
# Dataset Card for sidewalk-semantic

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
- [Dataset Structure](#dataset-structure)
  - [Data Categories](#data-categories)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-instances)
  - [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

- **Homepage:** [Dataset homepage on Segments.ai](https://segments.ai/segments/sidewalk-imagery/)
- **Repository:** [Needs More Information]
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Bert De Brabandere](mailto:bert@segments.ai)

### Dataset Summary

A dataset of sidewalk images gathered in Belgium in the summer of 2021. Label your own semantic segmentation datasets on [segments.ai](https://segments.ai/?utm_source=hf&utm_medium=hf-ds&utm_campaign=sidewalk)

### Supported Tasks and Leaderboards

- `semantic-segmentation`: The dataset can be used to train a semantic segmentation model, where each pixel is classified. The model performance is measured by how high its [mean IoU (intersection over union)](https://huggingface.co/metrics/mean_iou) to the reference is.

## Dataset Structure

### Data categories

| Id  | Name | Description |
| --- | ---- | ----------- |
| 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 | - |

### Data Instances

[Needs More Information]

### Data Fields

[Needs More Information]

### Data Splits

This dataset only contains one split.

## Dataset Creation

### Curation Rationale

[Needs More Information]

### Source Data

#### Initial Data Collection and Normalization

[Needs More Information]

#### Who are the source language producers?

[Needs More Information]

### Annotations

#### Annotation process

[Needs More Information]

#### Who are the annotators?

[Needs More Information]

### Personal and Sensitive Information

[Needs More Information]

## Considerations for Using the Data

### Social Impact of Dataset

[Needs More Information]

### Discussion of Biases

[Needs More Information]

### Other Known Limitations

[Needs More Information]

## Additional Information

### Dataset Curators

[Needs More Information]

### Licensing Information

[Needs More Information]

### Citation Information

[Needs More Information]
task_categories:image-segmentation task_ids:semantic-segmentation annotations_creators:crowdsourced annotations_creators:expert-generated language_creators:expert-generated size_categories:n<1K source_datasets:original license:cc-by-nc-4.0 region:us
{"annotations_creators": ["crowdsourced", "expert-generated"], "language_creators": ["expert-generated"], "license": "cc-by-nc-4.0", "multilinguality": [], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["image-segmentation"], "task_ids": ["semantic-segmentation"], "pretty_name": "sidewalk-semantic"}
TAGS
#task_categories-image-segmentation #task_ids-semantic-segmentation #annotations_creators-crowdsourced #annotations_creators-expert-generated #language_creators-expert-generated #size_categories-n<1K #source_datasets-original #license-cc-by-nc-4.0 #region-us 

Dataset Card for sidewalk-semantic
==================================


Table of Contents
-----------------


* Dataset Description
	+ Dataset Summary
	+ Supported Tasks
* Dataset Structure
	+ Data Categories
	+ Data Instances
	+ Data Fields
	+ Data Splits
* Dataset Creation
	+ Curation Rationale
	+ Source Data
	+ Annotations
	+ Personal and Sensitive Information
* Considerations for Using the Data
	+ Social Impact of Dataset
	+ Discussion of Biases
	+ Other Known Limitations
* Additional Information
	+ Dataset Curators
	+ Licensing Information
	+ Citation Information


Dataset Description
-------------------


* Homepage: Dataset homepage on URL
* Repository:
* Paper:
* Leaderboard:
* Point of Contact: Bert De Brabandere


### Dataset Summary


A dataset of sidewalk images gathered in Belgium in the summer of 2021. Label your own semantic segmentation datasets on URL


### Supported Tasks and Leaderboards


* 'semantic-segmentation': The dataset can be used to train a semantic segmentation model, where each pixel is classified. The model performance is measured by how high its mean IoU (intersection over union) to the reference is.


Dataset Structure
-----------------


### Data categories


Id: 0, Name: unlabeled, Description: -
Id: 1, Name: flat-road, Description: -
Id: 2, Name: flat-sidewalk, Description: -
Id: 3, Name: flat-crosswalk, Description: -
Id: 4, Name: flat-cyclinglane, Description: -
Id: 5, Name: flat-parkingdriveway, Description: -
Id: 6, Name: flat-railtrack, Description: -
Id: 7, Name: flat-curb, Description: -
Id: 8, Name: human-person, Description: -
Id: 9, Name: human-rider, Description: -
Id: 10, Name: vehicle-car, Description: -
Id: 11, Name: vehicle-truck, Description: -
Id: 12, Name: vehicle-bus, Description: -
Id: 13, Name: vehicle-tramtrain, Description: -
Id: 14, Name: vehicle-motorcycle, Description: -
Id: 15, Name: vehicle-bicycle, Description: -
Id: 16, Name: vehicle-caravan, Description: -
Id: 17, Name: vehicle-cartrailer, Description: -
Id: 18, Name: construction-building, Description: -
Id: 19, Name: construction-door, Description: -
Id: 20, Name: construction-wall, Description: -
Id: 21, Name: construction-fenceguardrail, Description: -
Id: 22, Name: construction-bridge, Description: -
Id: 23, Name: construction-tunnel, Description: -
Id: 24, Name: construction-stairs, Description: -
Id: 25, Name: object-pole, Description: -
Id: 26, Name: object-trafficsign, Description: -
Id: 27, Name: object-trafficlight, Description: -
Id: 28, Name: nature-vegetation, Description: -
Id: 29, Name: nature-terrain, Description: -
Id: 30, Name: sky, Description: -
Id: 31, Name: void-ground, Description: -
Id: 32, Name: void-dynamic, Description: -
Id: 33, Name: void-static, Description: -
Id: 34, Name: void-unclear, Description: -


### Data Instances


### Data Fields


### Data Splits


This dataset only contains one split.


Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


### Licensing Information



### Dataset Summary


A dataset of sidewalk images gathered in Belgium in the summer of 2021. Label your own semantic segmentation datasets on URL ### Supported Tasks and Leaderboards


* 'semantic-segmentation': The dataset can be used to train a semantic segmentation model, where each pixel is classified. The model performance is measured by how high its mean IoU (intersection over union) to the reference is.


Dataset Structure
----------------- ### Data categories


Id: 0, Name: unlabeled, Description: -
Id: 1, Name: flat-road, Description: -
Id: 2, Name: flat-sidewalk, Description: -
Id: 3, Name: flat-crosswalk, Description: -
Id: 4, Name: flat-cyclinglane, Description: -
Id: 5, Name: flat-parkingdriveway, Description: -
Id: 6, Name: flat-railtrack, Description: -
Id: 7, Name: flat-curb, Description: -
Id: 8, Name: human-person, Description: -
Id: 9, Name: human-rider, Description: -
Id: 10, Name: vehicle-car, Description: -
Id: 11, Name: vehicle-truck, Description: -
Id: 12, Name: vehicle-bus, Description: -
Id: 13, Name: vehicle-tramtrain, Description: -
Id: 14, Name: vehicle-motorcycle, Description: -
Id: 15, Name: vehicle-bicycle, Description: -
Id: 16, Name: vehicle-caravan, Description: -
Id: 17, Name: vehicle-cartrailer, Description: -
Id: 18, Name: construction-building, Description: -
Id: 19, Name: construction-door, Description: -
Id: 20, Name: construction-wall, Description: -
Id: 21, Name: construction-fenceguardrail, Description: -
Id: 22, Name: construction-bridge, Description: -
Id: 23, Name: construction-tunnel, Description: -
Id: 24, Name: construction-stairs, Description: -
Id: 25, Name: object-pole, Description: -
Id: 26, Name: object-trafficsign, Description: -
Id: 27, Name: object-trafficlight, Description: -
Id: 28, Name: nature-vegetation, Description: -
Id: 29, Name: nature-terrain, Description: -
Id: 30, Name: sky, Description: -
Id: 31, Name: void-ground, Description: -
Id: 32, Name: void-dynamic, Description: -
Id: 33, Name: void-static, Description: -
Id: 34, Name: void-unclear, Description: - ### Data Instances ### Data Fields ### Data Splits


This dataset only contains one split.


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information
TAGS
#task_categories-image-segmentation #task_ids-semantic-segmentation #annotations_creators-crowdsourced #annotations_creators-expert-generated #language_creators-expert-generated #size_categories-n<1K #source_datasets-original #license-cc-by-nc-4.0 #region-us 
 ### Dataset Summary


A dataset of sidewalk images gathered in Belgium in the summer of 2021. Label your own semantic segmentation datasets on URL ### Supported Tasks and Leaderboards


* 'semantic-segmentation': The dataset can be used to train a semantic segmentation model, where each pixel is classified. The model performance is measured by how high its mean IoU (intersection over union) to the reference is.


Dataset Structure
----------------- ### Data categories


Id: 0, Name: unlabeled, Description: -
Id: 1, Name: flat-road, Description: -
Id: 2, Name: flat-sidewalk, Description: -
Id: 3, Name: flat-crosswalk, Description: -
Id: 4, Name: flat-cyclinglane, Description: -
Id: 5, Name: flat-parkingdriveway, Description: -
Id: 6, Name: flat-railtrack, Description: -
Id: 7, Name: flat-curb, Description: -
Id: 8, Name: human-person, Description: -
Id: 9, Name: human-rider, Description: -
Id: 10, Name: vehicle-car, Description: -
Id: 11, Name: vehicle-truck, Description: -
Id: 12, Name: vehicle-bus, Description: -
Id: 13, Name: vehicle-tramtrain, Description: -
Id: 14, Name: vehicle-motorcycle, Description: -
Id: 15, Name: vehicle-bicycle, Description: -
Id: 16, Name: vehicle-caravan, Description: -
Id: 17, Name: vehicle-cartrailer, Description: -
Id: 18, Name: construction-building, Description: -
Id: 19, Name: construction-door, Description: -
Id: 20, Name: construction-wall, Description: -
Id: 21, Name: construction-fenceguardrail, Description: -
Id: 22, Name: construction-bridge, Description: -
Id: 23, Name: construction-tunnel, Description: -
Id: 24, Name: construction-stairs, Description: -
Id: 25, Name: object-pole, Description: -
Id: 26, Name: object-trafficsign, Description: -
Id: 27, Name: object-trafficlight, Description: -
Id: 28, Name: nature-vegetation, Description: -
Id: 29, Name: nature-terrain, Description: -
Id: 30, Name: sky, Description: -
Id: 31, Name: void-ground, Description: -
Id: 32, Name: void-dynamic, Description: -
Id: 33, Name: void-static, Description: -
Id: 34, Name: void-unclear, Description: - ### Data Instances ### Data Fields ### Data Splits


This dataset only contains one split.


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators ### Licensing Information
passage: TAGS
#task_categories-image-segmentation #task_ids-semantic-segmentation #annotations_creators-crowdsourced #annotations_creators-expert-generated #language_creators-expert-generated #size_categories-n<1K #source_datasets-original #license-cc-by-nc-4.0 #region-us 
### Dataset Summary


A dataset of sidewalk images gathered in Belgium in the summer of 2021. Label your own semantic segmentation datasets on URL### Supported Tasks and Leaderboards


* 'semantic-segmentation': The dataset can be used to train a semantic segmentation model, where each pixel is classified. The model performance is measured by how high its mean IoU (intersection over union) to the reference is.


Dataset Structure
-----------------