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Model

Pix2Text

Name: Pix2Text
Author: breezedeus

by breezedeus gh-model--breezedeus--pix2text

Nexus Index

46.0 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 71

R: Recency 85

Q: Quality 50

Tech Context

Vital Performance

0 DL / 30D

0.0%

Source →

Audited 46 FNI Score

Tiny - Params

- Context

0 Downloads

Commercial MIT License

Model Information Summary
Entity Passport
Registry ID	gh-model--breezedeus--pix2text
License	MIT
Provider	github

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Cite this model

Academic & Research Attribution

BibTeX

@misc{gh_model__breezedeus__pix2text,
  author = {breezedeus},
  title = {Pix2Text Model},
  year = {2026},
  howpublished = {\url{https://github.com/breezedeus/pix2text}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

breezedeus. (2026). Pix2Text [Model]. Free2AITools. https://github.com/breezedeus/pix2text

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone

git clone https://github.com/breezedeus/pix2text

⚖️ Nexus Index V2.0

Methodology Index Protocol

46.0

TOP 100% SYSTEM IMPACT

Semantic (S) 50

Authority (A) 0

Popularity (P) 71

Recency (R) 85

Quality (Q) 50

💬 Index Insight

FNI V2.0 for Pix2Text: Semantic (S:50), Authority (A:0), Popularity (P:71), Recency (R:85), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

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Technical Deep Dive

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📖 Doc | 👩🏻‍💻 Online Service | 👨🏻‍💻 Demo | 💬 Contact

中文 | English

Pix2Text

Update 2025.07.25: V1.1.4 Released

Major Changes:

Upgraded the Mathematical Formula Detection (MFD) and Mathematical Formula Recognition (MFR) models to version 1.5. All default configurations, documentation, and examples now use mfd-1.5 and mfr-1.5 as the standard models.

Update 2025.04.15: V1.1.3 Released

Major Changes:

Support for VlmTableOCR and VlmTextFormulaOCR models based on the VLM interface (see LiteLLM documentation) allowing the use of closed-source VLM models. Installation command: pip install pix2text[vlm].
- Usage examples can be found in tests/test_vlm.py and tests/test_pix2text.py.

Update 2024.11.17: V1.1.2 Released

Major Changes:

A new layout analysis model DocLayout-YOLO has been integrated, improving the accuracy of layout analysis.

Update 2024.06.18：V1.1.1 Released

Major changes:

Support the new mathematical formula detection models (MFD): breezedeus/pix2text-mfd (Mirror), which significantly improves the accuracy of formula detection.

See details: Pix2Text V1.1.1 Released, Bringing Better Mathematical Formula Detection Models | Breezedeus.com.

Update 2024.04.28: V1.1 Released

Major changes:

Added layout analysis and table recognition models, supporting the conversion of images with complex layouts into Markdown format. See examples: Pix2Text Online Documentation / Examples.
Added support for converting entire PDF files to Markdown format. See examples: Pix2Text Online Documentation / Examples.
Enhanced the interface with more features, including adjustments to existing interface parameters.
Launched the Pix2Text Online Documentation.

Update 2024.02.26: V1.0 Released

Main Changes:

The Mathematical Formula Recognition (MFR) model employs a new architecture and has been trained on a new dataset, achieving state-of-the-art (SOTA) accuracy. For detailed information, please see: Pix2Text V1.0 New Release: The Best Open-Source Formula Recognition Model | Breezedeus.com.

See more at: RELEASE.md .

Pix2Text (P2T) aims to be a free and open-source Python alternative to Mathpix, and it can already accomplish Mathpix's core functionality. Pix2Text (P2T) can recognize layouts, tables, images, text, mathematical formulas, and integrate all of these contents into Markdown format. P2T can also convert an entire PDF file (which can contain scanned images or any other format) into Markdown format.

Pix2Text (P2T) integrates the following models:

Layout Analysis Model: breezedeus/pix2text-layout (Mirror).
Table Recognition Model: breezedeus/pix2text-table-rec (Mirror).
Text Recognition Engine: Supports 80+ languages such as English, Simplified Chinese, Traditional Chinese, Vietnamese, etc. For English and Simplified Chinese recognition, it uses the open-source OCR tool CnOCR, while for other languages, it uses the open-source OCR tool EasyOCR.
Mathematical Formula Detection Model (MFD): breezedeus/pix2text-mfd-1.5 (Mirror). Implemented based on CnSTD.
Mathematical Formula Recognition Model (MFR): breezedeus/pix2text-mfr-1.5 (Mirror).

Several models are contributed by other open-source authors, and their contributions are highly appreciated.

For detailed explanations, please refer to the Pix2Text Online Documentation/Models.

As a Python3 toolkit, P2T may not be very user-friendly for those who are not familiar with Python. Therefore, we also provide a free-to-use P2T Online Web, where you can directly upload images and get P2T parsing results. The web version uses the latest models, resulting in better performance compared to the open-source models.

If you're interested, feel free to add the assistant as a friend by scanning the QR code and mentioning p2t. The assistant will regularly invite everyone to join the group where the latest developments related to P2T tools will be announced:

The author also maintains a Knowledge Planet P2T/CnOCR/CnSTD Private Group, where questions are answered promptly. You're welcome to join. The knowledge planet private group will also gradually release some private materials related to P2T/CnOCR/CnSTD, including some unreleased models, discounts on purchasing premium models, code snippets for different application scenarios, and answers to difficult problems encountered during use. The planet will also publish the latest research materials related to P2T/OCR/STD.

For more contact method, please refer to Contact.

