# Google Images Scraper (`easyapi/google-images-scraper`) Actor Powerful Google Images scraper collect up to 5000 image results per runn with flexible search options, language support. Perfect for visual content research, competitor analysis, and image SEO optimization. πŸ–ΌοΈπŸ” - **URL**: https://apify.com/easyapi/google-images-scraper.md - **Developed by:** [EasyApi](https://apify.com/easyapi) (community) - **Categories:** Integrations, Social media - **Stats:** 548 total users, 20 monthly users, 100.0% runs succeeded, 12 bookmarks - **User rating**: 4.59 out of 5 stars ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 ## Google Images Scraper πŸ–ΌοΈπŸ” Effortlessly scrape image data from Google with this powerful and flexible Actor! πŸš€ ### Features ✨ - 🎨 Scrape image results based on your search query - πŸ”’ Retrieve up to 5000 results per run - 🌐 Support for multiple countries and languages - ⏳ Time-based filtering options - πŸ’Ύ Results saved directly to your Apify dataset - πŸŽ›οΈ Advanced image filtering options (color, size, type, usage rights) ### Use Cases πŸ’‘ - πŸ–ΌοΈ Visual content research and trend analysis - 🎨 Competitor image strategy analysis - πŸ” Brand monitoring and logo tracking - πŸ“Š Image SEO optimization - 🎭 Specific image type searches (e.g., clipart, GIFs) - πŸ“ Size-specific image searches - πŸ–ŒοΈ Color-based image analysis ### How It Works πŸ› οΈ 1. Set your search parameters in the input 2. The Actor fetch Google Image search data 3. Results are processed and saved to your Apify dataset 4. Repeat until the desired number of results is reached or all available data is collected ### Input Parameters πŸ“ - `maxItems`: Maximum number of results to collect (100-5000) - `query`: Your search term - `images_page`: Specific page of image results to retrieve - `images_color`: Filter images by color (e.g., "red", "blue", "black_and_white") - `images_size`: Filter images by size ("large", "medium", "icon") - `images_type`: Filter images by type ("clipart", "line_drawing", "gif") - `images_usage`: Filter images by usage rights - `gl`: Google country code (e.g., "us" for United States) - `hl`: Interface language (e.g., "en" for English) - `lr`: Language of search results (e.g., "lang_en" for English) - `cr`: Country restriction for search results - `time_period`: Time range for results (e.g., "last_month") - `nfpr`: No auto-correction of spelling (0 or 1) - `filter`: Whether to filter similar results (0 or 1) ### Output πŸ“Š The Actor provides detailed information about each image result, including: - Title - Source URL - Image URL - Thumbnail URL - Original width and height - File format - And more! Get started with Google Images Scraper today and unlock valuable insights into visual content across the web! πŸš€πŸ–ΌοΈ #### Input Example A full explanation of an input example in JSON. ```` { "maxItems": 100, "query": "spacex" } ``` #### Output sample The results will be wrapped into a dataset which you can always find in theΒ **Storage**Β tab. Here's an excerpt from the data you'd get if you apply the input parameters above: And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML. ``` \[ { "position": 1, "title": "SpaceX - Mission", "link": "https://www.spacex.com/mission/", "domain": "www.spacex.com", "width": 275, "height": 183, "image": "https://www.spacex.com/static/images/locations/kennedy.jpg", "source": { "link": "https://SpaceX - Mission", "domain": "spacex", "name": "SpaceX - Mission" } }, { "position": 2, "title": "Amazon taps SpaceX for satellite launch even though Jeff Bezos has his own rocket company | CNN Business", "link": "https://www.cnn.com/2023/12/01/business/amazon-spacex-kuiper-launch-scn/index.html", "domain": "www.cnn.com", "width": 275, "height": 183, "image": "https://media.cnn.com/api/v1/images/stellar/prod/2023-05-22t004316z-2116487779-rc2831auwisd-rtrmadp-3-space-exploration-iss-axiom.jpg?c=original", "source": { "link": "https://Amazon taps SpaceX for satellite launch even though Jeff Bezos has his own rocket company | CNN Business", "domain": "amazon", "name": "Amazon taps SpaceX for satellite launch even though Jeff Bezos has his own rocket company | CNN Business" } }, ... ] ```` # Actor input Schema ## `maxItems` (type: `integer`): Maximum number of image results to be extracted. ## `query` (type: `string`): The search term to use ## `images_color` (type: `string`): Filter images by color. ## `images_size` (type: `string`): Filter images by