--- annotations_creators: - crowdsourced - expert-generated language_creators: - expert-generated license: cc-by-nc-4.0 multilinguality: [] pretty_name: sidewalk-semantic size_categories: - n<1K source_datasets: - original task_categories: - image-segmentation task_ids: - semantic-segmentation --- # 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]