# Building a PDF Translation Pipeline · Divyam Ahuja
How I built a pipeline to translate Hindi PDFs to English using OCR and neural machine translation.
Author: Divyam Ahuja

# Building a PDF Translation Pipeline

DIVYAM AHUJA · 11 Feb 2026 | #python #ocr #ml

Recently, I needed to translate a PDF document from Hindi to English. Sounds simple enough, right? Turns out, it’s a surprisingly deep rabbit hole.

## The Pipeline

The approach I settled on follows this flow:

    PDF → Images → OCR → Translation → Rendered Images → PDF

Each step has its own set of challenges:

1. PDF to Images: Convert each page to a high-DPI image for better OCR accuracy
2. OCR: Extract text with position data using PaddleOCR
3. Translation: Run extracted text through NLLB (No Language Left Behind)
4. Rendering: Paint translated text back onto the original image
5. Assembly: Combine rendered images back into a PDF

## Lessons Learned

- DPI matters a lot — bumping from 150 to 300 DPI dramatically improved OCR accuracy for Hindi text
- Font rendering is hard — getting translated text to fit in the same bounding boxes required careful font size calculation
- Fallback strategies — TrOCR as a fallback when PaddleOCR fails on certain text regions

The code is messy but it works. Sometimes that’s enough.

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