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Datasets:
rsdmu
/
streetreview

Tasks:
Zero-Shot Classification
Image Classification
Image Segmentation
Modalities:
Image
Languages:
English
Size:
10K<n<100K
Tags:
urban-planning
montreal
publicspace
inclusivity
accessibility
participatory
License:
Dataset card Viewer Files Community
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  # StreetReview Dataset
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- ![StreetReview Banner](https://example.com/banner.jpg)
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  ## Overview
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  **StreetReview** is a curated dataset designed to evaluate the inclusivity, accessibility, aesthetics, and practicality of urban streetscapes, particularly in a multicultural city context. Focused on Montréal, Canada, the dataset combines diverse demographic evaluations with rich metadata and street-view imagery. It aims to advance research in urban planning, public space design, and machine learning applications for creating inclusive and user-friendly urban environments.
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  ## Table of Contents
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  ---
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- © 2024 RSDMU. All rights reserved.
 
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+ ---
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+ datasets:
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+ - rsdmu/streetreview
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+ task_categories:
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+ - zero-shot-classification
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+ - image-classification
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+ - image-segmentation
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+ - image-feature-extraction
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+ tags:
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+ - urban-planning
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+ - montreal
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+ - publicspace
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+ - inclusivity
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+ - accessibility
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+ - participatory
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+ license: cc-by-4.0
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+ language:
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+ - en
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+ size_categories:
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+ - 1K<n<10K
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+ pretty_name: Street Review Dataset
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+ annotations_creators:
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+ - crowdsourced
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+ - expert-generated
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+ ---
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+
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+
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  # StreetReview Dataset
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/657d0fd583543a061b23b027/8rTxCdOovDoGAGjTYVSMw.png)
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  ## Overview
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+
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  **StreetReview** is a curated dataset designed to evaluate the inclusivity, accessibility, aesthetics, and practicality of urban streetscapes, particularly in a multicultural city context. Focused on Montréal, Canada, the dataset combines diverse demographic evaluations with rich metadata and street-view imagery. It aims to advance research in urban planning, public space design, and machine learning applications for creating inclusive and user-friendly urban environments.
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  ## Table of Contents
 
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  ---
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+ © 2024 RSDMU. All rights reserved.