# Free Google Maps Images Scraper — Bulk Photo URLs (`s-r/free-google-maps-images-scraper`) Actor - **URL**: https://apify.com/s-r/free-google-maps-images-scraper.md - **Developed by:** [SR](https://apify.com/s-r) (community) - **Categories:** Lead generation, Business - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Free Google Maps Images Scraper — Bulk Photo URLs from Any Place A Google Maps photo scraper that returns every image URL Google has on file for any business listing — full direct image URLs, no thumbnail proxies, no `lh3-googleusercontent.com` redirects to resolve. Pass any canonical Google Maps place URL and get back up to 200 photos per place at $0.0008 each. No Google Places API photo references (which expire after 1 hour and bill $7-$70 per 1000), no headless browser, no manual right-click-and-save loop. ### What you get - Direct image URLs at `lh5.googleusercontent.com/p/=w-h` — pasteable into a browser, downloadable with `curl`, no expiring tokens - Image dimensions when Google embeds them in the URL (most images come in `w408-h408`, `w1080-h720`, or `=s10000` variants you can resize on the fly by editing the suffix) - Place name and canonical URL echoed back so you can join photos back to their place rows - `photos_count_returned` — the actual count delivered for this run, useful for budget reconciliation - Photo ordering matches Google's relevance sort — the first photos in the array are the ones Google deems most representative of the place - Mix of merchant-uploaded photos (the cover shot, interior, exterior, menu, etc.) and customer-uploaded photos (food shots, room photos, signage) ### Why scrape Google Maps photos Google Places API "Place Photo" requests bill **$7 per 1000** for the basic tier and **$70 per 1000** for `maxHeightPx > 1600` — and every photo URL it returns is a `photoreference` token that **expires after one hour** and resolves to a single fixed-size image you can't easily re-derive at a different resolution. For real estate listing tools, AI computer-vision training pipelines, hotel-content aggregators, food-delivery apps, and travel inspiration sites that need durable, high-res image URLs at scale, the official Photos API is both expensive and operationally awkward (the 1-hour token expiry forces re-fetching every time you render the same photo). This actor solves that by hitting Google Maps' internal `/maps/preview/place` AJAX endpoint with `curl_cffi` (Chrome TLS impersonation) plus fresh anonymous Google session cookies from a managed minter pool. One call returns the embedded photo URLs Google's web client renders for the place panel — typically 30-150 photos per popular venue — for **$0.0008 per image**, or **$0.80 per 1000**. That's roughly **9× cheaper** than Google Places API (Basic) and **88× cheaper** than the high-res tier. The URLs are direct `lh5.googleusercontent.com/p/...` paths, which Google serves without expiry as long as the photo remains attached to the listing. Concrete buyer math: a real-estate listings site that wants 30 photos per property × 5,000 properties pays 150,000 × $0.0008 = **$120 once** for a permanent image set — versus Google Photos API at $1,050 (basic) or $10,500 (high-res) plus the operational overhead of re-fetching every URL hourly. A computer-vision team training a "what does the inside of a coffee shop look like" classifier on 10,000 venues × 20 photos = 200,000 images pays $160. ### Input | Field | Default | Description | |---|---|---| | `place_urls` | required | Array of canonical Google Maps place URLs (`https://www.google.com/maps/place//@,,17z/`) | | `max_photos_per_place` | `30` | Cap photos per place URL (1-200) | | `use_cookies` | `true` | Use a fresh anonymous Google session — bypasses the EU consent banner and reduces CAPTCHA at scale | The actor extracts the FID, lat/lng, and place ID from the URL itself — you don't need to pass any extra metadata. Both short URLs (`/maps/place//`) and long ones with `/data=!4m...` parameters are accepted. ### Output ```json { "place_name": "Eiffel Tower", "place_url": "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/", "photos_count_returned": 30, "photos": [ { "url": "https://lh5.googleusercontent.com/p/AF1QipPZ8j2Yk_h8...=w408-h540-k-no", "width": 408, "height": 540 }, { "url": "https://lh5.googleusercontent.com/p/AF1QipNgQrL2x4M9Z...=w1080-h720-k-no", "width": 1080, "height": 720 }, { "url": "https://lh5.googleusercontent.com/p/AF1QipMzC8t5rAv...