# Google Lens OCR API: Sub-second Image to Text (`getascraper/google-lens-ocr`) Actor Extract text from any image with exact word-level bounding boxes and pixel coordinates. Powered by the official Google Lens engine for sub-second, multi-language OCR under 500ms. No browser required. $4.99 per 1k images. - **URL**: https://apify.com/getascraper/google-lens-ocr.md - **Developed by:** [GetAScraper](https://apify.com/getascraper) (community) - **Categories:** Developer tools, AI, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 1,000 listing scrapeds 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 Lens OCR API: Sub-second Image to Text Extract text from any image with exact word-level bounding boxes and absolute pixel coordinates. Powered by the official Google Lens engine for sub-second, multi-language OCR under 500ms. No browser required. Get fully structured, line-by-line paragraph, line, and word extractions with absolute pixel width, height, and coordinates, fully optimized for price intelligence, document indexing, and AI RAG pipelines. --- ### What can you do with it? * **I am an AI developer** building a RAG pipeline and looking to quickly extract high-fidelity text segments, tables, and paragraphs from scanned documents or PDFs in under 500ms. * **I am an automation engineer** looking to programmatically OCR receipts, invoices, and menus with precise pixel bounding-box coordinates for automatic layout reconstructions. * **I am a translation vendor** looking to hint specific languages and instantly translate image text blocks to another target locale. --- ### How to extract text from images step-by-step 1. Create a free Apify account. 2. Open the **Google Lens OCR API** in the Apify Store. 3. Enter your target **Image URL** (e.g. any public JPEG, PNG, or WebP link). 4. Configure optional filters like **Language Hint** or **Translate To**. 5. Click **Start** and download your structured OCR text dataset as JSON, CSV, or Excel. #### API quick start Trigger runs programmatically with a single POST request in under 500ms: ```bash curl --request POST \ --url "https://google-lens-ocr.apify.actor/ocr?token=YOUR_API_TOKEN" \ --header 'Content-Type: application/json' \ --data '{ "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "outputDetail": "full" }' ```` *** ### Input | Field | Type | Required | Description | | :--- | :--- | :--- | :--- | | `imageUrl` | `string` | No | The public URL of a single image to extract text from. Either `imageUrl` or `imageUrls` must be provided. | | `imageUrls` | `array of URLs` | No | Paste multiple image URLs to extract in a single bulk-batch run. | | `outputDetail` | `enum` | No | Level of structural detail to output: `full` (lines + boxes), `paragraphs`, `lines`, `words`, `text_only`. | | `language` | `string` | No | ISO 639-1 language code hint to improve OCR accuracy (e.g. `en`, `de`, `fr`, `ja`, `ar`). | | `region` | `enum` | No | Select country region hint to improve address, phone number, and date parser formats. | | `translateTo` | `string` | No | Optional ISO 639-1 language code to automatically translate detected text block (e.g. `es`, `de`). | *** ### Output Each run produces one result with these fields. Bounding boxes include absolute pixel coordinates (`x`, `y`, `width`, `height`) for immediate use in image annotations. ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "language": "en", "fullText": "Mild Splendour of the various-vested Night!\nMother of wildly-working visions! hail!", "lines": [ { "text": "Mild Splendour of the various-vested Night!", "x": 30, "y": 33, "width": 1265, "height": 77 }, { "text": "Mother of wildly-working visions! hail!", "x": 99, "y": 109, "width": 1099, "height": 76 } ], "scrapedAt": "2026-06-15T11:14:58.726Z" } ``` #### Field reference | Field | Type | Description | | :--- | :--- | :--- | | `imageUrl` | `string` | Public URL of the parsed image. | | `language` | `string` | Detected language code. | | `fullText` | `string` | Complete extracted text block joined by newlines. | | `lines` | `array` | Lines of text with absolute pixel coordinates (x, y, width, height). | | `paragraphs` | `array` | Paragraph elements with absolute pixel coordinates. | | `scrapedAt` | `string` | ISO timestamp of when the image was processed. | *** ### Pricing and cost Pricing is pay-per-result and is billed per successfully processed image. Failed runs cost absolutely nothing. - Rate: **$4.99 per 1,000 images** ($0.00499 per image). - 100 images typically cost **$0.49**. - 1,000 images cost exactly **$4.99**. - 10,000 images cost exactly **$49.90**. - No fixed monthly subscriptions or hidden maintenance fees. *** ### Tips and best practices - **Avoid browser cold starts.** By deploying in Standby mode, this Actor remains alive in the background. You receive sub-second OCR responses (typically under 200-500ms) with zero initialization delay! - **Keep dimensions reasonable.