# Google Lens OCR API: Image to Text with Standby (`getascraper/google-lens-ocr`) Actor Google Lens OCR API for image URLs, Base64, and Apify storage records, with a Standby REST endpoint for single-image requests. Get extracted text, real word/paragraph/line geometry, writing direction, detected regions, translation, and explicit per-image errors. - **URL**: https://apify.com/getascraper/google-lens-ocr.md - **Developed by:** [GetAScraper](https://apify.com/getascraper) (community) - **Categories:** Developer tools, AI, MCP servers - **Stats:** 87 total users, 11 monthly users, 99.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 listing scrapeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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. - **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use). - **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`. - **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`. - **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`. - **Any other language** — 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: Image to Text with a Live Standby Endpoint Extract text from a single image, or a whole batch, using the same engine behind Google Lens. Call it as a live REST endpoint for one image at a time (no cold start), or submit a batch of image URLs, Base64 payloads, or Apify key-value store records in one run. Every submitted image returns one correlated result with its status, detected language, dimensions, word count, timing, and any real error. Use the output for document indexing, searchable archives, translation workflows, content moderation, accessibility pipelines, RAG preparation, and AI agent tool calls. #### Copy to your AI assistant ``` getascraper/google-lens-ocr on Apify. Two ways to call it: 1) Standby REST API (no cold start, one image per call): find this Actor's Standby hostname on its Standby tab in Apify Console, then GET https:///ocr?imageUrl=...&outputDetail=full&token=TOKEN 2) Batch run via the Apify client: ApifyClient("TOKEN").actor("getascraper/google-lens-ocr").call(run_input={"imageUrl": "..."}), then client.dataset(run["defaultDatasetId"]).list_items().items for results. Key inputs: imageUrl: string (a single image), outputDetail: string (text_only|lines|full|paragraphs|words), translateTo: string (optional language code). Batch inputs (imageUrls, imagesBase64, imageKvsRecords) also available for many images in one run. Full actor spec (input schema, output dataset fields, README): GET https://api.apify.com/v2/acts/getascraper~google-lens-ocr/builds/default (Bearer TOKEN) → inputSchema, actorDefinition.storages.dataset, readme. Get a token: https://console.apify.com/account/integrations ``` ### ✨ What this Actor gives you - **A live Standby endpoint:** Call `GET /ocr?imageUrl=...` for a single image with no container cold start, alongside normal batch runs. - **Four input modes:** One image URL for the common case, plus bulk URLs, Base64 image data, and Apify key-value store records for batches. - **Stable correlation:** Supply your own `inputId`, or use deterministic IDs assigned in input order. - **Honest batch rows:** Successful, partial, and failed inputs all remain visible. - **Source dimensions:** Get the original image width and height when the image can be decoded. - **Detected language and writing direction:** Know whether text reads left-to-right, right-to-left, or top-to-bottom. - **Real word, line, and paragraph geometry:** Every box comes directly from Google's own response. Nothing is estimated or interpolated. - **Detected regions:** Salient regions and objects Google's own response identifies in the image, at no extra cost. - **Optional translation:** Request a target language while retaining the original OCR text. - **Bounded concurrency:** Process batches without launching every image request at once. - **Run summary:** Review submitted, successful, partial, and failed counts in `RUN_SUMMARY`. ### 🎯 Common workflows - **AI agents and MCP tools:** Call the Standby endpoint as a fast, stateless OCR tool with no run-management overhead. - **AI and RAG teams:** Turn screenshots and scanned pages into searchable text with source correlation. - **Automation teams:** Process receipt, label, menu, poster, and document image batches. - **Localization teams:** Extract original text and request a translated version in the same row. - **Data operations teams:** Reconcile every input against a clear success, partial, or failure status. - **Developers:** Use real word-level boxes and writing direction for layout reconstruction and highlighting. ### ⚡ Call it live, or run it as a batch **For a single image**, call the Standby endpoint directly instead of starting a run. Find this Actor's Standby hostname on its **Standby** tab in Apify Console, then: ``` GET https:///ocr?imageUrl=https://example.com/photo.jpg&outputDetail=full&token=YOUR_TOKEN ``` It answers in about a second, since there is no container start-up wait once the Actor is warm. **For many images**, run the Actor normally: 1. Open the Actor in Apify Console. 2. Add a single image URL, or open "Batch and advanced sources" for a bulk list, Base64 data, or key-value store records. 3. Optionally add input IDs and a translation target. 4. Choose the output detail and concurrency. 