=s10000", "width": null, "height": null } ] } ```` The actor returns one record per place (not one per photo), with the photos bundled into a `photos[]` array. The `=w408-h540` suffix on each URL is editable — change it to `=w1920-h1080` or `=s10000` (max-dim) to fetch the same image at a different resolution from the same `googleusercontent` host. ### Use cases **Real-estate marketplace seeding listings with hero photos.** You launch a Lisbon short-term rental aggregator and need 20 hero photos per apartment for 3,000 listings. Pull each apartment's Google Maps URL, run the actor with `max_photos_per_place=20`, and you have 60,000 direct image URLs for **$48**. Resize on the fly by editing the `=w408` suffix to `=w1080` — no re-scraping, no re-billing. **Food-delivery app populating restaurant gallery cards.** Your app shows 8 photos per restaurant on the menu screen. Across 12,000 restaurants in 50 cities, that's 96,000 photos for $76.80. Through Places API: $672 (basic) or $6,720 (high-res), plus you'd need to re-fetch every URL hourly because of the 1-hour token expiry. **Computer-vision team training scene classifiers.** You're training a model that classifies "is this a hotel lobby" vs. "restaurant interior" vs. "retail storefront". Pull 1,000 places per category × 30 photos = 30,000 photos per category at $24 each. Cheaper than the cost of one engineer's hour of API debugging. **Travel content site building "Top 50 attractions in Tokyo" galleries.** You need a curated gallery of 30 photos per attraction across 50 attractions per article × 100 articles = 150,000 photos for $120. Each URL is durable (no expiry), so you can cache and CDN them indefinitely. ### How it compares | Actor | Price per 1000 photos | URL durability | Resize-on-the-fly | Max per place | |---|---|---|---|---| | **This actor (s-r/free-google-maps-images-scraper)** | **$0.80** | durable (no expiry) | yes (edit `=w...` suffix) | 200 | | `slash-scrape/advanced-google-maps-photos-scraper` (#3 on `google maps photo scraper` SERP) | per-result, similar tier | durable | yes | varies | | Outscraper Google Maps Photos (#1 SERP) | flat-rate subscription | durable | yes | up to 1000 | | Google Places API Photo (basic, ≤1600px) | $7 + 1-hour expiry | **1-hour token expiry** | partial (size at request time) | unlimited (per-request billing) | | Google Places API Photo (high-res, >1600px) | $70 + 1-hour expiry | 1-hour token expiry | partial | unlimited | The competitive edge here is the price floor combined with URL durability — Google's `lh5.googleusercontent.com/p/` URLs work indefinitely as long as the photo is still attached to the listing, so you can cache them in your own CDN without re-scraping. Google's official Photo API tokens expire in 1 hour, which forces every render to round-trip through the API. ### Pricing This actor uses Apify's pay-per-event monetization at $0.0008 per photo returned — that's $0.80 per 1000 photos. All pricing is pay-per-event — you only pay for results you receive. No actor-start fee, no per-compute-unit charges, no charge for empty queries. ### Limits and gotchas - Maximum 200 photos per place per run — most popular venues have 100-300 photos; for the long tail (the Eiffel Tower has thousands), 200 covers the most-relevant set Google's panel renders by default - Photo dimensions are only available when Google embeds them in the URL suffix (~85% of cases); for the rest, the `width`/`height` fields are `null` and you can probe by editing `=s10000` to get the max available - The order of photos matches Google's relevance sort — the first photos are merchant-uploaded covers; deeper indices are mostly customer-uploaded - Apify residential proxy is **not** required — the cookie pool plus `curl_cffi`'s Chrome TLS fingerprint is enough for sustained throughput - Cold-start time is ~3-5 seconds for the first place; subsequent places in the same run reuse the session pool - The `place_url` must be the canonical Maps URL with the FID encoded; shortlinks like `g.co/...` need to be resolved upstream - We return URLs only — the actor does not download the image bytes, so you're not paying Apify storage fees for the photo content. Download is on your side via plain `curl` or `httpx` ### FAQ **How do I download photos from Google Maps in bulk?** Pass any canonical Google Maps place URL to this actor. It returns up to 200 direct image URLs per place at `lh5.googleusercontent.com/p/=w-h` paths — pasteable into a browser, downloadable with `curl -o photo.jpg`, no Google Photos API key needed. **Can I use Google Maps photos commercially?