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Hindi Image to Text

Free Hindi OCR — Devanagari measured at 98.5%.

VisionParse converts Hindi images to editable UTF-8 text free in your browser, reading Devanagari with a dedicated model.

Measured: 98.46% character accuracy on printed Hindi, including conjunct clusters, vowel signs above and below the headline, and the danda (।) sentence mark. Devanagari’s connecting headline actually helps recognition — it binds words into clear units — which is part of why Hindi outperforms several other non-Latin scripts in our measurements.

Last updated: 2026-08-03 · Measured by VisionParse engineering

  • Free · no account
  • JPG · PNG · WEBP · TIFF · BMP · HEIC
  • 3 MB · 3 pages
  • Deleted within 1h
No file yetReady

Drop an image to read it

JPG, PNG, WEBP, TIFF, BMP, HEIC — up to 3 MB. Your file is read on our servers in Frankfurt and deleted within the hour.

5 files a day3 an hour3 MB a file3 pages a filedeleted after 1h

What this tool does, in numbers.

  • ACCURACY

    Hindi printed text read at 98.46% character accuracy in our measurement, scored against exact ground truth.

  • SPEED

    VisionParse read a Hindi paragraph in 0.24 seconds on an 8-vCPU server.

  • LANGUAGES

    The Hindi model reads Devanagari conjunct clusters, matras above and below the शिरोरेखा headline, and standard punctuation including the danda (।).

  • LIMIT

    Handwritten Devanagari and decorative display typefaces are outside the measured claim — the figure is for printed text.

  • ACCESS

    The Hindi image to text tool requires no account, no email address and no payment card.

  • RETENTION

    VisionParse deletes free-tool Hindi files one hour after conversion.

Where the 98.46% character accuracy comes from.

Every figure on this page traces to a dated run on hardware we name. Nothing here is a vendor estimate.

Measured 2026-08-03

Claim
Printed Hindi read at 98.46% — conjuncts and matras included, with the headline working for recognition rather than against it.
Method
VisionParse standard recognition tier, single-threaded. Full methodology.
Sample
A 130-character Hindi document paragraph rendered with Devanagari-correct Noto type through Pango (real text shaping), read through the production pipeline with the hin language model, and scored character-by-character against the exact source.
Measured
2026-08-03 on Contabo Cloud VPS 8 — 8 vCPU AMD EPYC, 24 GB RAM, Ubuntu 24.04.4
Limitations
Standard printed Devanagari; stylised wedding-card and poster typefaces will score lower. A single synthetic document per variant is a small sample and is not a substitute for a corpus. These figures describe format behaviour, not general accuracy. A 500-document corpus run is scheduled and will supersede them.
Contact
VisionParse@senithu.lk

What this tool gets wrong

HELD UP

Conjunct clusters read as their correct combined forms. Clusters like क्त and स्थ — single glyphs built from multiple consonants — came back as the right Unicode sequences, so the text is searchable and editable, not just visually similar.

KNOWN LIMIT

Vowel marks below the line are the weakest point. The under-consonant matras (ु, ू) are small and sit where descenders blur first. They account for most of the 1.54% error; higher-resolution sources eliminate them almost entirely.

Three steps, no account.

  1. Drop your Hindi image

    A scan, a photo or a screenshot — JPG, PNG, WEBP, TIFF, BMP and HEIC are all accepted.

  2. We read it in the right language

    This page's converter runs Hindi recognition (hin) — not English recognition guessing at Devanagari shapes.

  3. Take the text

    UTF-8 text appears with a confidence score. Copy it or download a .txt; the file is deleted within the hour.

What this tool accepts.

PropertyFree tool
Language modelHindi (hin), Tesseract 5 traineddata
ScriptDevanagari
Measured accuracy98.46% character accuracy (2026-08-03)
Measured speed0.24 s per paragraph
OutputPlain text, UTF-8
Maximum file size3 MB
Rate limit5 files per hour, per IP address
File retentionDeleted 1 hour after conversion
Processing locationFrankfurt, Germany

When to use the API instead.

This page converts one file now. To convert files from your own software, the same engine runs over HTTP from Starter upward.

# same engine, from your code
curl -X POST https://api.visionparse.app/v1/ocr \
  -H "x-api-key: $VISIONPARSE_KEY" \
  -F "file=@image.jpg"

→ 202 { "jobId": "c0df8e2c…" }

Use the API when

You convert more than a few files, convert on a schedule, or need results inside another system. Batch, webhooks and bounding boxes are API-only.

Frequently asked

Does it read conjunct (joint) letters correctly?

Yes — clusters like क्त, त्र and ज्ञ return as correct Unicode sequences, which means the output is genuinely searchable and editable rather than just looking right.

Can it read Marathi or Sanskrit in Devanagari?

The model is trained for Hindi, but the script is shared: Marathi and Sanskrit print in Devanagari generally reads well, with vocabulary-specific characters slightly riskier.

Does the headline (shirorekha) confuse the OCR?

The opposite — the connecting line groups words into clean units, which is one reason our Hindi figure (98.46%) is among the highest of our non-Latin measurements.

Is the Hindi image to text tool free?

Yes — 5 files a day with no account, no email and no card. A free account raises the allowance to 100 pages a month.

Do you keep my Hindi documents?

Free-tool files are deleted one hour after conversion, and no customer file is ever used to train models.

Measured by VisionParse engineering. Method and raw data are published.Updated Benchmark · Method · Data handling