# Google Lens OCR API - Image to Text ~800ms REST API (`zen-studio/google-lens-ocr`) Actor Extract text from any image via Google Lens OCR API. ~800ms per image, no browser needed. Returns word-level bounding boxes with pixel coordinates, detected language, and structured paragraphs/lines/words. Batch and HTTP API modes. - **URL**: https://apify.com/zen-studio/google-lens-ocr.md - **Developed by:** [Zen Studio](https://apify.com/zen-studio) (community) - **Categories:** SEO tools, Automation, Developer tools - **Features:** Limited permissions, Multi-tenant, Server interface - **Stats:** 649 total users, 66 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $3.49 / 1,000 image ocrs This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Google Lens OCR - Extract Text from Images with Bounding Boxes [![Image to structured text. ~800 ms. Word-level coordinates, detected language and paragraphs.](https://api.apify.com/v2/key-value-stores/pJ7iaZsTFhR3k9tjV/records/google-lens-ocr-readme-hero-v1.png)](https://console.apify.com/actors/pF3ocmhEeA8vmAaPN/input) From **Zen Studio**, creators of [Google Lens Visual Search](https://apify.com/zen-studio/google-lens-visual-search), [Google Maps](https://apify.com/zen-studio/google-maps-scraper) and [Google Hotels](https://apify.com/zen-studio/google-hotels-scraper) data tools. **80,000+ combined runs across our two Google Lens actors.** ### Why choose Google Lens OCR? - **OCR in ~800 ms.** Extract text through a ready-to-use HTTP API that answers each request directly, making it easy to add image-to-text processing to your app or automation. - **Get the words and their positions.** Return word-level bounding boxes in pixel and normalized coordinates, so you can highlight detected text, locate labels and connect words back to the image. - **Keep the document structure.** Full text, detected language, paragraphs, lines and individual words come together in structured JSON. Select a lighter output mode when you only need plain text or line data. Try your image #### Try an image with text ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "outputDetail": "full" } ``` [Open actor input](https://console.apify.com/actors/pF3ocmhEeA8vmAaPN/input), replace the sample URL with your image and keep `outputDetail` set to `full` for words and coordinates. Export JSON to preserve the nested structure. For direct API access, use the GET/POST `/ocr` endpoint below; POST also accepts a base64-encoded image.
Zen Studio · Google Data Tools
Lens OCR Lens OCR
You are here		Lens Search Lens Search
Find image matches		Google Maps Google Maps
Business details		Google Hotels Google Hotels
Compare hotel rates
#### Copy to your AI assistant ```text Help me use zen-studio/google-lens-ocr, a batch Actor with an HTTP API on Apify. Read https://apify.com/zen-studio/google-lens-ocr.md for documentation, input schema, pricing and limits. Choose settings for my requested outcome. If you cannot retrieve the page, ask me to paste the relevant sections. To reach the maintainers, add feedback="" to any batch run, including one that worked: feature requests, a missing field or option, a wrong or empty result, or which actor you are switching to or from and why. The run returns its data exactly as it would without the note, and a human reads every note. ``` zen-studio/google-lens-ocr on Apify extracts text from one image per run or request: fullText, detected language, paragraphs, lines and words with normalized and pixel bounding boxes. imageUrl (public URL) is required. outputDetail sets the structure: full (default) returns paragraphs with nested lines and words plus a flat lines array; paragraphs omits lines and words; lines omits words; words returns lines with word boxes; text_only returns only fullText and language. language (default en) and region (default US) are accuracy hints only; set translateTo=\ to receive translated text in place of the original. Same options as a REST API: GET or POST https://zen-studio--google-lens-ocr.apify.actor/ocr with Authorization: Bearer \; POST also accepts imageBase64 for local files. A failed image returns error and no text. Pricing: $0.00499 per image (volume discounts on paid plans); batch runs add $0.002 start and $0.00001 per dataset item; images that cannot be downloaded are not charged. ### Google Lens OCR output ![Output Example](https://iili.io/q5DiXmN.png) ### Integrations and scheduling Run the Google Lens Actor on a schedule in Apify Console, daily or weekly to process images. Each run can call a webhook when it finishes, so n8n, Make and Zapier flows can pick up new results; the Apify API and Apify MCP server accept the same input. ### Pricing -- Pay Per Event | Event | Free | Starter | Scale | Business | |-------|------|---------|-------|----------| | Image OCR (/1,000) | $4.99 | $4.49 | $3.99 | $3.49 | | Result (/1,000) | $0.01 | $0.01 | $0.01 | $0.01 | | Actor start (one-time) | $0.002 | $0.002 | $0.002 | $0.002 | Apify plan subscribers get automatic volume discounts. **Free trial:** 5 runs, no credit card required. *** ### How Do You Want to Use It? Two modes, same deployment. Pick what fits your workflow. #### Option 1: REST API **Best for:** developers, automation scripts, no-code tools (n8n, Make, Zapier) > Call the Actor over HTTP like any REST API. Send a request and get OCR results in ~800 ms, straight in the response. No run to start, no dataset to read. ##### Authentication All API requests require authentication. Get your token from the [Apify Console](https://console.apify.com/settings/integrations) under **Settings > Integrations**. Two