size. ## `images_type` (type: `string`): Filter images by type. ## `images_usage` (type: `string`): Filter images by usage rights. ## `gl` (type: `string`): The Google country to use for the query ## `hl` (type: `string`): The Google UI language to return results ## `lr` (type: `string`): Limit the results to a specific language ## `cr` (type: `string`): Limit the results to a specific country ## `time_period` (type: `string`): Time period for results ## `time_period_min` (type: `string`): Minimum date for custom time period (MM/DD/YYYY) ## `time_period_max` (type: `string`): Maximum date for custom time period (MM/DD/YYYY) ## `nfpr` (type: `integer`): Exclude results from auto-corrected queries (0 or 1) ## `filter` (type: `integer`): Enable/disable Similar Results and Omitted Results filters (0 or 1) ## Actor input object example ```json { "maxItems": 1000, "query": "spacex" } ```` # 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 = { "maxItems": 1000, "query": "spacex" }; // Run the Actor and wait for it to finish const run = await client.actor("easyapi/google-images-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "maxItems": 1000, "query": "spacex", } # Run the Actor and wait for it to finish run = client.actor("easyapi/google-images-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 1000, "query": "spacex" }' | apify call easyapi/google-images-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=easyapi/google-images-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Images Scraper", "description": "Powerful Google Images scraper collect up to 5000 image results per runn with flexible search options, language support. Perfect for visual content research, competitor analysis, and image SEO optimization. πŸ–ΌοΈπŸ”", "version": "0.0", "x-build-id": "EeHi6lDEcLrFPRZyJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/easyapi~google-images-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-easyapi-google-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/easyapi~google-images-scraper/runs": { "post": { "operationId": "runs-sync-easyapi-google-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/easyapi~google-images-scraper/run-sync": { "post": { "operationId": "run-sync-easyapi-google-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": [ "query", "maxItems" ], "properties": { "maxItems": { "title": "Maximum Items", "minimum": 100, "maximum": 50000, "type": "integer", "description": "Maximum number of image results to be extracted.", "default": 100 }, "query": { "title": "Search Query", "type": "string", "description": "The search term to use", "default": "spacex" }, "images_color": { "title": "Images color", "enum": [ "any", "black_and_white", "transparent", "red", "orange", "yellow", "green", "teal", "blue", "purple", "pink", "white", "gray", "black", "brown" ], "type": "string", "description": "Filter images by color." }, "images_size": { "title": "Images size", "enum": [ "large", "medium", "icon" ], "type": "string", "description": "Filter images by size." }, "images_type": { "title": "Images type", "enum": [ "clipart", "line_drawing", "gif" ], "type": "string", "description": "Filter images by type." }, "images_usage": { "title": "Images usage rights", "enum": [ "non_commercial_reuse_with_modification", "non_commercial_reuse" ], "type": "string", "description": "Filter images by usage rights." }, "gl": { "title": "Google Country", "enum": [ "af", "al", "dz", "as", "ad", "ao", "ai", "aq", "ag", "ar", "am", "aw", "ac", "au", "at", "az", "bs", "bh", "bd", "bb", "by", "be", "bz", "bj", "bm", "bt", "bo", "ba", "bw", "bv", "br", "io", "bn", "bg", "bf", "bi", "kh", "cm", "ca", "cv", "cat", "ky", "cf", "td", "cl", "cn", "cx", "cc", "co", "km", "cg", "cd", "ck", "cr", "ci", "hr", "cy", "cz", "dk", "dj", "dm", "do", "tl", "ec", "eg", "sv", "gq", "er", "ee", "et", "fk", "fo", "fj", "fi", "fr", "gf", "pf", "tf", "ga", "gm", "ge", "de", "gh", "gi", "gr", "gl", "gd", "gp", "gu", "gt", "gn", "gw", "gy", "ht", "hm", "hn", "hk", "hu", "is", "in", "id", "iq", "ie", "il", "it", "jm", "jp", "jo", "kz", "ke", "ki", "kw", "kg", "la", "lv", "lb", "ls", "lr", "ly", "li", "lt", "lu", "mo", "mk", "mg", "mw", "my", "mv", "ml", "mt", "mh", "mq", "mr", "mu", "yt", "mx", "fm", "md", "mc", "mn", "ms", "ma", "mz", "na", "nr", "np", "nl", "an", "nc", "nz", "ni", "ne", "ng", "nu", "nf", "mp", "no", "om", "pk", "pw", "ps", "pa", "pg", "py", "pe", "ph", "pn", "pl", "pt", "pr", "qa", "re", "ro", "ru", "rw", "kn", "lc", "vc", "ws", "sm", "st", "sa", "sn", "cs", "sc", "sl", "sg", "sk", "si", "sb", "so", "za", "gs", "kr", "es", "lk", "sh", "pm", "sr", "sj", "sz", "se", "ch", "tw", "tj", "tz", "th", "tg", "tk", "to", "tt", "tn", "tr", "tm", "tc", "tv", "ug", "ua", "ae", "gb", "us", "um", "uy", "uz", "vu", "va", "ve", "vn", "vg", "vi", "wf", "eh", "ye", "zm", "zw" ], "type": "string", "description": "The