# Changelog of Google Maps Photos Scraper - Menu, Food, Vibe & Owner (`sian.agency/google-maps-photos-scraper`) Actor

- **URL**: https://apify.com/sian.agency/google-maps-photos-scraper/changelog.md
- **Full Actor documentation**: https://apify.com/sian.agency/google-maps-photos-scraper.md

## Changelog

All notable changes to Google Maps Photos Scraper will be documented in this file.

### \[2026-09-04]

#### 🎉 Google Maps Photos Scraper - Launch!

- **Category-Tagged Photos** - Every Google Maps photo arrives stamped with the tab Google files it under: Menu, Food & drink, Vibe, Rooms, Exterior, Amenities, By owner, From visitors, Street View & 360° and Videos. No image classification on your side.
- **Plain-Text Place Lookup** - Paste "Katz's Delicatessen New York" instead of hunting for a URL. Maps URLs and hex place IDs work too, and the place name, address, category and GPS come back on every row.
- **One Row Per Photo** - Filter by category, sort by upload date, feed an image pipeline. No bundle to unpack before you can use the data.
- **Full-Resolution Image URLs** - Four sizes, including each photo's own native dimensions. A thumbnail URL rides along on every row whatever you pick.
- **Owner vs Visitor Split** - A flag on every row saying whether the business posted the photo or a customer did, taken from Google's own upload source.
- **Videos Included** - Visitor video clips come through with a playable URL and a duration, or switch them off for stills only.
- **18 Languages** - Category labels in the language you choose, matched on Google's language-independent category IDs so filtering never breaks.

#### 💎 User Benefits

- Menu digitisation without a classification step: ask for the Menu tab and get menus.
- No Google Places API key, no quota, no billing account, no proxy to configure.
- $1.20 per 1,000 photos on paid plans — a third below the next-cheapest categorised photo Actor.
- Per-place caps keep a list of 200 restaurants from turning into a surprise bill.
- Pay per photo returned, never for a place that fails.

#### 🎯 Use Cases

- Delivery platforms pulling photographed menus across a whole city for OCR.
- Travel marketplaces filling hotel galleries with dated Rooms, Exterior and Amenities shots.
- Brand managers auditing which store locations have stale owner photos.
- ML teams assembling category-labelled, geotagged image sets for vision models.
- Local agencies watching a competitor's Latest tab as a proxy for foot traffic.
- Publishers sourcing landmark and neighbourhood imagery for city guides.