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⇱ πŸ“πŸ“Έ Google Street View Scraper (PPE) Β· Apify


πŸ‘ πŸ“πŸ“Έ Google Street View Scraper (PPE) avatar

πŸ“πŸ“Έ Google Street View Scraper (PPE)

Pricing

Pay per event

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πŸ“πŸ“Έ Google Street View Scraper (PPE)

Extract data from thousands of Google Maps Street View locations, including points of interest (businesses, shops, etc.), historical data, panorama images & more. Cover wide map areas by leveraging powerful input methods. Fast, cheap & reliable. Pay-per-event version.

Pricing

Pay per event

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πŸ‘ 3x1t

3x1t

Maintained by Community

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2

Bookmarked

89

Total users

9

Monthly active users

5 months ago

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πŸ” What is Google Street View Scraper?

Google Street View Scraper is a tool for extracting Street View metadata, including found places, points of interest (and their IDs/URLs), historical Street Views (+links), panorama (360Β°) images in JPEG format and more.

There is a variety of input types you can leverage and we are working on adding even more.

Potential use cases for this scraper include:

  • Finding all places in a given area
  • Real-estate & property analysis
  • Training datasets for computer vision
  • Urban planning & smart-city analytics
  • VR/AR environment reconstruction
  • Bulk location verification or address auditing
  • Automating research workflows

This version is configured as Pay per event (PPE), meaning you will pay a price according to the amount of scraped results. If you prefer fixed price per month (Rental), visit πŸ“πŸ“Έ Google Street View Scraper.

πŸš€ Features

  1. 🎯 Choose from multiple input types
    Supports a wide variety of input formats:
    • πŸ”— Street View URLs
    • πŸ“ Latitude/Longitude coordinates (+ optional radius scan)
    • πŸ”Ž Location text query
    • 🌐 Custom GeoJSON object
    • βž• …more coming soon (contact us with suggestions!)
  2. πŸ“ Customizable panorama resolution
    Pick the exact output size you want β€” from lightweight thumbnails to high-resolution panoramas.
  3. πŸ› οΈ Image corruption detection + auto-repair
  4. βœ… No upfront costs (e.g. per area search...)
  5. πŸ“€ Export your results in JSON, XML, CSV, and other formats supported by Apify.

πŸ“Š What is being extracted?

πŸ“ Points of InterestπŸ•’ Historical Street ViewsπŸ–ΌοΈ Panorama images
🏷️ AddressesπŸ“… DatesπŸ”— URLs
🧭 Latitude🧭 LongitudeπŸ†” ID

And more! Checkout the output section for more detailed view.

Want to get more fields? Looking for something specific? Contact me via issues or at contact@3x1t.dev with any feature suggestions.

❓ How to use

This section contains information about each input option.

πŸ”— Street View URLs

This is pretty straightforward, just copy the URL from your browser and insert it here.

You can also use other URL sources than browser, but make sure that the links are valid (the Actor has an auto-validator for input, so it will tell you if it is a valid URL).

πŸ“ Latitude/Longitude coordinates (+ optional radius scan)

Use the input interface to input points into each field. If you omit the radius field, it will be set to default value (default is 5 meters).

πŸ”Ž Location text query

This format type is possibly quite useful, but it also can be deceptive. It lets you define location boundary (polygon) using free text.

How this works:

  1. Your query gets sent into "https://nominatim.openstreetmap.org/" to get a polygon from your query.
  2. The Actor uses the found polygon as the input.

It is recommended to NOT use street addresses β€” street is not an area. Also other very small locations/generic names will not work.

Input examples:

  • Good text queries:
    • Hoboken, New Jersey
    • Manhattan, New York
    • Green Wood Cemetery, New York
  • Bad text queries:
    • Lower Manhattan, New York
    • Franklin Street, New York
    • Journal Square, Jersey City (it is a point)

You can validate your text query beforehand at https://nominatim.openstreetmap.org/ or just use GeoJSON input format instead for better stability.

🌐 Custom GeoJSON object

  1. Go to https://geojson.io.
  2. Find the location you want to scrape panoramas for on the map
  3. Select Draw Polygon option from the toolbar
  4. Draw the polygon (you finish the polygon by clicking on the initial point of the polygon)
  5. The JSON entry will get updated in the text box on the right side.
  6. Copy the whole JSON text and paste it into the GeoJSON polygon input field of this Actor.
  7. (Optional) Setup other settings like resolution and limit.
  8. Click Start to see your results!

πŸ“‘ Example input

Street View URL

{
"panoramaImageResolution":"512x256",
"scrapePanoramaImages":true,
"streetViewUrls":[
"https://www.google.com/maps/@51.50567952815255,-0.07523477743727235,3a,75y,0h,90t/data=!3m5!1e1!3m3!1syzC6tviBA2kbnO1Q5a4a1Q!2e0!5s20241001T000000"
]
}

GeoJSON

{
"geoJSON":{
"type":"FeatureCollection",
"features":[
{
"type":"Feature",
"properties":{},
"geometry":{
"coordinates":[
[
[
-0.07488689695912853,
51.507109792556406
],
[
-0.0769781886279759,
51.504310315763036
],
[
-0.07565163565999455,
51.50405840295656
],
[
-0.07378514161396765,
51.50670383680142
],
[
-0.07488689695912853,
51.507109792556406
]
]
],
"type":"Polygon"
}
}
]
},
"panoramaImageResolution":"512x256",
"resultLimitPerThread":50,
"scrapePanoramaImages":true
}

πŸ–ΌοΈ Example output

The resulting images are automatically stitched into whole panoramas, making large-scale scraping operations very easy. There's also prepared a special Key-Value-Store collection called "Panorama Images" for making the process of extracting scraped images even smoother.

