Image to Text OCR: Extract Text from Photos and Screenshots

What it does

Text trapped in pictures is everywhere: screenshots pasted into tickets, photos of whiteboards and letters, receipts, product labels, memes. Copying it out by hand does not scale. The Image to Text OCR actor reads those images in bulk and returns the text with its line and paragraph breaks.

It takes PNG, JPEG, TIFF, WebP, GIF, BMP and JPEG 2000 links. Each image becomes one row with the recognised text, a word count and an OCR confidence score, so you can tell a crisp screenshot from a blurry phone photo at a glance. Turn on includeWords and every word also comes with its own confidence and pixel box, which is what you need for redaction or highlighting.

Recognition uses Tesseract 5 in 29 languages, up to 4 per run. Pricing is $3 per 1,000 images with no compute bill on top, and failed downloads or blank images are not charged. It is built for developers adding an image-to-text step to an app, analysts working through screenshot collections, and automations in tools like Make, n8n and Zapier.

How it works

1. You list image links in urls; scanned PDFs are accepted too and are read page by page.
2. Each image is downloaded and passed to Tesseract 5 with your chosen languages and pageSegmentation mode.
3. For screenshots and forms with scattered text, the sparse segmentation mode looks for text anywhere on the image; single-block suits receipts and snippets.
4. Each image returns one row with text, word count and confidence, plus word boxes when includeWords is on and minWordConfidence filtering if set.
5. Blank or unreadable images and failed downloads are reported free of charge.

Input example

A typical run input (JSON). Every field is also available as a form in the Apify console.

{
  "urls": [
    "https://github.com/tesseract-ocr/tessdoc/raw/main/images/eurotext.png",
    "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/phototest.tif"
  ],
  "languages": [
    "eng"
  ],
  "pageSegmentation": "sparse",
  "includeWords": true,
  "minWordConfidence": 50
}

Output example

Each image comes back as one row; the sample shows a PNG with mixed punctuation and a TIFF test page, each with its own confidence score.

Pricing

Pay per event: you are charged only for the results you receive, with no subscription. Set a maximum total charge on any run and it stops cleanly at the cap.

Prices are read from the live Apify Store listing when this page is built. The listing is always authoritative.

Use cases

How it compares

For a handful of images, your phone's built-in text selection is quicker and free. Cloud vision services can handle handwriting and difficult photos better; this actor is aimed at printed and on-screen text in bulk at a predictable price.

Limits and honest notes

• Tesseract reads printed and typed text very well (95%+ confidence on clean scans); handwriting, low-resolution photos, heavy stamps and decorative fonts come out poorly. The confidence score tells you which pages to check.
• Output is plain text in reading order with line and paragraph breaks. Tables come out as lines of text, not structured tables. Images and charts have no text to extract.
• Pages rotated by 90° or 180° are not auto-rotated; slightly skewed scans are fine.
• Up to 4 languages per run; picking only the languages your documents use is faster and more accurate. Modern Greek is not available.
• HEIC/AVIF photos and SVG are not supported (convert photos to JPEG). Files up to 100 MB; PDFs up to 2,000 pages each (200 by default).
• Password-protected PDFs need the password input. Links that return a web page instead of a file are reported and not charged.
• Respects your run budget: set a maximum total charge and processing stops cleanly at the cap, with no page charged twice.

FAQ

Use it from code

Run the actor through the Apify API with the input above.

cURL

curl -X POST "https://api.apify.com/v2/acts/actor-forge~image-to-text-ocr/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"urls": ["https://github.com/tesseract-ocr/tessdoc/raw/main/images/eurotext.png", "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/phototest.tif"], "languages": ["eng"], "pageSegmentation": "sparse", "includeWords": true, "minWordConfidence": 50}'

JavaScript (Node.js)

// Node.js 18+ (built-in fetch). Set APIFY_TOKEN in your environment.
const input = {
  "urls": [
    "https://github.com/tesseract-ocr/tessdoc/raw/main/images/eurotext.png",
    "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/phototest.tif"
  ],
  "languages": [
    "eng"
  ],
  "pageSegmentation": "sparse",
  "includeWords": true,
  "minWordConfidence": 50
};

const res = await fetch(
  "https://api.apify.com/v2/acts/actor-forge~image-to-text-ocr/run-sync-get-dataset-items",
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.APIFY_TOKEN}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify(input),
  }
);
const items = await res.json();
console.log(items.length, items[0]);

Python

# pip install apify-client   (set APIFY_TOKEN in your environment)
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "urls": [
        "https://github.com/tesseract-ocr/tessdoc/raw/main/images/eurotext.png",
        "https://raw.githubusercontent.com/tesseract-ocr/test/main/testing/phototest.tif"
    ],
    "languages": [
        "eng"
    ],
    "pageSegmentation": "sparse",
    "includeWords": True,
    "minWordConfidence": 50
}

run = client.actor("actor-forge/image-to-text-ocr").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

The run-sync-get-dataset-items endpoint waits for the run (up to 5 minutes) and returns the dataset rows directly. For longer runs, start the run asynchronously and read the dataset when it finishes, as the Python example does. Replace APIFY_TOKEN with your own token from the Apify console.

Step-by-step guides

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