REPOGEO REPORT · LITE

Topdu/OpenOCR

Default branch main · commit 0d522801 · scanned 6/1/2026, 4:21:58 AM

GitHub: 1,356 stars · 128 forks

AI VISIBILITY SCORE

35 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

1 pass · 1 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Topdu/OpenOCR, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

highreadme#1

Clarify OpenOCR's scope in the README's opening

Why:

CURRENT

OpenOCR is an open-source toolkit developed by the OCR team from FVL Lab, Fudan University, under the guidance of Prof. Yu-Gang Jiang and Prof. Zhineng Chen. It focuses on 「General-OCR」 tasks, including **Text Detection and Recognition, Formula and Table Recognition**, as well as **Document Parsing and Understanding**. The toolkit integrates a unified training and evaluation benchmark, commercial-grade OCR and Document Parsing systems, and faithful reproductions of the core implementations from a wide range of academic papers.

COPY-PASTE FIX

OpenOCR is a comprehensive open-source toolkit for General-OCR research and applications, developed by the OCR team from FVL Lab, Fudan University. **It is not merely a wrapper for existing OCR engines like Tesseract, but a full-fledged platform** integrating a unified training and evaluation benchmark, commercial-grade OCR and Document Parsing systems, and faithful reproductions of core implementations from a wide range of academic papers. OpenOCR focuses on tasks including Text Detection and Recognition, Formula and Table Recognition, and Document Parsing and Understanding.

mediumtopics#2

Expand repository topics to include specific advanced features

Why:

CURRENT

chineseocr, document-analysis, document-parsing, document-processing, ocr, ocr-pytorch, scene-text-detection, scene-text-recognition

COPY-PASTE FIX

chineseocr, document-analysis, document-parsing, document-processing, ocr, ocr-pytorch, scene-text-detection, scene-text-recognition, table-recognition, formula-recognition, document-understanding, ocr-toolkit, research-platform

mediumhomepage#3

Add a homepage URL to the repository

Why:

COPY-PASTE FIX

[Insert official project homepage URL here, e.g., a dedicated project website or FVL Lab page]

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface Topdu/OpenOCR

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Tesseract OCR

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Tesseract OCR · recommended 1×
PaddleOCR · recommended 1×
OCRmyPDF · recommended 1×
EasyOCR · recommended 1×
Surya · recommended 1×

CATEGORY QUERY
Looking for an open-source OCR toolkit for general document analysis and text recognition.
you: not recommended
AI recommended (in order):
1. Tesseract OCR
2. PaddleOCR
3. OCRmyPDF
4. EasyOCR
5. Surya
AI recommended 5 alternatives but never named Topdu/OpenOCR. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Need a robust library for document parsing, including table and formula recognition.
you: not recommended
AI recommended (in order):
1. Apache Tika (apache/tika)
2. PDFMiner.six (pdfminer/pdfminer.six)
3. Camelot (camelot-dev/camelot)
4. Mathpix OCR
5. Nougat (facebookresearch/nougat)
6. Tabula-py (tabulapdf/tabula-py)
AI recommended 6 alternatives but never named Topdu/OpenOCR. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
warn
Suggestion:
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of Topdu/OpenOCR?
pass
AI named Topdu/OpenOCR explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts Topdu/OpenOCR in production, what risks or prerequisites should they evaluate first?
pass
AI named Topdu/OpenOCR explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo Topdu/OpenOCR solve, and who is the primary audience?
pass
AI named Topdu/OpenOCR explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of Topdu/OpenOCR. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

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HTML

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Topdu/OpenOCR — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite