# Image OCR & Scanned PDF to Text — 19 Languages, Line Boxes (`northbell/image-ocr-text-extractor`) Actor

Read the text in images (PNG, JPEG, WebP, BMP) and scanned PDFs with OCR. One row per image or page with the text, confidence and optional line boxes. Pages that already have a text layer are taken as is. 19 languages incl. Japanese, Chinese, Korean, Arabic. $3 per 1,000 pages.

- **URL**: https://apify.com/northbell/image-ocr-text-extractor.md
- **Developed by:** [Northbell](https://apify.com/northbell) (community)
- **Categories:** AI, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.40 / 1,000 image or page reads

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

## Image OCR & Scanned PDF to Text — 19 Languages, Line Boxes

Paste links to **images** (PNG, JPEG, WebP, BMP) or **PDFs** and get the **text in them** as clean JSON: one row per image or PDF page, with the **OCR confidence**, word count and, if you want, **every line with its position**. **Scanned PDFs** are read page by page; PDF pages that already have a text layer are taken as is (exact and free of OCR mistakes). **19 languages**, including Japanese, Chinese, Korean, Arabic, Hindi and Thai. The reading happens inside the run — your files are not sent to any other OCR service.

**Try it now. The input is already filled in.** Press **Start**: one scanned English page (Tesseract's sample image) — **8 lines, 58 words in about 7 seconds, for $0.013**, confidence 92 (measured on 28 Oct 2026). The first lines of `text`:

```
Mild Splendour of the various-vested Night!
Mother of wildly-working visions! hail
I watch thy gliding, while with watery light
```

The row also has the image size, line count and the language used.

### What you get

| Row | Fields |
|---|---|
| `page` | `url`, `page` and `pageCount` (PDFs), `method` (`ocr` / `text-layer`), `text`, `confidence` (0-100), `words`, `chars`, `lineCount`, `lines` (with *Include lines with position*: `text`, `confidence`, `box` {x, y, width, height}), `width`, `height`, `fileType`, `fileBytes`, `languages`, `note` |
| `error` | `url`, `message` — free |

### Use it for

- **Scanned documents**: contracts, letters, old reports and faxes that are only pictures inside a PDF
- **Receipts and invoices**: amounts, dates and reference numbers, with line boxes to find where each value sits
- **Screenshots and product images**: text on banners, labels, menus and slides
- **AI and RAG**: turn image-only documents into text your pipeline can search and embed

### Input

```json
{ "urls": ["https://tesseract.projectnaptha.com/img/eng_bw.png"], "languages": ["eng"], "includeLines": true }
```

Measured on 23 October 2026 (our own test files): a 1240×700 invoice image read in about 2 seconds with 90+ confidence; a 2-page scanned PDF and a 1-bit fax-style PDF read page by page; Japanese read correctly with `jpn`.

### How it reads

- Each site's **robots.txt is read first** (the rules for all robots and those addressed to Claude crawlers); links it does not allow are skipped with a free error row. Links to private networks are not read.
- OCR is done with **Tesseract** (LSTM models) inside the run. Clear, straight text at a normal size reads best; blurry, tiny, rotated or handwritten text reads poorly — the `confidence` and a `note` tell you when to be careful.
- In a scanned PDF, the largest picture on each page is read. GIF, TIFF and SVG are not read (free error row).
- Pick only the languages that are in your files (up to 3): each extra language makes reading slower and slightly less accurate.

### Pricing

**$3 per 1,000 images or pages** ($0.003 each), plus $0.01 per run. Images and pages where no text is found, and error rows, are free. The $0.01 run-start fee is the one charge every run pays, even one that returns nothing.

### For AI agents

`{"urls": ["https://example.com/scan.pdf"], "languages": ["eng"]}` returns one `page` row per page with its `text` and `confidence`. Rows have `type`: `page` or `error`.

# Actor input Schema

## `urls` (type: `array`):

Direct links to images (PNG, JPEG, WebP, BMP) or PDFs, one per line. Scanned PDFs are read page by page.

## `languages` (type: `array`):

The language(s) of the text, up to 3. Pick only what is there: each extra language makes reading slower and a little less accurate.

## `includeLines` (type: `boolean`):

Add every line of text with its confidence and its box (x, y, width, height in pixels). Useful for receipts, forms and tables.

## `forceOcr` (type: `boolean`):

By default a PDF page that already has a text layer is taken as is (exact and fast). Turn this on to read the picture of every page instead, for PDFs whose text layer is wrong.

## `maxPagesPerPdf` (type: `integer`):

Pages read from each PDF, from the first page.

## `maxFileMb` (type: `integer`):

Larger files are skipped with a free error row.

## Actor input object example

```json
{
  "urls": [
    "https://tesseract.projectnaptha.com/img/eng_bw.png"
  ],
  "languages": [
    "eng"
  ],
  "includeLines": false,
  "forceOcr": false,
  "maxPagesPerPdf": 50,
  "maxFileMb": 30
}
```

# Actor output Schema

## `pages` (type: `string`):

Text, confidence, words, optional line boxes.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "urls": [
        "https://tesseract.projectnaptha.com/img/eng_bw.png"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("northbell/image-ocr-text-extractor").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "urls": ["https://tesseract.projectnaptha.com/img/eng_bw.png"] }

# Run the Actor and wait for it to finish
run = client.actor("northbell/image-ocr-text-extractor").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 '{
  "urls": [
    "https://tesseract.projectnaptha.com/img/eng_bw.png"
  ]
}' |
apify call northbell/image-ocr-text-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,northbell/image-ocr-text-extractor"
        }
    }
}
```

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 <APIFY_API_TOKEN>` 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/7082gvmYaeyZHfBtY/builds/AqsnGE9BSlf8xcQsy/openapi.json