** Images are automatically resized to under 1200x1200px before uploading. This speeds up transfer latency and avoids large binary payload blocks while preserving 100% OCR accuracy. *** ### FAQ ##### Does it require a browser to execute? No. Unlike browser-rendered scrapers, this Actor connects directly to Google's native binary API. This guarantees sub-second execution speeds, zero browser memory overhead, and extremely low running costs. ##### Are all image formats supported? Yes. The Actor supports JPEG, PNG, WebP, BMP, TIFF, and HEIC formats. ##### Is handwriting recognized? Yes. The Actor uses the same advanced neural OCR engine as Google Lens in Chromium. Accuracy is exceptionally high for both printed text and clear handwriting. *** ### Target SEO keywords - Google Lens OCR API - image to text API - extract text from image - word bounding box coordinates - Chromium OCR unblocked *** ### Disclaimers and support - **Disclaimer:** This Actor connects to publicly available image uploading services. Users are responsible for ensuring they have the rights to process the images they submit. - **Support:** Open an issue from the Actor page in the Apify Console for bug reports or feature requests. # Actor input Schema ## `imageUrl` (type: `string`): The public URL of a single image to extract text from (JPEG, PNG, WebP, BMP, TIFF, HEIC). ## `imageUrls` (type: `array`): Paste multiple image URLs to extract in a single bulk-batch run. ## `outputDetail` (type: `string`): Level of structural detail to output (bounding boxes, paragraphs, lines, etc.). ## `language` (type: `string`): ISO 639-1 language code hint to improve OCR accuracy (e.g. 'en', 'de', 'fr', 'ja', 'ar'). ## `region` (type: `string`): Select country region hint to improve address, phone number, and date parser formats. ## `translateTo` (type: `string`): Optional ISO 639-1 language code to automatically translate detected text block (e.g. 'es', 'de'). ## Actor input object example ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrls": [], "outputDetail": "full", "language": "en", "region": "US", "translateTo": "" } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrls": [] }; // Run the Actor and wait for it to finish const run = await client.actor("getascraper/google-lens-ocr").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 = { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrls": [], } # Run the Actor and wait for it to finish run = client.actor("getascraper/google-lens-ocr").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 '{ "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrls": [] }' | apify call getascraper/google-lens-ocr --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getascraper/google-lens-ocr", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Lens OCR API: Sub-second Image to Text", "description": "Extract text from any image with exact word-level bounding boxes and pixel coordinates. Powered by the official Google Lens engine for sub-second, multi-language OCR under 500ms. No browser required. $4.99 per 1k images.", "version": "0.1", "x-build-id": "lNhAdceWIt7aGfNtc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getascraper~google-lens-ocr/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getascraper-google-lens-ocr", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/getascraper~google-lens-ocr/runs": { "post": { "operationId": "runs-sync-getascraper-google-lens-ocr", "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/getascraper~google-lens-ocr/run-sync": { "post": { "operationId": "run-sync-getascraper-google-lens-ocr", "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", "properties": { "imageUrl": { "title": "Single Image URL", "type": "string", "description": "The public URL of a single image to extract text from (JPEG, PNG, WebP, BMP, TIFF, HEIC)." }, "imageUrls": { "title": "Bulk Image URLs", "type": "array", "description": "Paste multiple image URLs to extract in a single bulk-batch run.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "outputDetail": { "title": "Output Detail Level", "enum": [ "full", "paragraphs", "lines", "words", "text_only" ], "type": "string", "description": "Level of structural detail to output (bounding boxes, paragraphs, lines, etc.).", "default": "full" }, "language": { "title": "Language Hint", "type": "string", "description": "ISO 639-1 language code hint to improve OCR accuracy (e.g. 'en', 'de', 'fr', 'ja', 'ar').", "default": "en" }, "region": { "title": "Region Hint", "enum": [ "US", "GB", "DE", "FR", "CA", "AU", "ES", "IT", "BR", "NL", "AR", "AT", "BE", "BG", "CH", "CL", "CO", "CZ", "DK", "EG", "FI", "GR", "HK", "HR", "HU", "ID", "IE", "IL", "IN", "JP", "KR", "MX", "MY", "NG", "NO", "NZ", "PE", "PH", "PK", "PL", "PT", "RO", "SA", "SE", "SG", "SK", "TH", "TR", "TW", "UA", "VN", "ZA" ], "type": "string", "description": "Select country region hint to improve address, phone number, and date parser formats.", "default": "US" }, "translateTo": { "title": "Translate To", "type": "string", "description": "Optional ISO 639-1 language code to automatically translate detected text block (e.g. 'es', 'de').", "default": "" } } }, "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 } } } } } } } } } } ```