# Image OCR Scraper (`seemuapps/image-ocr-scraper`) Actor Extract text from any image. Bulk OCR for screenshots, scanned documents, receipts, signs, and photos. Supports 109 languages and outputs clean Markdown or structured JSON with bounding boxes. - **URL**: https://apify.com/seemuapps/image-ocr-scraper.md - **Developed by:** [Andrew](https://apify.com/seemuapps) (community) - **Categories:** AI, Developer tools, Social media - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $30.00 / 1,000 image processeds 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 ## Image OCR Scraper Extract text from any image — bulk OCR for screenshots, scanned documents, receipts, signs, menus, business cards, and photos. Supports 109 languages with text, table, formula, and chart recognition. ### What you get - Clean extracted text in **Markdown** format (preserves headings, lists, tables) or **JSON** (with bounding boxes for each text block) - Accurate recognition powered by PaddleOCR — handles printed and handwritten text, multiple languages mixed in one image, rotated text, and low-quality scans - One output record per image with the extracted text and source URL - Bulk processing — pass up to 50 image URLs and get all text in a single run - Export to JSON or CSV directly from the Apify console ### Use cases - **Document digitization** — turn scanned PDFs, receipts, and invoices into searchable text - **Data entry automation** — pull structured data from forms, business cards, and ID documents - **Screenshot analysis** — extract text from app screenshots, error messages, or social media images - **Translation pipelines** — OCR a foreign-language image, then run the text through a translator - **Accessibility** — generate text alternatives for image-based content - **Compliance & search** — make image-heavy archives full-text searchable ### How to use 1. Paste one or more image URLs into the **Images** field (or upload files directly) 2. Choose **Output Format** — Markdown for human-readable text, JSON for structured data with positions 3. Click **Run** — extracted text appears in the **Dataset** tab when complete 4. Export results as JSON or CSV, or connect to downstream actors via the Apify API ### Output format Each dataset record: ```json { "inputImageUrl": "https://example.com/receipt.jpg", "text": "## Receipt\n\n**Store:** Example Mart\n**Date:** 2026-05-10\n\n| Item | Price |\n|------|-------|\n| Coffee | $4.50 |\n| Bagel | $3.25 |\n\n**Total:** $7.75", "outputFormat": "markdown", "status": "success", "error": null } ```` When `outputFormat` is `json`, the `text` field contains structured JSON with text blocks and bounding-box coordinates instead of Markdown. ### Input options | Field | Type | Description | |-------|------|-------------| | Images | URL list | One or more `http/https` image URLs or base64 data URIs | | Upload Images | File upload | Upload images directly from your computer | | Output Format | Select | `Markdown` (clean readable text) or `JSON` (structured with bounding boxes) — default: Markdown | ### Limits - Maximum 50 images per run - Each image must be a publicly accessible URL or a base64 data URI - Processing time is typically under 1 second per image - Supported languages: 109 including English, Spanish, French, German, Chinese, Japanese, Korean, Arabic, Hindi, and more # Actor input Schema ## `images` (type: `array`): Images to OCR. Each entry must be a publicly accessible http/https URL or a base64 data URI (data:image/jpeg;base64,...). ## `imageFiles` (type: `array`): Upload image files directly. Combined with any URLs provided above. ## `outputFormat` (type: `string`): Markdown gives clean human-readable text with structure preserved. JSON returns structured data with text positions and bounding boxes for downstream processing. ## Actor input object example ```json { "images": [ "https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test" ], "outputFormat": "markdown" } ``` # Actor output Schema ## `results` (type: `string`): One record per image: inputImageUrl, text, outputFormat, status (success|error), error. # 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 = { "images": [ "https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test" ] }; // Run the Actor and wait for it to finish const run = await client.actor("seemuapps/image-ocr-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 = { "images": ["https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test"] } # Run the Actor and wait for it to finish run = client.actor("seemuapps/image-ocr-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 '{ "images": [ "https://dummyimage.com/600x100/fff/000.png&text=Hello+World+OCR+Test" ] }' | apify call seemuapps/image-ocr-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=seemuapps/image-ocr-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Image OCR Scraper", "description": "Extract text from any image. Bulk OCR for screenshots, scanned documents, receipts, signs, and photos. Supports 109 languages and outputs clean Markdown or structured JSON with bounding boxes.", "version": "1.0", "x-build-id": "UFnfBpdIC6SitLinw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/seemuapps~image-ocr-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-seemuapps-image-ocr-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/seemuapps~image-ocr-scraper/runs": { "post": { "operationId": "runs-sync-seemuapps-image-ocr-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/seemuapps~image-ocr-scraper/run-sync": { "post": { "operationId": "run-sync-seemuapps-image-ocr-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "images": { "title": "Images", "type": "array", "description": "Images to OCR. Each entry must be a publicly accessible http/https URL or a base64 data URI (data:image/jpeg;base64,...).", "items": { "type": "string" } }, "imageFiles": { "title": "Upload Images", "type": "array", "description": "Upload image files directly. Combined with any URLs provided above.", "items": { "type": "string" } }, "outputFormat": { "title": "Output Format", "enum": [ "markdown", "json" ], "type": "string", "description": "Markdown gives clean human-readable text with structure preserved. JSON returns structured data with text positions and bounding boxes for downstream processing.", "default": "markdown" } } }, "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 } } } } } } } } } } ```