List of Supported Languages

The text recognition engine of Pix2Text supports 80+ languages, including English, Simplified Chinese, Traditional Chinese, Vietnamese, etc. Among these, English and Simplified Chinese recognition utilize the open-source OCR tool CnOCR, while recognition for other languages employs the open-source OCR tool EasyOCR. Special thanks to the respective authors.

List of Supported Languages and Language Codes are shown below:

↓↓↓ Click to show details ↓↓↓

Language	Code Name
Abaza	abq
Adyghe	ady
Afrikaans	af
Angika	ang
Arabic	ar
Assamese	as
Avar	ava
Azerbaijani	az
Belarusian	be
Bulgarian	bg
Bihari	bh
Bhojpuri	bho
Bengali	bn
Bosnian	bs
Simplified Chinese	ch_sim
Traditional Chinese	ch_tra
Chechen	che
Czech	cs
Welsh	cy
Danish	da
Dargwa	dar
German	de
English	en
Spanish	es
Estonian	et
Persian (Farsi)	fa
French	fr
Irish	ga
Goan Konkani	gom
Hindi	hi
Croatian	hr
Hungarian	hu
Indonesian	id
Ingush	inh
Icelandic	is
Italian	it
Japanese	ja
Kabardian	kbd
Kannada	kn
Korean	ko
Kurdish	ku
Latin	la
Lak	lbe
Lezghian	lez
Lithuanian	lt
Latvian	lv
Magahi	mah
Maithili	mai
Maori	mi
Mongolian	mn
Marathi	mr
Malay	ms
Maltese	mt
Nepali	ne
Newari	new
Dutch	nl
Norwegian	no
Occitan	oc
Pali	pi
Polish	pl
Portuguese	pt
Romanian	ro
Russian	ru
Serbian (cyrillic)	rs_cyrillic
Serbian (latin)	rs_latin
Nagpuri	sck
Slovak	sk
Slovenian	sl
Albanian	sq
Swedish	sv
Swahili	sw
Tamil	ta
Tabassaran	tab
Telugu	te
Thai	th
Tajik	tjk
Tagalog	tl
Turkish	tr
Uyghur	ug
Ukranian	uk
Urdu	ur
Uzbek	uz
Vietnamese	vi

Ref: Supported Languages .

Online Service

Everyone can use the P2T Online Service for free, with a daily limit of 10,000 characters per account, which should be sufficient for normal use. Please refrain from bulk API calls, as machine resources are limited, and this could prevent others from accessing the service.

Due to hardware constraints, the Online Service currently only supports Simplified Chinese and English languages. To try the models in other languages, please use the following Online Demo.

Online Demo 🤗

You can also try the Online Demo to see the performance of P2T in various languages. However, the online demo operates on lower hardware specifications and may be slower. For Simplified Chinese or English images, it is recommended to use the P2T Online Service.

Examples

See: Pix2Text Online Documentation/Examples.

Usage

See: Pix2Text Online Documentation/Usage.

Models

See: Pix2Text Online Documentation/Models.

Install

Well, one line of command is enough if it goes well.

bash

pip install pix2text

If you need to recognize languages other than English and Simplified Chinese, please use the following command to install additional packages:

bash

pip install pix2text[multilingual]

If the installation is slow, you can specify an installation source, such as using the Aliyun source:

bash

pip install pix2text -i https://mirrors.aliyun.com/pypi/simple

For more information, please refer to: Pix2Text Online Documentation/Install.

Command Line Tool

See: Pix2Text Online Documentation/Command Tool.

HTTP Service

See: Pix2Text Online Documentation/Command Tool/Start Service.

MacOS Desktop Application

Please refer to Pix2Text-Mac for installing the Pix2Text Desktop App for MacOS.

A cup of coffee for the author

It is not easy to maintain and evolve the project, so if it is helpful to you, please consider offering the author a cup of coffee 🥤.

Official code base: https://github.com/breezedeus/pix2text. Please cite it properly.

For more information on Pix2Text (P2T), visit: https://www.breezedeus.com/article/pix2text.

🚀 Quick Start

bash

pip install pix2text

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository

3.1KStars

Repo Issues

🐙 Data Source: GitHub ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: gh-model--breezedeus--pix2text
slug: breezedeus--pix2text
source: github
author: breezedeus
license: MIT
tags: math-formula, ocr, latex, math-formula-recognition, mathpix, python, pytorch, layout-analysis, math-ocr, table-ocr, image-to-markdown, latex-pdf, jupyter notebook

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag: other

📊 Engagement & Metrics

downloads: 0
stars: 3,084
forks: 0

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Pix2Text

Update 2025.07.25: **V1.1.4** Released

Update 2025.04.15: **V1.1.3** Released

Update 2024.11.17: **V1.1.2** Released

Update 2024.06.18：**V1.1.1** Released

Update 2024.04.28: **V1.1** Released

Update 2024.02.26: **V1.0** Released

List of Supported Languages

Online Service

Online Demo 🤗

Examples

Usage

Models

Install

Command Line Tool

HTTP Service

MacOS Desktop Application

A cup of coffee for the author

🚀 Quick Start

⚠️ Incomplete Data

📝 Limitations & Considerations

Social Proof

🛡️ Model Transparency Report

🆔 Identity & Source

⚙️ Technical Specs

📊 Engagement & Metrics

Update 2025.07.25: V1.1.4 Released

Update 2025.04.15: V1.1.3 Released

Update 2024.11.17: V1.1.2 Released

Update 2024.06.18：V1.1.1 Released

Update 2024.04.28: V1.1 Released

Update 2024.02.26: V1.0 Released