Google country to use for the query" }, "hl": { "title": "UI Language", "enum": [ "af", "ak", "sq", "am", "ar", "hy", "az", "eu", "be", "bem", "bn", "bh", "bs", "br", "bg", "km", "ca", "chr", "ny", "zh-cn", "zh-tw", "co", "hr", "cs", "da", "nl", "en", "eo", "et", "ee", "fo", "tl", "fi", "fr", "fy", "gaa", "gl", "ka", "de", "el", "gn", "gu", "ht", "ha", "haw", "he", "iw", "hi", "hu", "is", "ig", "id", "ia", "ga", "it", "ja", "jw", "kn", "kk", "rw", "rn", "kg", "ko", "kri", "ku", "ckb", "ky", "lo", "la", "lv", "ln", "lt", "loz", "lg", "ach", "mk", "mg", "ms", "ml", "mt", "mi", "mr", "mfe", "mo", "mn", "sr-ME", "ne", "pcm", "nso", "no", "nn", "oc", "or", "om", "ps", "fa", "pl", "pt", "pt-br", "pt-pt", "pa", "qu", "ro", "rm", "nyn", "ru", "gd", "sr", "sh", "st", "tn", "crs", "sn", "sd", "si", "sk", "sl", "so", "es", "es-419", "su", "sw", "sv", "tg", "ta", "tt", "te", "th", "ti", "to", "lua", "tum", "tr", "tk", "tw", "ug", "uk", "ur", "uz", "vi", "cy", "wo", "xh", "yi", "yo", "zu" ], "type": "string", "description": "The Google UI language to return results" }, "lr": { "title": "Language Results", "enum": [ "lang_ar", "lang_hy", "lang_be", "lang_bg", "lang_ca", "lang_zh-cn", "lang_zh-tw", "lang_hr", "lang_cs", "lang_da", "lang_nl", "lang_en", "lang_eo", "lang_et", "lang_tl", "lang_fi", "lang_fr", "lang_de", "lang_el", "lang_iw", "lang_hu", "lang_is", "lang_id", "lang_it", "lang_ja", "lang_ko", "lang_lv", "lang_lt", "lang_no", "lang_fa", "lang_pl", "lang_pt", "lang_ro", "lang_ru", "lang_sr", "lang_sk", "lang_sl", "lang_es", "lang_sv", "lang_th", "lang_tr", "lang_uk", "lang_vi" ], "type": "string", "description": "Limit the results to a specific language" }, "cr": { "title": "Country Results", "enum": [ "af", "al", "dz", "as", "ad", "ao", "ai", "aq", "ag", "ar", "am", "aw", "ac", "au", "at", "az", "bs", "bh", "bd", "bb", "by", "be", "bz", "bj", "bm", "bt", "bo", "ba", "bw", "bv", "br", "io", "bn", "bg", "bf", "bi", "kh", "cm", "ca", "cv", "cat", "ky", "cf", "td", "cl", "cn", "cx", "cc", "co", "km", "cg", "cd", "ck", "cr", "ci", "hr", "cy", "cz", "dk", "dj", "dm", "do", "tl", "ec", "eg", "sv", "gq", "er", "ee", "et", "fk", "fo", "fj", "fi", "fr", "gf", "pf", "tf", "ga", "gm", "ge", "de", "gh", "gi", "gr", "gl", "gd", "gp", "gu", "gt", "gn", "gw", "gy", "ht", "hm", "hn", "hk", "hu", "is", "in", "id", "iq", "ie", "il", "it", "jm", "jp", "jo", "kz", "ke", "ki", "kw", "kg", "la", "lv", "lb", "ls", "lr", "ly", "li", "lt", "lu", "mo", "mk", "mg", "mw", "my", "mv", "ml", "mt", "mh", "mq", "mr", "mu", "yt", "mx", "fm", "md", "mc", "mn", "ms", "ma", "mz", "na", "nr", "np", "nl", "an", "nc", "nz", "ni", "ne", "ng", "nu", "nf", "mp", "no", "om", "pk", "pw", "ps", "pa", "pg", "py", "pe", "ph", "pn", "pl", "pt", "pr", "qa", "re", "ro", "ru", "rw", "kn", "lc", "vc", "ws", "sm", "st", "sa", "sn", "cs", "sc", "sl", "sg", "sk", "si", "sb", "so", "za", "gs", "kr", "es", "lk", "sh", "pm", "sr", "sj", "sz", "se", "ch", "tw", "tj", "tz", "th", "tg", "tk", "to", "tt", "tn", "tr", "tm", "tc", "tv", "ug", "ua", "ae", "gb", "us", "um", "uy", "uz", "vu", "va", "ve", "vn", "vg", "vi", "wf", "eh", "ye", "zm", "zw" ], "type": "string", "description": "Limit the results to a specific country" }, "time_period": { "title": "Time Period", "enum": [ "last_hour", "last_day", "last_week", "last_month", "last_year", "custom" ], "type": "string", "description": "Time period for results" }, "time_period_min": { "title": "Custom Time Period Min", "type": "string", "description": "Minimum date for custom time period (MM/DD/YYYY)" }, "time_period_max": { "title": "Custom Time Period Max", "type": "string", "description": "Maximum date for custom time period (MM/DD/YYYY)" }, "nfpr": { "title": "No Autocorrect", "minimum": 0, "maximum": 1, "type": "integer", "description": "Exclude results from auto-corrected queries (0 or 1)" }, "filter": { "title": "Filter", "minimum": 0, "maximum": 1, "type": "integer", "description": "Enable/disable Similar Results and Omitted Results filters (0 or 1)" } } }, "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 } } } } } } } } } } ```