|
--- |
|
datasets: |
|
- rsdmu/streetreview |
|
task_categories: |
|
- zero-shot-classification |
|
- image-classification |
|
- image-segmentation |
|
- image-feature-extraction |
|
tags: |
|
- urban-planning |
|
- montreal |
|
- publicspace |
|
- inclusivity |
|
- accessibility |
|
- participatory |
|
license: cc-by-4.0 |
|
language: |
|
- en |
|
size_categories: |
|
- 10K<n<100K |
|
pretty_name: Street Review Dataset |
|
annotations_creators: |
|
- crowdsourced |
|
- expert-generated |
|
--- |
|
|
|
|
|
# StreetReview Dataset |
|
|
|
 |
|
|
|
## Overview |
|
|
|
|
|
**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. |
|
|
|
## Table of Contents |
|
|
|
- [Overview](#overview) |
|
- [Dataset Structure](#dataset-structure) |
|
- [Root Directory](#root-directory) |
|
- [Street Image Data](#street-image-data) |
|
- [Street Evaluation Data](#street-evaluation-data) |
|
- [Methodology](#methodology) |
|
- [Participatory Evaluation Process](#participatory-evaluation-process) |
|
- [Data Collection](#data-collection) |
|
- [Data Fields](#data-fields) |
|
- [Metadata](#metadata) |
|
- [Evaluations](#evaluations) |
|
- [Usage](#usage) |
|
- [Cloning the Repository](#cloning-the-repository) |
|
- [Example Code](#example-code) |
|
- [License](#license) |
|
- [Citing StreetReview](#citing-streetreview) |
|
- [Contributing](#contributing) |
|
- [Contact](#contact) |
|
|
|
## Dataset Structure |
|
|
|
The **StreetReview** dataset is organized as follows: |
|
|
|
### Root Directory |
|
|
|
- **`metadata.csv`**: Comprehensive metadata for each evaluation point. |
|
- **`street_eval/`**: CSV files containing evaluation data for individual street sections. |
|
- **`street_img/`**: Street-view images categorized by street and section. |
|
|
|
### Street Image Data |
|
|
|
Images are stored in `street_img/` and organized into folders by street and section, with three perspectives per section (`_main`, `_head`, `_tail`). Example structure: |
|
|
|
``` |
|
street_img/ |
|
├── i01_cote_sainte_catherine_main/ |
|
│ ├── main_001.jpg |
|
│ ├── main_002.jpg |
|
│ ... |
|
└── i02_rue_berri_main/ |
|
├── main_001.jpg |
|
├── main_002.jpg |
|
... |
|
``` |
|
|
|
### Street Evaluation Data |
|
|
|
Evaluation data is stored in `street_eval/` as CSV files named after their corresponding street section. Example: |
|
|
|
``` |
|
street_eval/ |
|
├── i01_evaluations.csv |
|
├── i02_evaluations.csv |
|
... |
|
``` |
|
|
|
## Methodology |
|
|
|
### Participatory Evaluation Process |
|
|
|
The dataset was created using a participatory approach to capture diverse urban experiences: |
|
|
|
1. **Individual Evaluation**: Participants rated 20 street on four criteria using a color-coded system. |
|
2. **Group Evaluation**: In focus groups, participants reassessed images collectively and refined their evaluations. |
|
|
|
### Data Collection |
|
|
|
- **Participants**: 28 individuals contributed to criteria development; 12 participated in detailed evaluations. |
|
- **Evaluation Points**: 60 points across 20 streets, with two images per point. |
|
- **Dataset Expansion**: Up to 250 images per point, rotated for diversity. |
|
|
|
## Data Fields |
|
|
|
### Metadata |
|
|
|
The `metadata.csv` file contains attributes such as: |
|
|
|
| Field | Description | |
|
|------------------------|--------------------------------------| |
|
| `point_id` | Unique identifier | |
|
| `sidewalk_width` | Width of sidewalks | |
|
| `greenery_presence` | Presence of greenery | |
|
| `building_height` | Height of adjacent buildings | |
|
| ... | ... | |
|
|
|
### Evaluations |
|
|
|
Each CSV file in `street_eval/` includes ratings from various demographic groups. Ratings are based on a 1-4 scale. For example, a score of 1 for accessibility means "not accessible," scores of 2 or 3 indicate "average accessibility," and a score of 4 represents "highest accessibility." |
|
|
|
| Field | Description | |
|
|---------------------------|---------------------------------| |
|
| `lgbtqia2+_accessibility` | Accessibility rating by LGBTQIA2+ | |
|
| `elderly_male_practicality` | Practicality rating by elderly males | |
|
| `group_inclusivity` | Inclusivity rating by groups of 3-5 diverse individuals | |
|
| ... | ... | |
|
|
|
## Usage |
|
|
|
### Cloning the Repository |
|
|
|
Clone the repository with: |
|
|
|
```bash |
|
git clone https://huggingface.co/datasets/rsdmu/streetreview |
|
``` |
|
|
|
### Example Code |
|
|
|
```python |
|
import pandas as pd |
|
from PIL import Image |
|
import os |
|
|
|
# Load metadata |
|
metadata = pd.read_csv('metadata.csv') |
|
|
|
# Load evaluation data |
|
eval_data = pd.read_csv('street_eval/i01_evaluations.csv') |
|
|
|
# Display an image |
|
image_path = 'street_img/i01_cote_sainte_catherine_main/main_001.jpg' |
|
image = Image.open(image_path) |
|
image.show() |
|
``` |
|
|
|
## License |
|
|
|
Licensed under [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/). |
|
|
|
## Citing StreetReview |
|
|
|
```bibtex |
|
@dataset{streetreview2024, |
|
title = {StreetReview Dataset: Evaluating Urban Streetscapes for Inclusivity and Accessibility}, |
|
author = {Rashid Mushkani}, |
|
year = {2025}, |
|
url = {https://huggingface.co/datasets/rsdmu/streetreview} |
|
} |
|
``` |
|
|
|
## Contributing |
|
|
|
We welcome contributions! Please fork the repository, make changes, and submit a pull request. |
|
|
|
## Contact |
|
|
|
For inquiries, contact: |
|
|
|
- **Email**: [Rashid Mushkani](mailto:[email protected]) |
|
- **Website**: [Rashid Mushkani](https://rsdmu.com) |
|
- **GitHub**: [RSDMU](https://github.com/rsdmu) |
|
|
|
--- |
|
|
|
© 2024 RSDMU. All rights reserved. |