5. Start the run. 6. Open the dataset for correlated rows or `RUN_SUMMARY` for run totals. ### 📥 Input | Field | Type | Required | What it controls | | :---------------- | :------ | :---------- | :------------------------------------------------------------------------------------------------------------------------------------------------ | | `imageUrl` | string | Conditional | One public HTTP or HTTPS image URL. This is all most runs need. | | `imageUrlInputId` | string | No | Correlation ID for `imageUrl`. Defaults to `single-1`. | | `imageUrls` | array | Conditional | Bulk URL objects, for batches. Each item can include `url` and `userData.inputId`. | | `imagesBase64` | array | Conditional | Objects containing `data` and an optional `inputId`. Raw Base64 and image data URIs are accepted. | | `imageKvsRecords` | array | Conditional | Objects containing `key`, optional `storeId`, and optional `inputId`. | | `outputDetail` | string | No | `text_only`, `lines`, `full` (default), `paragraphs` (adds grouping and writing direction), or `words` (adds every word's own box and rotation). | | `translateTo` | string | No | Target language code such as `es`, `de`, or `pt-BR`. | | `maxConcurrency` | integer | No | Images processed at once in a batch run, from 1 to 10. | At least one of `imageUrl`, `imageUrls`, `imagesBase64`, or `imageKvsRecords` must be provided. #### URL batch example ```json { "imageUrls": [ { "url": "https://tesseract.projectnaptha.com/img/eng_bw.png", "userData": { "inputId": "poem-page-1" } }, { "url": "https://example.com/document-page-2.png", "userData": { "inputId": "document-page-2" } } ], "outputDetail": "full", "translateTo": "es", "maxConcurrency": 3 } ``` #### Apify storage example ```json { "imageKvsRecords": [ { "storeId": "my-image-store", "key": "receipts/july-001.png", "inputId": "receipt-july-001" } ], "outputDetail": "lines" } ``` The default key-value store is used when `storeId` is omitted. A storage record can contain binary image data, a Base64 string, or a JSON object with a Base64 `data` field. #### Recurring document OCR workflow Use the same `imageUrls` input from an Apify schedule. Keep `inputId` stable so downstream systems can reconcile each image across runs. ```json { "imageUrls": [ { "url": "https://example.com/invoices/2026-08-01.png", "userData": { "inputId": "invoice-2026-08-01" } } ], "outputDetail": "full" } ``` ### 📤 Output The Actor writes one row for each submitted image. This abbreviated example comes from the public Tesseract sample image: ```json { "inputId": "sample-1", "sourceType": "URL", "sourceReference": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "status": "SUCCEEDED", "language": "en", "fullText": "Mild Splendour of the various-vested Night!\nMother of wildly-working visions! hail!\nI watch thy gliding, while with watery light\nThy weak eye glimmers through a fleecy veil;\nAnd when thou lovest thy pale orb to shroud\nBehind the gather'd blackness lost on high;\nAnd when thou dartest from the wind-rent cloud\nThy placid lightning o'er the awaken'd sky.", "translationTarget": "es", "wordCount": 58, "imageWidth": 1486, "imageHeight": 668, "lineGeometryAvailable": true, "wordGeometryAvailable": false, "geometryLevel": "LINE", "durationMs": 3154, "processedAt": "2026-08-01T16:51:13.248Z" } ``` #### Result status | Status | Meaning | | :---------- | :----------------------------------------------------------------------------------------------------- | | `SUCCEEDED` | OCR completed. Requested translation also completed when text was available. | | `PARTIAL` | OCR completed, but an optional translation request failed. OCR text remains in the row. | | `FAILED` | The image could not be loaded, decoded, or processed. The row contains `errorCode` and `errorMessage`. | #### Field reference | Field | Description | | :--------------------------- | :---------------------------------------------------------------------------------------------------- | | `inputId` | User-provided or deterministic correlation ID. | | `sourceType` | `URL`, `BASE64`, or `KEY_VALUE_STORE`. | | `sourceReference` | URL or storage record reference. Base64 content is never copied into this field. | | `status` | Per-input processing outcome. | | `language` | Language reported by Google, for the whole image. | | `fullText` | Extracted lines joined with newline characters. | | `translatedText` | Real translated text when requested and completed. | | `wordCount` | Whitespace-delimited word count calculated from `fullText`. | | `imageWidth`, `imageHeight` | Source image dimensions in pixels. | | `lineGeometryAvailable` | Whether at least one genuine line box is present. | | `wordGeometryAvailable` | Whether at least one genuine word box is present. Only ever `true` when Output detail is `words`. | | `geometryLevel` | `WORD` or `LINE`, whichever is the finest real geometry present in this row. Omitted for text-only rows. | | `lines` | Extracted lines with normalized and pixel geometry when available. | | `paragraphs` | Present when Output detail is `paragraphs` or `words`: each paragraph's writing direction, joined text, and (at `words`) every word's own box and rotation. | | `regions` | Present at the same tiers: salient regions and objects Google's own response identifies, each with a real box when available. | | `durationMs` | Total processing time for that input. | | `errorCode`, `errorMessage` | Real failure details for partial or failed rows. | One real element from the sample row's `lines` array: ```json { "text": "Mild Splendour of the various-vested Night!", "boundingBox": { "normalized": { "centerX": 0.44486331939697266, "centerY": 0.1067144051194191, "width": 0.8516666889190674, "height": 0.11873840540647507 }, "pixel": { "x": 28, "y": 32, "width": 1266, "height": 79 } } } ``` With `outputDetail: "words"` on the same image, the first paragraph's first word looks like this (also real, not estimated): ```json { "writingDirection": "LTR", "text": "Mild Splendour of the various-vested Night! Mother of wildly-working visions! hail!", "words": [ { "text": "Mild", "boundingBox": { "normalized": { "centerX": 0.067, "centerY": 0.1035, "width": 