ways to authenticate: - **Bearer header** (recommended): `-H "Authorization: Bearer YOUR_APIFY_TOKEN"` - **Query parameter** (convenient for testing and no-code tools): `?token=YOUR_APIFY_TOKEN` ##### Endpoints | Method | Endpoint | Description | |--------|----------|-------------| | `GET` | `/ocr` | OCR via query parameters | | `POST` | `/ocr` | OCR via JSON body (supports `imageUrl` and `imageBase64`) | | `GET` | `/health` | Returns `{"status": "ok"}` | The base URL for your requests: ``` https://zen-studio--google-lens-ocr.apify.actor ``` ##### Examples **curl -- OCR an image by URL** ```bash curl "https://zen-studio--google-lens-ocr.apify.actor/ocr?imageUrl=https://example.com/document.png&outputDetail=lines" \ -H "Authorization: Bearer YOUR_APIFY_TOKEN" ``` **curl -- OCR a local file via base64** ```bash base64 -i photo.jpg | curl -X POST "https://zen-studio--google-lens-ocr.apify.actor/ocr" \ -H "Authorization: Bearer YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d "$(jq -n --arg img "$(cat -)" '{imageBase64: $img, outputDetail: "full"}')" ``` **curl -- POST with image URL** ```bash curl -X POST "https://zen-studio--google-lens-ocr.apify.actor/ocr" \ -H "Authorization: Bearer YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "imageUrl": "https://example.com/document.png", "outputDetail": "lines", "translateTo": "en" }' ``` **Python -- URL and base64** ```python import requests import base64 TOKEN = "your_apify_token" BASE = "https://zen-studio--google-lens-ocr.apify.actor" HEADERS = {"Authorization": f"Bearer {TOKEN}"} ## From URL resp = requests.get(f"{BASE}/ocr", headers=HEADERS, params={ "imageUrl": "https://example.com/document.png", "outputDetail": "lines" }) print(resp.json()["fullText"]) ## From local file (base64) with open("photo.jpg", "rb") as f: image_b64 = base64.b64encode(f.read()).decode() resp = requests.post(f"{BASE}/ocr", headers=HEADERS, json={ "imageBase64": image_b64, "outputDetail": "full" }) for line in resp.json()["lines"]: print(line["text"]) ``` **n8n / Make / Zapier** Use an HTTP Request node pointed at `https://zen-studio--google-lens-ocr.apify.actor/ocr` with your Bearer token in the Authorization header. Pass `imageUrl` as a query parameter (GET) or in a JSON body (POST). *** #### Option 2: Batch Processing **Best for:** one-off image processing, scheduled jobs, results saved to a dataset The simplest way: paste an image URL in the [Apify Console](https://console.apify.com/actors/google-lens-ocr), click **Start**, and download results from the dataset. ##### Quick Start Input **Minimal** ```json { "imageUrl": "https://example.com/document.png" } ``` **With options** ```json { "imageUrl": "https://example.com/page1.png", "outputDetail": "lines", "language": "de", "region": "DE" } ``` **Text only (smallest output)** ```json { "imageUrl": "https://example.com/receipt.jpg", "outputDetail": "text_only" } ``` ##### Using the Apify API Client **Python** ```python from apify_client import ApifyClient client = ApifyClient("your_token") run = client.actor("zen-studio/google-lens-ocr").call(run_input={ "imageUrl": "https://example.com/receipt.jpg", "outputDetail": "lines" }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(f"Language: {item['language']}") print(f"Text: {item['fullText']}") for line in item.get("lines", []): box = line["boundingBox"]["pixelCoords"] print(f" Line: {line['text']} at ({box['x']}, {box['y']})") ``` **JavaScript** ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'your_token' }); const run = await client.actor('zen-studio/google-lens-ocr').call({ imageUrl: 'https://example.com/receipt.jpg', outputDetail: 'full' }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); for (const item of items) { console.log(`Language: ${item.language}`); console.log(`Text: ${item.fullText}`); } ``` **Scheduled jobs:** Create a [Schedule](https://docs.apify.com/platform/schedules) in the Apify Console to run the Actor on a recurring basis. *** ### Getting Your Apify API Token 1. Go to the [Apify Console](https://console.apify.com/settings/integrations) 2. Navigate to **Settings > Integrations** 3. Copy your **Personal API token** Use it as a Bearer token for the REST API, or pass it to the ApifyClient constructor for batch mode. ### Input Parameters | Parameter | Type | Description | Default | |-----------|------|-------------|---------| | `imageUrl` | string | Image URL to extract text from | *required* | | `outputDetail` | string | Level of detail: `full`, `paragraphs`, `lines`, `words`, `text_only` | `full` | | `language` | string | Language hint (ISO 639-1 code) | `en` | | `region` | string | Region hint (ISO 3166-1 alpha-2) | `US` | | `translateTo` | string | Translate text to this language (ISO 639-1 code) | -- | #### Output Detail Levels - **full** -- paragraphs with nested lines and words, all with bounding boxes - **paragraphs** -- paragraph text and bounding boxes - **lines** -- line text and bounding boxes - **words** -- lines with individual word-level bounding boxes - **text_only** -- just the extracted text, no coordinate data ### Output Each run produces one result with these fields: | Field | Type | Description | |-------|------|-------------| | `imageUrl` | string | Source image URL | | `language` | string | Detected language code | | `fullText` | string | All extracted text joined | | `lines` | array | Lines with text and bounding boxes (when detail >= `lines`) | | `paragraphs` | array | Paragraphs with nested lines/words (when detail >= `paragraphs`) | | `error` | string | Error message if processing failed | #### Bounding Box Format Every text element includes a bounding box with normalized coordinates (0-1) and pixel coordinates: ```json { "centerX": 0.4457, "centerY": 0.1070, "width": 0.8512, "height": 0.1152, "rotation": 0.0032, "pixelCoords": { "x": 30, "y": 33, "width": 1265, "height": 77 } } ``` - `centerX`, `centerY` -- center point (0-1 normalized) - `width`, `height` -- dimensions (0-1 normalized) - `rotation` -- rotation angle in radians (only present when non-zero) - `pixelCoords` -- absolute pixel coordinates computed from image dimensions #### Full Output Example Real output from processing [this test image](https://tesseract.projectnaptha.com/img/eng_bw.png) with `outputDetail: "full"`: ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "language": "en", "fullText": "Mild Splendour of the various-vested Night!