Any URL OCR avatar

Any URL OCR

Under maintenance

Pricing

from $50.00 / 1,000 ocr per pages

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Any URL OCR

Any URL OCR

Under maintenance

Extract text from any image or PDF by URL using Tesseract OCR. Multi-language, PDF page-by-page, no paid OCR API.

Pricing

from $50.00 / 1,000 ocr per pages

Rating

0.0

(0)

Developer

Caleno

Caleno

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

21 hours ago

Last modified

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URL OCR 🔤

Extract text from any image or PDF by URL — automatic language detection, PDF support, no paid OCR API.

Point it at an image or PDF URL and get the text back. It uses a modern deep-learning OCR engine, so it reads the hard cases too: screenshots, UI and menus, photos, low-contrast scans and light-text-on-dark backgrounds — not just clean black-on-white documents.


✨ What it does

  • 🖼️ Images & 📄 PDFs — PNG, JPG, WebP, TIFF, and multi-page PDFs (processed page by page).
  • 🌍 Automatic language detection — no need to pick a language. English, Hungarian, German, French, Spanish, Italian, Portuguese, Dutch, Polish and more.
  • 🌓 Dark-background aware — automatically inverts light-text-on-dark images (navbars, hero sections, dark UI) that plain OCR reads as garbage.
  • 🎯 Clean output — plain text plus word/character counts and the detected language; PDFs also return per-page text.
  • 💸 No external OCR API — everything runs inside the actor, keeping it cheap.

🎯 Use cases

  • Digitize scanned documents, invoices and receipts
  • Pull text out of screenshots, app UIs and social posts
  • Make PDFs searchable (page-by-page text)
  • Feed extracted text into search, AI, translation or data pipelines
  • Read text from product photos and signage

📥 Input

FieldDescription
Image / PDF URLsOne or more image or PDF URLs to read.
PDF render quality (DPI)Resolution for rasterizing PDF pages (default 200).
ProxyOptional proxy for downloading the files.

Example input

{
"urls": [
"https://example.com/invoice.pdf",
"https://example.com/screenshot.png"
]
}

📤 Output

One dataset item per URL:

{
"url": "https://example.com/screenshot.png",
"type": "image",
"detectedLanguage": "en",
"words": 128,
"characters": 742,
"text": "The full extracted text …",
"width": 1440,
"height": 900
}

For a PDF you also get pageCount and a pages array with the text of each page.


⚙️ How it works

The file is downloaded, images are preprocessed (upscaled and cleaned up so small or low-contrast text is readable), and the text is recognized with a deep-learning OCR model. The language is detected from the result automatically. PDFs are rasterized page by page and each page is read separately.


💳 Pricing

Pay per page: you are charged per page processed — an image counts as one page, a PDF is charged per page. Failed URLs are free.


❓ Notes

  • Best results come from real text. Stylized logos and heavy artwork are graphics, not text, so they may not read cleanly.
  • Very low-resolution or blurry sources reduce accuracy — a higher-quality image gives better text.

Questions or a feature request? Open an issue on the actor page — the actor is actively maintained. 🔄