# OCR Text Extractor: text from images and scanned PDFs (`examsens.ai/ocr-text-extractor`) Actor

Reads the text in images (PNG, JPEG, WebP, TIFF) and scanned PDF files you link to, page by page, with a confidence score for every line. OCR runs inside the actor; no outside service is called.

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

## Pricing

from $20.00 / 1,000 page 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/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

## OCR Text Extractor: text from images and scanned PDFs

Give it links to images or PDF files and it returns the text on every page, read with optical character recognition (OCR). Each page comes with a mean confidence score, and you can ask for every line with its own confidence and position.

- Images: PNG, JPEG, WebP, BMP, GIF, and multi page TIFF (each frame is a page)
- PDF files: each page is rendered and read. Pages that already carry a text layer can return that text directly, without OCR
- Tested on English, German, French, Italian, Spanish and Portuguese text, and on a typewritten scan from 1946

OCR runs inside the actor with RapidOCR and the PP-OCRv6 models. No outside OCR service is called and no API key is needed.

### Input

- Image or PDF URLs (required), up to 50 MB per file
- Use the PDF text layer when present (default on)
- Maximum pages per file (default 50)
- PDF render resolution in DPI (default 200)
- Minimum line confidence in percent (default 50): lines below it are dropped
- Include line details (default off): every line with its confidence and bounding box

### Output

Dataset: one item per file with `url`, `ok`, `fileType` (`pdf` or `image`), `pageCount`, `pagesProcessed`, `text` (all pages), and `pages`. Each page has `page`, `method` (`ocr` or `text-layer`), `text`, `meanConfidence`, and with line details on, `lines`. A file that cannot be downloaded or read gets `ok: false` and an `error`. Export as JSON, CSV or Excel, or read it over the API.

### Pricing

Pay per event: one event per page processed, whether read by OCR or from the text layer. Set the page limit to control cost. The run stops when it reaches the maximum charge you set, and the file it stopped in is marked with a `note`.

### Scope and conduct

Only the URLs you supply are fetched. Files are processed in memory and nothing is kept beyond the run's own dataset. Handwriting was not tested.

Apify gives a run one CPU core for every 4 GB of memory, so OCR speed follows the memory you choose. A full page of small print (a US tax form) took about 20 seconds with 4 GB.

### Support

Questions and problems: the Issues tab on this page. Replies are written by an AI assistant on behalf of the developer and reviewed by the developer.

# Actor input Schema

## `fileUrls` (type: `array`):

Direct links to images (PNG, JPEG, WebP, BMP, GIF, TIFF) or PDF files, up to 50 MB each. Use files you own or are allowed to process.

## `useTextLayer` (type: `boolean`):

For PDF pages that already contain text (20 characters or more), return that text and skip OCR. Turn off to OCR every page.

## `maxPagesPerFile` (type: `integer`):

Stop after this many pages (or TIFF frames) in each file. Each processed page is one billable event.

## `pdfDpi` (type: `integer`):

Resolution used to turn PDF pages into images before OCR.

## `minConfidencePercent` (type: `integer`):

Drop recognized lines whose confidence is below this percentage.

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

Add every recognized line with its confidence and bounding box (pixel corners) to each page.

## Actor input object example

```json
{
  "fileUrls": [
    {
      "url": "https://raw.githubusercontent.com/tesseract-ocr/tessdoc/main/images/eurotext.png"
    }
  ],
  "useTextLayer": true,
  "maxPagesPerFile": 50,
  "pdfDpi": 200,
  "minConfidencePercent": 50,
  "includeLines": false
}
```

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

// Prepare Actor input
const input = {
    "fileUrls": [
        {
            "url": "https://raw.githubusercontent.com/tesseract-ocr/tessdoc/main/images/eurotext.png"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("examsens.ai/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 = { "fileUrls": [{ "url": "https://raw.githubusercontent.com/tesseract-ocr/tessdoc/main/images/eurotext.png" }] }

# Run the Actor and wait for it to finish
run = client.actor("examsens.ai/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 '{
  "fileUrls": [
    {
      "url": "https://raw.githubusercontent.com/tesseract-ocr/tessdoc/main/images/eurotext.png"
    }
  ]
}' |
apify call examsens.ai/ocr-text-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,examsens.ai/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/CfhDEngkx5GRhDw8e/builds/EXp4wYRNXUmJFDBM2/openapi.json