Streetview by Country

Intro

Hi, I thought I would pull together a dataset comprising of streetview images from different countries. I saw there were a couple datasets on Kaggle with a similar intention, but I wanted to help solve 2 main problems.

1) Balanced classes across countries. 2) Images tagged with coordinates.

What is included

What I have here are roughly 1000 images (and each image is 640x640 pixels) per country/region (many island nations get separate groupings to their nominal sovereign state, e.g., Bermuda, Faroe etc.) that have sufficient official google streetview coverage. There are some countries that do have streetview coverage, but I have not included, because the coverage is extremely limited. For example, Belarus only has limited trekker coverage in the centre of Minsk, so I don't feel it is representative of the region at large in a geography-prediction dataset. More info on which countries are in the dataset and which aren't is in Country-picking.md.

There are 111 regions in total. Each is indexed by its 2-letter shortening as you can find here https://www.iban.com/country-codes, they are also in country-picking.md, for reference.

Methodology

To collect each set I first used an incredible tool to generate valid coordinates within a specified country, you can find this at https://github.com/slashP/Vali. Big thanks to the creator I could not have created this otherwise. The coordinates generated per country are intended to be spread apart, within respective sub-regions, which I hope will help create a representative dataset of that country overall. Downloaded images were then assorted to their respective country's folder and titled with the coordinates that they correspond to. For example

"42d436079_1d473612_h213.jpg"

means that the image was taken at a latitude of 42.436079, a longitude of 1.473612 and a heading (between 0 and 360) of 213.

Another note! Some regions are just that small that I couldn't curate 1000 locations within them, or I had to scale down the minimum distance between points. Notes explaining on which countries this is relevant are in Country-picking.md.

This is my first dataset so please if you have any suggestions please let me know I'd be happy to help make this a better dataset. In the future I'd love to expand this dataset into specific subregions of countries.

****Hello! This project contains images of Turkey's cities like Bursa, İstanbul, Konya. It also contains photos from other countries.

****This model's aim is the make traffic detection programme. It detects, person, car, bus, motorbike and bicycle.

****Why I need this model? It's because I'm working on a project about object detection and tracking. Pretrained YOLOV5 model has poor accuracy in images taken from above like traffic cameras. So I needed a better model for detection of objects. This model that I developed is have so much better than the pretrained yolov5 model.

**** Hope this model performs good for you :)

This dataset provides a list Latitude and longitude coordinates of valid Google Maps Street View locations. Also includes ISO code of country. Collected using public Google Street View Static API.

dll-streetview/sem-seg-country-safety-bins dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset provides information about the number of properties, residents, and average property values for Country View Road cross streets in Malvern, PA.

Street Noise-Level — Statistically Interpolated + Processed Measurements

Connect with our experts for the world’s most comprehensive Street Noise-Level Dataset. Access hyper-local and global average noise levels (dBA) from public streets across over 180+ countries. This dataset, built using over 35 billion datapoints and developed in collaboration with leading acoustics professionals, provides unparalleled insight into real-world urban soundscapes. Unlike conventional noise models, which rely solely on simulations, our dataset combines real measurements with AI-powered interpolation to deliver statistically robust, highly accurate, and spatially complete noise-level data.

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With coverage of over 180+ countries and high spatial granularity, the dataset provides insights from the city level down to street segments.

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Delivered via CSV exports or S3 bucket delivery (APIs coming soon) for easy integration into AI training pipelines, geospatial tools, or analytics platforms.

Are you looking to identify B2B leads to promote your business, product, or service? Outscraper Google Maps Scraper might just be the tool you've been searching for. This powerful software enables you to extract business data directly from Google's extensive database, which spans millions of businesses across countless industries worldwide.

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Query Name Site Type Subtypes Category Phone Full Address Borough Street City Postal Code State Us State Country Country Code Latitude Longitude Time Zone Plus Code Rating Reviews Reviews Link Reviews Per Scores Photos Count Photo Street View Working Hours Working Hours Old Format Popular Times Business Status About Range Posts Verified Owner ID Owner Title Owner Link Reservation Links Booking Appointment Link Menu Link Order Links Location Link Place ID Google ID Reviews ID

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Email Facebook Github Instagram Linkedin Phone Twitter Youtube

MBI is one of the first distributors of HERE Technologies and provides detailed street maps from HERE for most of the countries or territories worldwide.

HERE Maps are available as Essential or Advanced Map. Essential Map is a basic 2D canvas of the world that enables use cases such as basic map display, data visualization, search, localization tracking and tracing.

Building on Essential Map, Advanced Map is the most complete and detailed map available. It includes detailed features for modeling road networks, such as navigable attributes, speed limits, sign text and the full set of Places (Point of Interest), and enables use cases such as point-to-point routing, turn-by-turn navigation, advanced navigation for cars and trucks, business intelligence, planning and optimization, and much more.

The HERE Map product line can be further enriched with additional curated and specialized location content products that enable you to build differentiating location-enabled services and applications. Over 50 premium location content products seamlessly integrate with the HERE Map Data product line, such as Places, Point Addressing, Trucks, Road Infrastructure, and many more. Available in the following formats: GDF, RDF, NavStreets, FGDB,

dll-streetview/sem-seg-country-beauty-bins dataset hosted on Hugging Face and contributed by the HF Datasets community

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

This dataset provides information about the number of properties, residents, and average property values for Country View Drive cross streets in Valley Springs, CA.

Global and hyper-local street noise-level dataset covering 180+ countries. Built from 35B datapoints, combining real measurements and AI interpolation. Ideal for urban planning, and mobility analysis. Fully anonymized and GDPR-compliant.