This example is only the dataset entry, the images will be automatically stored in the Key-Value store and referenced in the dataset entries via URLs in the panoramaImageUrl field.

{
"id":"NQmbvEpCoEnD2CfguyuqPw",
"location":{
"latitude":51.50421828553964,
"longitude":-0.07600345440559082
},
"streetViewUrl":"https://www.google.com/maps/@51.50421828553964,-0.07600345440559082,3a,75y,0h,90t/data=!3m4!1e1!3m2!1sNQmbvEpCoEnD2CfguyuqPw!2e0",
"googleMapsUrl":"https://www.google.com/maps/place/51.50421828553964,-0.07600345440559082",
"panoramaImageUrl":"",// Panorama image URL hidden in example
"address":{
"street":"48 Shad Thames",
"cityAndCountry":"London, England",
"countryCode":"GB"
},
"date":{
"year":2022,
"month":6
},
"pointsOfInterest":[
{
"name":"Starbucks",
"url":"https://www.google.com/maps/place///data=!4m2!3m1!1s0x4876034619fd361b%3A0x126019398b3f2d0",
"streetViewCenteredUrl":"https://www.google.com/maps/@51.50421828553964,-0.07600345440559082,3a,75y,121.16095804735681h,91.29863874283065t/data=!3m4!1e1!3m2!1sNQmbvEpCoEnD2CfguyuqPw!2e0",
"relativePositionInPanorama":{
"x":0.00969652272760868,
"y":0.5056449174880981
},
"distanceFromCamera":49.11770248413086,
"placeCategory":"Coffee shop"
},
{
"name":"Horselydown stairs",
"url":"https://www.google.com/maps/place///data=!4m2!3m1!1s0x4876030846d2414b%3A0x6748a367f93745d5",
"streetViewCenteredUrl":"https://www.google.com/maps/@51.50421828553964,-0.07600345440559082,3a,75y,93.57900540068903h,91.5340521919089t/data=!3m4!1e1!3m2!1sNQmbvEpCoEnD2CfguyuqPw!2e0",
"relativePositionInPanorama":{
"x":0.9331086277961731,
"y":0.502669632434845
},
"distanceFromCamera":26.1407585144043,
"placeCategory":"Tourist attraction"
}
],
"historicalPanoramas":[
{
"id":"1yysorCh2z4NMHq93N0TwQ",
"type":"official",
"streetViewUrl":"https://www.google.com/maps/@51.50424167658521,-0.07604303179084063,3a,75y,0h,90t/data=!3m5!1e1!3m3!1s1yysorCh2z4NMHq93N0TwQ!2e0!5s20210501T000000",
"location":{
"latitude":51.50424167658521,
"longitude":-0.07604303179084063
},
"date":{
"year":2021,
"month":5
}
},
{
"id":"nsMd9-UHKC8Y7ayZ696vAg",
"type":"official",
"streetViewUrl":"https://www.google.com/maps/@51.504237913559,-0.07603361351516633,3a,75y,0h,90t/data=!3m5!1e1!3m3!1snsMd9-UHKC8Y7ayZ696vAg!2e0!5s20170901T000000",
"location":{
"latitude":51.504237913559,
"longitude":-0.07603361351516633
},
"date":{
"year":2017,
"month":9
}
},
{
"id":"Pgl5qaoLtgiHw96EMkyLTQ",
"type":"official",
"streetViewUrl":"https://www.google.com/maps/@51.50422542533391,-0.07599953144126885,3a,75y,0h,90t/data=!3m5!1e1!3m3!1sPgl5qaoLtgiHw96EMkyLTQ!2e0!5s20160501T000000",
"location":{
"latitude":51.50422542533391,
"longitude":-0.07599953144126885
},
"date":{
"year":2016,
"month":5
}
}
],
"originIdentifier":"{\"name\":\"polygon-0\"}"
}

πŸ”— Integrating with other platforms

Google Street View Scraper supports integrations with external services, enabling automated workflows and data exchange. Through the Apify platform integrations, it connects with tools like Make and Zapier, facilitating interactions with Slack, Airbyte, GitHub, Google Sheets, and Google Drive (learn about integrations). Additionally, its API and webhook support allow real-time interactions, such as triggering automated workflows or receiving notifications when a scraping task is completed.

πŸ› οΈ Support

If there is a feature that you would love to see (more fields, better input, etc.), do not hesitate to create an issue or contact me at contact@3x1t.dev.

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Can't find what you're looking for? No worries, we've got your back! Hit us up at contact@3x1t.dev or create an issue. If all else fails, you can always visit the Apify store β€” it could have exactly what you need. πŸ˜‰

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