 0.0                  | 0.2163                     | 0.0047                      | 0.0                      | 0.0                      | 0.0318                      | 0.0223                         | 0.0003                     | 0.0136                     | 0.0166                               | 0.0                          | nan                          | 0.0008                       | 0.0511               | 0.0                         | 0.0665                       | 0.0261                     | 0.0005                  | 0.0010       | 0.0697               | 0.0014                | 0.0720               | 0.0020                | 0.0           | 0.0128        | 0.3979            | 0.0509             | 0.0221               | 0.0166                   | 0.0                | 0.0003        | 0.0              | 0.0001          | 0.0769          | 0.0000            | 0.0             | 0.0015                | 0.0003                 | 0.0                 | 0.0                 | 0.0001                 | 0.0219                    | 0.0001                | 0.0089                | 0.0103                          | 0.0                     | 0.0                     | 0.0001                  | 0.0070          | 0.0                    | 0.0001                  | 0.0257                | 0.0005             | 0.0009  | 0.0109          | 0.0004           | 0.0099          | 0.0019           |
+| 3.3613        | 0.03  | 10   | 3.5116          | 0.0268   | 0.0661        | 0.2418           | nan                | 0.0351             | 0.5938                 | 0.3236                  | 0.0338                    | 0.0555                        | nan                     | 0.0006             | 0.0                   | 0.0003               | 0.3388               | 0.0016                 | 0.0                  | 0.2141                     | 0.0053                      | 0.0                      | 0.0                      | 0.0888                      | 0.0391                         | 0.0                        | 0.0074                     | 0.0239                               | 0.0                          | nan                          | 0.0006                       | 0.0593               | 0.0                         | 0.0665                       | 0.0846                     | 0.0002                  | 0.0030       | 0.0635               | 0.0004                | 0.0720               | 0.0022                | 0.0           | 0.0297        | 0.4826            | 0.0624             | 0.0279               | 0.0203                   | 0.0                | 0.0005        | 0.0              | 0.0001          | 0.1389          | 0.0000            | 0.0             | 0.0013                | 0.0007                 | 0.0                 | 0.0                 | 0.0004                 | 0.0383                    | 0.0                   | 0.0057                | 0.0127                          | 0.0                     | 0.0                     | 0.0001                  | 0.0085          | 0.0                    | 0.0002                  | 0.0818                | 0.0002             | 0.0027  | 0.0115          | 0.0001           | 0.0102          | 0.0021           |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3

config.json

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 {
-  "do_normalize": true,
-  "do_reduce_labels": true,
-  "do_rescale": true,
-  "do_resize": true,
-  "feature_extractor_type": "SegformerFeatureExtractor",
-  "image_mean": [
-    0.485,
-    0.456,
-    0.406
-  ],
-  "image_processor_type": "SegformerFeatureExtractor",
-  "image_std": [
-    0.229,
-    0.224,
-    0.225
-  ],
-  "resample": 2,
-  "rescale_factor": 0.00392156862745098,
-  "size": {
-    "height": 512,
-    "width": 512
-  }
+  "_name_or_path": "nvidia/mit-b0",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    32,
+    64,
+    160,
+    256
+  ],
+  "id2label": {
+    "0": "unlabeled",
+    "1": "flat-road",
+    "2": "flat-sidewalk",
+    "3": "flat-crosswalk",
+    "4": "flat-cyclinglane",
+    "5": "flat-parkingdriveway",
+    "6": "flat-railtrack",
+    "7": "flat-curb",
+    "8": "human-person",
+    "9": "human-rider",
+    "10": "vehicle-car",
+    "11": "vehicle-truck",
+    "12": "vehicle-bus",
+    "13": "vehicle-tramtrain",
+    "14": "vehicle-motorcycle",
+    "15": "vehicle-bicycle",
+    "16": "vehicle-caravan",
+    "17": "vehicle-cartrailer",
+    "18": "construction-building",
+    "19": "construction-door",
+    "20": "construction-wall",
+    "21": "construction-fenceguardrail",
+    "22": "construction-bridge",
+    "23": "construction-tunnel",
+    "24": "construction-stairs",
+    "25": "object-pole",
+    "26": "object-trafficsign",
+    "27": "object-trafficlight",
+    "28": "nature-vegetation",
+    "29": "nature-terrain",
+    "30": "sky",
+    "31": "void-ground",
+    "32": "void-dynamic",
+    "33": "void-static",
+    "34": "void-unclear"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "construction-bridge": 22,
+    "construction-building": 18,
+    "construction-door": 19,
+    "construction-fenceguardrail": 21,
+    "construction-stairs": 24,
+    "construction-tunnel": 23,
+    "construction-wall": 20,
+    "flat-crosswalk": 3,
+    "flat-curb": 7,
+    "flat-cyclinglane": 4,
+    "flat-parkingdriveway": 5,
+    "flat-railtrack": 6,
+    "flat-road": 1,
+    "flat-sidewalk": 2,
+    "human-person": 8,
+    "human-rider": 9,
+    "nature-terrain": 29,
+    "nature-vegetation": 28,
+    "object-pole": 25,
+    "object-trafficlight": 27,
+    "object-trafficsign": 26,
+    "sky": 30,
+    "unlabeled": 0,
+    "vehicle-bicycle": 15,
+    "vehicle-bus": 12,
+    "vehicle-car": 10,
+    "vehicle-caravan": 16,
+    "vehicle-cartrailer": 17,
+    "vehicle-motorcycle": 14,
+    "vehicle-tramtrain": 13,
+    "vehicle-truck": 11,
+    "void-dynamic": 32,
+    "void-ground": 31,
+    "void-static": 33,
+    "void-unclear": 34
+  },
+  "layer_norm_eps": 1e-06,
+  "mlp_ratios": [
+    4,
+    4,
+    4,
+    4
+  ],
+  "model_type": "segformer",
+  "num_attention_heads": [
+    1,
+    2,
+    5,
+    8
+  ],
+  "num_channels": 3,
+  "num_encoder_blocks": 4,
+  "patch_sizes": [
+    7,
+    3,
+    3,
+    3
+  ],
+  "reshape_last_stage": true,
+  "semantic_loss_ignore_index": 255,
+  "sr_ratios": [
+    8,
+    4,
+    2,
+    1
+  ],
+  "strides": [
+    4,
+    2,
+    2,
+    2
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.0"
 }

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