Contains:World HillshadeWorld Street Map (with Relief) - Base LayerLarge Scale International Boundaries (v11.3)World Street Map (with Relief) - LabelsDoS Country Labels DoS Country LabelsCountry (admin 0) labels that have been vetted for compliance with foreign policy and legal requirements. These labels are part of the US Federal Government Basemap, which contains the borders and place names that have been vetted for compliance with foreign policy and legal requirements.Source: DoS Country Labels - Overview (arcgis.com)Large Scale International BoundariesVersion 11.3Release Date: December 19, 2023DownloadFor more information on the LSIB click here: https://geodata.state.gov/ A direct link to the data is available here: https://data.geodata.state.gov/LSIB.zipAn ISO-compliant version of the LSIB metadata (in ISO 19139 format) is here: https://geodata.state.gov/geonetwork/srv/eng/catalog.search#/metadata/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2 Direct inquiries to internationalboundaries@state.govOverviewThe Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.3 (published 19 December 2023). The 11.3 release contains updates to boundary lines and data refinements enabling reuse of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.National Geospatial Data AssetThis dataset is a National Geospatial Data Asset managed by the Department of State on behalf of the Federal Geographic Data Committee's International Boundaries Theme.DetailsSources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.Attribute StructureThe dataset uses thefollowing attributes:Attribute NameCC1COUNTRY1CC2COUNTRY2RANKSTATUSLABELNOTES These attributes are logically linked:Linked AttributesCC1COUNTRY1CC2COUNTRY2RANKSTATUS These attributes have external sources:Attribute NameExternal Data SourceCC1GENCCOUNTRY1DoS ListsCC2GENCCOUNTRY2DoS ListsThe eight attributes listed above describe the boundary lines contained within the LSIB dataset in both a human and machine-readable fashion. Other attributes in the release include "FID", "Shape", and "Shape_Leng" are components of the shapefile format and do not form an intrinsic part of the LSIB."CC1" and "CC2" fields are machine readable fields which contain political entity codes. These codes are derived from the Geopolitical Entities, Names, and Codes Standard (GENC) Edition 3 Update 18. The dataset uses the GENC two-character codes. The code ‘Q2’, which is not in GENC, denotes a line in the LSIB representing a boundary associated with an area not contained within the GENC standard.The "COUNTRY1" and "COUNTRY2" fields contain human-readable text corresponding to the name of the political entity. These names are names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the list of Independent States in the World and the list of Dependencies and Areas of Special Sovereignty maintained by the Department of State. To ensure the greatest compatibility, names are presented without diacritics and certain names are rendered using commonly accepted cartographic abbreviations. Names for lines associated with the code ‘Q2’ are descriptive and are not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS are names of independent states. Other names are those associated with dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.The following fields are an intrinsic part of the LSIB dataset and do not rely on external sources:Attribute NameMandatoryContains NullsRANKYesNoSTATUSYesNoLABELNoYesNOTESNoYesNeither the "RANK" nor "STATUS" field contains null values; the "LABEL" and "NOTES" fields do.The "RANK" field is a numeric, machine-readable expression of the "STATUS" field. Collectively, these fields encode the views of the United States Government on the political status of the boundary line.Attribute NameValueRANK123STATUSInternational BoundaryOther Line of International Separation Special Line A value of "1" in the "RANK" field corresponds to an "International Boundary" value in the "STATUS" field. Values of "2" and "3" correspond to "Other Line of International Separation" and "Special Line", respectively.The "LABEL" field contains required text necessarily to describe the line segment. The "LABEL" field is used when the line segment is displayed on maps or other forms of cartographic visualizations. This includes most interactive products. The requirement to incorporate the contents of the "LABEL" field on these products is scale dependent. If a label is legible at the scale of a given static product a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field is not a line labeling field but does contain the preferred description for the three LSIB line types when lines are incorporated into a map legend. Using the "CC1", "CC2", or "RANK" fields for labeling purposes is prohibited.The "NOTES" field contains an explanation of any applicable special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, any limitations regarding the purpose of the lines, or the original source of the line. Use of the "NOTES" field for labeling purposes is prohibited.External Data SourcesGeopolitical Entities, Names, and Codes Registry: https://nsgreg.nga.mil/GENC-overview.jspU.S. Department of State List of Independent States in the World: https://www.state.gov/independent-states-in-the-world/U.S. Department of State List of Dependencies and Areas of Special Sovereignty: https://www.state.gov/dependencies-and-areas-of-special-sovereignty/The source for the U.S.—Canada international boundary (NGDAID97) is the International Boundary Commission: https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpThe source for the “International Boundary between the United States of America and the United States of Mexico” (NGDAID82) is the International Boundary and Water Commission: https://catalog.data.gov/dataset?q=usibwcCartographic UsageCartographic usage of the LSIB requires a visual differentiation between the three categories of boundaries. Specifically, this differentiation must be between:- International Boundaries (Rank 1);- Other Lines of International Separation (Rank 2); and- Special Lines (Rank 3).Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary.Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues.ContactDirect inquiries to internationalboundaries@state.gov.CreditsThe lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre.Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.Changes from Prior ReleaseThe 11.3 release is the third update in the version 11 series.This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Notable changes to lines include:• AFGHANISTAN / IRAN• ALBANIA / GREECE• ALBANIA / KOSOVO• ALBANIA/MONTENEGRO• ALBANIA / NORTH MACEDONIA• ALGERIA / MOROCCO• ARGENTINA / BOLIVIA• ARGENTINA / CHILE• BELARUS / POLAND• BOLIVIA / PARAGUAY• BRAZIL / GUYANA• BRAZIL / VENEZUELA• BRAZIL / French Guiana (FR.)• BRAZIL / SURINAME• CAMBODIA / LAOS• CAMBODIA / VIETNAM• CAMEROON / CHAD• CAMEROON / NIGERIA• CHINA / INDIA• CHINA / NORTH KOREA• CHINA / Aksai Chin• COLOMBIA / VENEZUELA• CONGO, DEM. REP. OF THE / UGANDA• CZECHIA / GERMANY• EGYPT / LIBYA• ESTONIA / RUSSIA• French Guiana (FR.) / SURINAME• GREECE / NORTH MACEDONIA• GUYANA / VENEZUELA• INDIA / Aksai Chin• KAZAKHSTAN / RUSSIA• KOSOVO / MONTENEGRO• KOSOVO / SERBIA• LAOS / VIETNAM• LATVIA / LITHUANIA• MEXICO / UNITED STATES• MONTENEGRO / SERBIA• MOROCCO / SPAIN• POLAND / RUSSIA• ROMANIA / UKRAINEVersions 11.0 and 11.1 were updates to boundary lines. Like this version, they also contained topology fixes, land boundary terminus refinements, and tripoint adjustments. Version 11.2 corrected a few errors in the attribute data and ensured that CC1 and CC2 attributes are in alignment with an updated version of the Geopolitical Entities, Names, and Codes (GENC) Standard, specifically Edition 3 Update 17.LayersLarge_Scale_International_BoundariesTerms of

This comprehensive vector street map includes most of the the map labels except for country labels. This map is designed to be used as one of the basemap layers for the US Federal Government Basemap (Beta) web map.Use this Map This map is designed to be used as one of the basemap layers in the preview web map: US Federal Government Basemap (Beta). It does not contain any basemap content, international boundary content or country names. These features are found on other vector tile layers that comrpise the web map.

