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IMAGE TO TEXT (OCR)

Photo, screenshot ya document yahan drop karein

JPG, PNG, WebP, BMP · aapki image kabhi upload nahi hoti

Pehli baar language data download hota hai

Image preview yahan dikhegi

Extracted text

IMAGE SE TEXT KAISE NIKAALEIN — POORA GUIDE

OCR (Optical Character Recognition) ka matlab hai — photo ke andar dekhe gaye text ko digital text me badal dena. Aaj ye kaam na kare to bhi zaroori ho jaata hai: koi aadhar/PAN card ki copy, invoice ka number, WhatsApp par bheja screenshot, newspaper ka column, ya kisi form me likha content — ye sab manually type karne me ghanton lagte hain.

Sahi photo = sahi result

OCR ki quality seedha aapki photo ki quality se aati hai. Ye cheezein accuracy barhaati hain:

  • Text page par sida hua aur seedha ho, tilt na ho
  • Page ko flat light me rakhiye — window ki roshni se, chhat ke neeche se nahi
  • Chamak (glare) na ho — flashlight ya dhundh se bachayein
  • Font jitna bada utna achha — chhoti handwriting sabse mushkil hoti hai
  • Photo original resolution me lo, compress mat karein
  • Background saaf ho — rang ya design wala paper text ko confuse karta hai

Confidence kya kahta hai

Har character par engine ko ek confidence milta hai, aur page ka average aapko dikhta hai. 80% se upar — aam taur par bharosa karne layak. 60-80% — kuch characters galat hue honge, proofread zaroor karein. 60% se neeche — dobara photo lo, better light me. Galat number ya naam padh kar koi kaam karna sabse buri cheez hai.

Jab OCR ki zaroorat na pade

Agar PDF ya e-book me text selectable hai, to use copy karna hamesha behtar hai — wo 100% accurate hai aur seconds lagta hai. OCR sirf tab chahiye jab text image ke roop me "chhupa" ho: scanned page, document ki photo, screenshot ya WhatsApp image. Isliye pehle try kar lijiye ki text copy ho raha hai ya nahi.

Aapki privacy

Ye tool recognition aapke browser me karta hai. Aadhar card, bank statement, ya koi personal document ki photo kisi server par nahi jaati — kyunki server par jaane ka koi code hi nahi hai. Ye isliye zaroori hai kyunki jo image aap upload karte hain, wo aksar aapke kisi document ka original hota hai.

Common kaam jinke liye ye aata hai

  • Aadhar / PAN / voter ID ka number copy karna
  • Invoice aur bill me item ke naam, GST number, date
  • WhatsApp par bheja hua text ka hisaab (kisi ne kitna kitna)
  • Handwriting waale form ya register
  • Book ya board ka content digital banana
  • Hindi board, newspaper, railway notice

IMAGE TO TEXT — SAWAAL JAWAAB

Frequently Asked Questions (FAQ)

No. The recognition runs inside your browser using a compiled OCR engine, so your photo, receipt or screenshot is never sent to a server. The only thing that downloads is the language data file itself, once, and then it is cached by your browser. That also means it works even on an unreliable connection after the first use.

OCR quality depends almost entirely on the photo, not the tool. The engine struggles with a small or blurry font, a skewed or sideways page, low contrast text, a glare streak across the page, and handwriting unless the writing is very clear. A phone photo of a document held flat in good light reads far better than a screenshot of a compressed social media image.

English is the default and by far the most accurate. Hindi is available as a separate language pack. Indian signboards, invoices and railway notices in Devanagari are the practical case for Hindi. You can switch the language before running recognition, and the first run of a new language downloads its data file, so the next run starts faster.

It is how sure the engine is about the characters it read, averaged across the page. Above roughly eighty percent you can generally trust the result. Between sixty and eighty usually means a few characters were misread and you should proofread anything important. Below that, a retake of the photo in better light will beat any amount of manual correction.

Partially. Printed text is far easier for the engine than handwriting. Clear block capitals like a register or a form can read reasonably well. Cursive handwriting, faded pencil, and text over a busy background usually do not come out well, and a wrong number or a name in a document is worse than no output at all, so always proofread before acting on handwriting.

The practical limit is your browser memory. Images up to about ten megapixels work comfortably. Very large photos are scaled down slightly before recognition, because the engine gains nothing from extreme resolution and a huge canvas is where browsers start struggling. If a large image is rejected, resize or screenshot only the text region instead.

Not directly here, because this tool takes images. For a PDF, open it and take a screenshot of the pages you need, or use the site PDF tools. If a PDF has selectable text then copying it directly is always more accurate than OCR, so only reach for OCR when the text is scanned into the image.

Usually there was no text at the resolution the engine saw, or the text was too small. Another common cause is that the image is a photo of a screen showing a photo, so you have two layers of compression. Check the preview looks clear and correctly oriented, and if the text occupies only a small part of a large photo, crop to the text and run it again.

The result appears in an editable box, so you can fix any character the engine got wrong before copying or downloading. That is the normal workflow with OCR rather than an exception: treat the output as a very good first draft and correct the few places it drifted.

Yes. There is no account, no limit on how many images you process, and nothing to install. The whole point of doing recognition locally is that the tool costs the site nothing per image, so there is nothing to meter.

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