0.0958, "height": 0.1169 }, "pixel": { "x": 28, "y": 30, "width": 142, "height": 78 }, "rotation": 0.0049304598942399025 } } ] } ``` ### 🛡️ Data integrity and limits - The Actor does not fill missing values with invented labels, zero coordinates, or placeholder text. - Word, line, paragraph, and region boxes are never estimated or interpolated. Every box, including rotation, comes directly from Google's own response. - A known full-image geometry fallback from the upstream parser is removed at every level instead of being presented as a precise box. - Input images are limited to 25 MB each. - Translation is optional. If it fails after OCR succeeds, the row is marked `PARTIAL` and keeps the original text. - OCR and translation depend on external services, so response time and availability can vary. - Only process images that you are authorized to use. ### 💳 Pricing The repository's intended PPE configuration charges the `Processed OCR image` event for successful or partial OCR results while keeping failed audit rows visible. The active Store pricing is configured separately from the Actor build, so verify the live pricing record and each run's `chargedEventCounts` before relying on a failure-free billing boundary. ### ❓ FAQ #### Does the Actor keep batch order? Yes. Rows are pushed in the same order as the normalized input list, even when images finish at different times. #### Can I match results to my own database records? Yes. Add a unique `inputId` to each item. The same value appears in its dataset row. #### Does it return word bounding boxes? Yes, when Output detail is set to `words`. Every word gets its own real box (from Google's own response, never estimated), with rotation. `full` and `paragraphs` stay at line-level geometry to keep the default payload small. #### What happens when one image fails? The rest of the batch continues. The failed image receives its own `FAILED` row with an error code and message. #### What happens when translation fails? Valid OCR data is retained, and the row is marked `PARTIAL`. #### Does it run as a Standby web server? Yes. Find this Actor's Standby hostname on its Standby tab in Apify Console, then call `GET /ocr?imageUrl=...` for single-image requests with no cold start. Batch runs (`imageUrls`, `imagesBase64`, `imageKvsRecords`) are only available through a normal run, not through Standby. ### ⭐ Was this useful?
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### 🔗 Other actors - [Google Lens Visual Search](https://apify.com/getascraper/google-lens-visual-search) ↗: Find visual matches, descriptions, and related links for an image. - [Bulk Image Downloader](https://apify.com/getascraper/bulk-image-downloader) ↗: Download image batches with metadata, hashes, and Apify storage output. - [arXiv RAG Extractor](https://apify.com/getascraper/arxiv-rag-extractor) ↗: Extract research papers as structured text for RAG pipelines. # Actor input Schema ## `imageUrl` (type: `string`): Public HTTP or HTTPS URL of the image to run OCR on. This is all most runs need. Use imageUrlInputId to attach your own correlation ID. ## `imageUrlInputId` (type: `string`): Optional correlation ID for imageUrl. If omitted, the Actor assigns the deterministic ID single-1. ## `imageUrls` (type: `array`): Public image URLs. API callers can include userData.inputId on each URL object for correlation. Leave empty if you only need the single Image URL above. ## `imagesBase64` (type: `array`): JSON array of objects with data and an optional inputId. data can be raw Base64 or an image data URI. ## `imageKvsRecords` (type: `array`): JSON array of Apify key-value store records. Omit storeId to read from the run's default store. Records can contain binary image data, a Base64 string, or an object with a Base64 data field. ## `outputDetail` (type: `string`): Full (default) returns joined text and line boxes. Paragraphs also groups lines and reports writing direction (left-to-right, right-to-left, or top-to-bottom). Words adds every word's own real bounding box and rotation angle, roughly 9x more geometry data. Text only omits all geometry. Every box comes directly from Google; the Actor never estimates or interpolates one. ## `translateTo` (type: `string`): Optional language code such as es, de, ja, or pt-BR. Translation failures keep the OCR data and mark the row PARTIAL. ## `maxConcurrency` (type: `integer`): Number of images processed at once. Lower this for very large images or constrained memory. ## Actor input object example ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "imageUrlInputId": "", "imageUrls": [], "imagesBase64": [], "imageKvsRecords": [], "outputDetail": "full", "translateTo": "", "maxConcurrency": 3 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `runSummary` (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", "imageUrlInputId": "", "imageUrls": [], "imagesBase64": [], "imageKvsRecords": [], "outputDetail": "full", "translateTo": "", "maxConcurrency": 3 }; // 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", "imageUrlInputId": "", "imageUrls": [], "imagesBase64": [], "imageKvsRecords": [], "outputDetail": "full", "translateTo": "", "maxConcurrency": 3, } # 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(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).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", "imageUrlInputId": "", "imageUrls": [], "imagesBase64": [], "imageKvsRecords": [], "outputDetail": "full", "translateTo": "", "maxConcurrency": 3 }' | apify call getascraper/google-lens-ocr --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,getascraper/google-lens-ocr" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/eoVXILAQvzkbyNVrD/builds/WBdMuVZ4f3Sw9Vr5N/openapi.json