** Photos on Google Maps are uploaded under Google's Maps user contribution terms — generally permissive for non-commercial display (e.g. attribution-required reuse), but commercial republication is the photographer's call. Always check the photo's contributor attribution before republishing in a paid product. This actor returns the URL only; it does not transfer copyright. **What's the cost to scrape 10,000 Google Maps photos?** 10,000 × $0.0008 = **$8**. For comparison: Google Places API Photo (basic) costs $70 for the same 10,000 photos, and the URLs expire after 1 hour each. **Can I get high-resolution images?** Yes. Each URL ends in `=w408-h540-k-no` or similar — change the `w` and `h` numbers (or use `=s10000` for max-dim) and Google's `lh5.googleusercontent.com` host serves the same photo at the new resolution. No re-scraping needed. **Will Google rate-limit my scraping?** At default settings (fresh session cookies, no proxy) the actor sustains ~10 places/second without throttling. For sustained >50 places/sec throughput, supply a residential proxy URL via the `PROXY_URL` env var. ### Related Actors - [Free Google Maps Scraper](https://apify.com/s-r/free-google-maps-scraper) — find places by keyword and city; outputs canonical URLs ready to feed into this Images scraper - [Free Google Maps Reviews Scraper](https://apify.com/s-r/free-google-maps-reviews-scraper) — every review for any place URL (stars, text, owner reply, photos) - [Free Google Hotels Scraper](https://apify.com/s-r/free-google-hotels-scraper) — Google Hotels search with per-room pricing and 18-31 OTA price comparison # Actor input Schema ## `place_urls` (type: `array`): List of Google Maps place URLs. ## `max_photos_per_place` (type: `integer`): Cap photos per place URL (1-200). Default 30. ## `use_cookies` (type: `boolean`): Recommended. Bypasses the EU consent banner and reduces CAPTCHA at scale. ## Actor input object example ```json { "place_urls": [ "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/", "https://www.google.com/maps/place/Statue+of+Liberty/@40.6892494,-74.0445004,17z/" ], "max_photos_per_place": 30, "use_cookies": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "place_urls": [ "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/", "https://www.google.com/maps/place/Statue+of+Liberty/@40.6892494,-74.0445004,17z/" ] }; // Run the Actor and wait for it to finish const run = await client.actor("s-r/free-google-maps-images-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "place_urls": [ "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/", "https://www.google.com/maps/place/Statue+of+Liberty/@40.6892494,-74.0445004,17z/", ] } # Run the Actor and wait for it to finish run = client.actor("s-r/free-google-maps-images-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "place_urls": [ "https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/", "https://www.google.com/maps/place/Statue+of+Liberty/@40.6892494,-74.0445004,17z/" ] }' | apify call s-r/free-google-maps-images-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=s-r/free-google-maps-images-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Free Google Maps Images Scraper — Bulk Photo URLs", "version": "0.1", "x-build-id": "bzGiUe8F4gPrYGK6c" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/s-r~free-google-maps-images-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-s-r-free-google-maps-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/s-r~free-google-maps-images-scraper/runs": { "post": { "operationId": "runs-sync-s-r-free-google-maps-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/s-r~free-google-maps-images-scraper/run-sync": { "post": { "operationId": "run-sync-s-r-free-google-maps-images-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "place_urls" ], "properties": { "place_urls": { "title": "Google Maps place URLs", "type": "array", "description": "List of Google Maps place URLs.", "items": { "type": "string" } }, "max_photos_per_place": { "title": "Max photos per place", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cap photos per place URL (1-200). Default 30.", "default": 30 }, "use_cookies": { "title": "Use fresh Google cookies", "type": "boolean", "description": "Recommended. Bypasses the EU consent banner and reduces CAPTCHA at scale.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```