# Scanned Document OCR with Bounding Boxes

**Use case:** 

Scanned document OCR with bounding boxes gives document-review teams genuine line positions alongside extracted text.

## Input

```json
{
  "imageUrl": "https://tesseract.projectnaptha.com/img/eng_bw.png",
  "imageUrlInputId": "",
  "imageUrls": [],
  "imagesBase64": [],
  "imageKvsRecords": [],
  "outputDetail": "full",
  "translateTo": "",
  "maxConcurrency": 3
}
```

## Output

```json
{
  "inputId": {
    "label": "Input ID",
    "format": "string"
  },
  "imageUrl": {
    "label": "Image",
    "format": "string"
  },
  "imageWidth": {
    "label": "Width",
    "format": "integer"
  },
  "imageHeight": {
    "label": "Height",
    "format": "integer"
  },
  "lineGeometryAvailable": {
    "label": "Line boxes available",
    "format": "boolean"
  },
  "wordGeometryAvailable": {
    "label": "Word boxes available",
    "format": "boolean"
  },
  "geometryLevel": {
    "label": "Geometry level",
    "format": "string"
  },
  "lines": {
    "label": "OCR lines and boxes",
    "format": "array"
  }
}
```

## About this Actor

This example demonstrates how to use [Google Lens OCR API: Batch Image to Text](https://apify.com/getascraper/google-lens-ocr) with a specific input configuration. Visit the [Actor detail page](https://apify.com/getascraper/google-lens-ocr) to learn more, explore other use cases, and run it yourself.


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This Task's input is already configured above — use it as-is rather than inventing a new one.

- **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).
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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/getascraper/google-lens-ocr.md

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).