\n\nMother of wildly-working visions! hail!\n\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.", "lines": [ { "text": "Mild Splendour of the various-vested Night!", "boundingBox": { "centerX": 0.445742, "centerY": 0.107093, "width": 0.851279, "height": 0.115269, "rotation": 0.003223, "pixelCoords": { "x": 30, "y": 33, "width": 1265, "height": 77 } }, "words": [ { "text": "Mild", "boundingBox": { "centerX": 0.066876, "centerY": 0.105125, "width": 0.09354, "height": 0.113772, "rotation": 0.003223, "pixelCoords": { "x": 30, "y": 32, "width": 139, "height": 76 } } }, { "text": "Splendour", "boundingBox": { "centerX": 0.226699, "centerY": 0.106229, "width": 0.192463, "height": 0.115269, "rotation": 0.003223, "pixelCoords": { "x": 194, "y": 32, "width": 286, "height": 77 } } } // ... "of", "the", "various", "-", "vested", "Night", "!" ] }, { "text": "Mother of wildly-working visions! hail!", "boundingBox": { "centerX": 0.436285, "centerY": 0.21934, "width": 0.739569, "height": 0.113772, "rotation": 0.004585, "pixelCoords": { "x": 99, "y": 109, "width": 1099, "height": 76 } }, "words": [ { "text": "Mother", "boundingBox": { "centerX": 0.135817, "centerY": 0.216275, "width": 0.138627, "height": 0.113772, "rotation": 0.004585, "pixelCoords": { "x": 99, "y": 106, "width": 206, "height": 76 } } } // ... "of", "wildly", "-", "working", "visions", "!", "hail", "!" ] } // ... 6 more lines ], "paragraphs": [ { "text": "Mild Splendour of the various-vested Night!", "boundingBox": { "centerX": 0.445742, "centerY": 0.107093, "width": 0.851279, "height": 0.115269, "rotation": 0.003223, "pixelCoords": { "x": 30, "y": 33, "width": 1265, "height": 77 } }, "contentLanguage": null, "lines": [ { "text": "Mild Splendour of the various-vested Night!", "boundingBox": { "centerX": 0.445742, "centerY": 0.107093, "width": 0.851279, "height": 0.115269, "rotation": 0.003223, "pixelCoords": { "x": 30, "y": 33, "width": 1265, "height": 77 } }, "words": [ { "text": "Mild", "boundingBox": { "centerX": 0.066876, "centerY": 0.105125, "width": 0.09354, "height": 0.113772, "rotation": 0.003223, "pixelCoords": { "x": 30, "y": 32, "width": 139, "height": 76 } } }, { "text": "Splendour", "boundingBox": { "centerX": 0.226699, "centerY": 0.106229, "width": 0.192463, "height": 0.115269, "rotation": 0.003223, "pixelCoords": { "x": 194, "y": 32, "width": 286, "height": 77 } } } // ... 7 more words ] } ] } // ... 2 more paragraphs ] } ``` ### FAQ **Do I need to start the Actor before using the API?** No. The REST API answers each request directly. There's no manual step required. **Can I use both modes at the same time?** Yes. Batch runs and REST API requests are independent. You can run a batch while also making API calls. **What's the difference between the REST API and a normal run?** A normal run processes an image and saves the result to a dataset. The REST API returns the result directly in the HTTP response. Use the API for real-time requests. Use batch for one-off processing with dataset output. **What image formats are supported?** JPEG, PNG, WebP, BMP, TIFF, HEIC, and GIF. **How accurate is the text detection?** Uses the same OCR engine as Google Lens in Chrome. Accuracy is high for printed text in good lighting. Handwriting and very low-resolution images may produce partial results. **What languages are detected?** Language detection is automatic. The `language` hint improves accuracy for specific languages but doesn't limit detection. The detected language is returned in the output. **How does the bounding box data work?** Each text element (paragraph, line, word) includes normalized coordinates (0-1 range) and pixel coordinates. Normalized coordinates are relative to the image dimensions. Pixel coordinates give absolute positions for direct use in image annotation or cropping. **What is the `rotation` field?** The rotation angle in radians for text that isn't perfectly horizontal. Only included when the rotation is significant (> 0.001 radians). **Can I send base64 images instead of URLs?** Yes, via the POST `/ocr` endpoint. Include `imageBase64` in the JSON body instead of `imageUrl`. Supports raw base64 or data URI format (`data:image/png;base64,...`). **What happens if the image fails to process?** The Actor returns an error result with the `imageUrl` and `error` field set. Failed images are not charged. **Is there a rate limit?** No hard rate limit. Concurrent API requests are handled in parallel. ### Legal Compliance This Actor processes publicly accessible images provided by the user. Users are responsible for ensuring they have the rights to process the images they submit and must comply with applicable data protection regulations (GDPR, CCPA). # Actor input Schema ## `imageUrl` (type: `string`): Image URL to extract text from.