This dataset provides information about the number of properties, residents, and average property values for Country View Road cross streets in Odenville, AL.

This dataset provides information about the number of properties, residents, and average property values for Country View Drive cross streets in Towanda, PA.

This dataset provides information about the number of properties, residents, and average property values for Country View Road cross streets in White Salmon, WA.

Mature Support Notice: This item is in mature support as of July 2021. A replacement item has not been identified at this time. Esri recommends updating your maps and apps to phase out use of this item.This map presents transportation data, including highways, roads, railroads, and airports for the world.The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.You can add this layer on top of any imagery, such as the Esri World Imagery map service, to provide a useful reference overlay that also includes street labels at the largest scales. (At the largest scales, the line symbols representing the streets and roads are automatically hidden and only the labels showing the names of streets and roads are shown). Imagery With Labels basemap in the basemap dropdown in the ArcGIS web and mobile clients does not include this World Transportation map. If you use the Imagery With Labels basemap in your map and you want to have road and street names, simply add this World Transportation layer into your map. It is designed to be drawn underneath the labels in the Imagery With Labels basemap, and that is how it will be drawn if you manually add it into your web map.

The Global Administrative Unit Layers (GAUL) is an initiative implemented by FAO within the Bill & Melinda Gates Foundation, Agricultural Market Information System (AMIS) and AfricaFertilizer.org projects. The GAUL compiles and disseminates the best available information on administrative units for all the countries in the world, providing a contribution to the standardization of the spatial dataset representing administrative units. The GAUL always maintains global layers with a unified coding system at country, first (e.g. departments) and second administrative levels (e.g. districts). Where data is available, it provides layers on a country by country basis down to third, fourth and lowers levels. The overall methodology consists in a) collecting the best available data from most reliable sources, b) establishing validation periods of the geographic features (when possible), c) adding selected data to the global layer based on the last country boundaries map provided by the UN Cartographic Unit (UNCS), d) generating codes using GAUL Coding System and e) distribute data to the users (see TechnicalaspectsGAUL2015.pdf). Because GAUL works at global level, unsettled territories are reported. The approach of GAUL is to deal with these areas in such a way to preserve national integrity for all disputing countries (see TechnicalaspectsGAUL2015.pdf and G2015_DisputedAreas.dbf). GAUL is released once a year and the target beneficiary of GAUL data is the UN community and other authorized international and national partners. Data might not be officially validated by authoritative national sources and cannot be distributed to the general public. A disclaimer should always accompany any use of GAUL data. 5 territories have been updated respect to the previous release. Moreover, the coastline of American countries or other special areas have been updated using Open Street Map (see ReleaseNoteGAUL2015.pdf). GAUL keeps track of administrative units that has been changed, added or dismissed in the past for political causes. Changes implemented in different years are recorded in GAUL on different layers. For this reason the GAUL product is not a single layer but a group of layers, named "GAUL Set" (see ReleaseNoteGAUL2015.pdf). GAUL 2015 is the eighth release of the GAUL Set.

A comprehensive self-hosted geospatial database of street names, coordinates, and address data ranges for Enterprise use. The address data are georeferenced with industry-standard WGS84 coordinates (geocoding).

All geospatial data are provided in the official local languages. Names and other data in non-Roman languages are also made available in English through translations and transliterations.

Use cases for the Global Address Database (Geospatial data)

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Additional features

• Fully and accurately geocoded

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• Address ranges for streets covered by several zip codes

• Comprehensive city definitions across countries

• Administrative areas with a level range of 0-4

• International Address Formats

For additional insights, you can combine the map data with:

• UNLOCODE and IATA codes (geocoded)

• Time zones and Daylight Saving Time (DST)

• Population data: Past and future trends

Data export methodology

Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

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