Datasets:
license: mit
Dataset Card for panoramic street view images
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact:
Dataset Summary
The random streetview images dataset are labeled, panoramic images scraped from randomstreetview.com. Each image shows a location accessible by Google Streetview that has been roughly combined to provide ~360 degree view of a single location. The dataset was designed with the intent to geolocate an image purely based on its visual content.
Supported Tasks and Leaderboards
None as of now!
Languages
labels: Addresses are written in a combination of English and the official language of country they belong to. images: There are some images with signage that can contain a language. Albeit, they are less common.
Dataset Structure
For now, images exist exclusively in the train
split and it is at the user's discretion to split the dataset how they please.
Data Instances
For each instance, there is:
- timestamped file name: '{YYYYMMDD}_{address}.jpg`
- the image
- the country iso-alpha2 code
- the latitude
- the longitude
- the address
Fore more examples see the dataset viewer
{
filename: '20221001_Jarše Slovenia_46.1069942_14.9378597.jpg'
country_iso_alpha2 : 'SI'
latitude: '46.028223'
longitude: '14.345106'
address: 'Jarše Slovenia_46.1069942_14.9378597'
}
Data Fields
- country_iso_alpha2: a unique 2 character code for each country in the world following the ISO 3166 standard
- latitude: the angular distance of a place north or south of the earth's equator
- longitude: the angular distance of a place east or west of the standard meridian of the Earth
- address: the physical address written from most micro -> macro order (Street, Neighborhood, City, State, Country)
Data Splits
'train': all images are currently contained in the 'train' split
Dataset Creation
Curation Rationale
Google StreetView Images requires money per image scraped
This dataset provides a free, working sample of those images for whatever purpose you may desire!
Source Data
Who are the source image producers?
Google Street View provide the raw image, this dataset combined various cuts of the images into a panoramic.
[More Information Needed]
Annotations
Annotation process
The address, latitude, and longitude are all scraped from the API response. While portions of the data has been manually validated, the assurance in accuracy is based on the correctness of the API response.
Personal and Sensitive Information
While Google Street View does blur out images and license plates to the best of their ability, it is not guaranteed as can been seen in some photos. Please review Google's documentation for more information
Considerations for Using the Data
Social Impact of Dataset
This dataset was designed after inspiration from playing the popular online game, [geoguessr.com[(geoguessr.com). We ask that users of this dataset consider if their geolocation based application will harm or jeopardize any fair institution or system.
Discussion of Biases
Out of the ~195 countries that exists, this dataset only contains images from about 55 countries.
Other Known Limitations
As per Google's policy: "Street View imagery shows only what our cameras were able to see on the day that they passed by the location. Afterwards, it takes months to process them. This means that content you see could be anywhere from a few months to a few years old."
Licensing Information
MIT License
Citation Information
Contributions
Thanks to @WinsonTruong and @ David Hrachovy for helping developing this dataset. This dataset was developed for a Geolocator project with the aforementioned developers, @samhita-alla and @yiyixuxu Thanks to FSDL for a wonderful class and online cohort.