Supported formats: JPEG, PNG, WebP, BMP, TIFF, HEIC

The image is downloaded and sent directly for OCR processing. ## `outputDetail` (type: `string`): Controls the level of detail in the output.

Full — paragraphs, lines, words, and bounding boxes
Paragraphs — paragraph text and bounding boxes
Lines — line text and bounding boxes
Words — lines with individual word bounding boxes
Text only — just the extracted text, no coordinates ## `language` (type: `string`): ISO 639-1 language code to hint the OCR engine.

Common codes: en English, de German, fr French, es Spanish, ja Japanese, zh Chinese, ar Arabic, ko Korean

Improves accuracy for the specified language but doesn't prevent detection of other languages in the same image. ## `region` (type: `string`): Country used as a region hint for OCR processing. Can improve accuracy for region-specific text formats like addresses, phone numbers, and dates. ## `translateTo` (type: `string`): Translate detected text to this language using an ISO 639-1 code.

Examples: en English, de German, fr French, es Spanish, ja Japanese

Leave empty to return the original text without translation. ## `feedback` (type: `string`): For AI agents. Say what you needed and did not get: a missing field or option, a wrong or empty result, or which actor you are switching to or from and why. Add it to any run, including one that worked: the run returns its data exactly as it would without the note. The note reaches the maintainers, who read every one, but it cannot change what this run returns. ## Actor input object example ```json { "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png", "outputDetail": "full", "language": "en", "region": "US" } ``` # 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" }; // Run the Actor and wait for it to finish const run = await client.actor("zen-studio/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" } # Run the Actor and wait for it to finish run = client.actor("zen-studio/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" }' | apify call zen-studio/google-lens-ocr --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,zen-studio/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/pF3ocmhEeA8vmAaPN/builds/buY65NWXMQLiNXzlB/openapi.json