README.md 37.6 KB
Newer Older
xuchao's avatar
xuchao committed
1
2
<div align="center" xmlns="http://www.w3.org/1999/html">
<!-- logo -->
徐超's avatar
徐超 committed
3
<p align="center">
4
  <img src="docs/images/MinerU-logo.png" width="300px" style="vertical-align:middle;">
徐超's avatar
徐超 committed
5
6
</p>

xuchao's avatar
xuchao committed
7
<!-- icon -->
8

赵小蒙's avatar
赵小蒙 committed
9
10
11
[![stars](https://img.shields.io/github/stars/opendatalab/MinerU.svg)](https://github.com/opendatalab/MinerU)
[![forks](https://img.shields.io/github/forks/opendatalab/MinerU.svg)](https://github.com/opendatalab/MinerU)
[![open issues](https://img.shields.io/github/issues-raw/opendatalab/MinerU)](https://github.com/opendatalab/MinerU/issues)
myhloli's avatar
myhloli committed
12
13
14
15
[![issue resolution](https://img.shields.io/github/issues-closed-raw/opendatalab/MinerU)](https://github.com/opendatalab/MinerU/issues)
[![PyPI version](https://badge.fury.io/py/magic-pdf.svg)](https://badge.fury.io/py/magic-pdf)
[![Downloads](https://static.pepy.tech/badge/magic-pdf)](https://pepy.tech/project/magic-pdf)
[![Downloads](https://static.pepy.tech/badge/magic-pdf/month)](https://pepy.tech/project/magic-pdf)
16

17
[![OpenDataLab](https://img.shields.io/badge/Demo_on_OpenDataLab-blue?logo=data:image/svg+xml;base64,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&labelColor=white)](https://mineru.net/OpenSourceTools/Extractor?source=github)
Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
18
19
[![HuggingFace](https://img.shields.io/badge/Demo_on_HuggingFace-yellow.svg?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAF8AAABYCAMAAACkl9t/AAAAk1BMVEVHcEz/nQv/nQv/nQr/nQv/nQr/nQv/nQv/nQr/wRf/txT/pg7/yRr/rBD/zRz/ngv/oAz/zhz/nwv/txT/ngv/0B3+zBz/nQv/0h7/wxn/vRb/thXkuiT/rxH/pxD/ogzcqyf/nQvTlSz/czCxky7/SjifdjT/Mj3+Mj3wMj15aTnDNz+DSD9RTUBsP0FRO0Q6O0WyIxEIAAAAGHRSTlMADB8zSWF3krDDw8TJ1NbX5efv8ff9/fxKDJ9uAAAGKklEQVR42u2Z63qjOAyGC4RwCOfB2JAGqrSb2WnTw/1f3UaWcSGYNKTdf/P+mOkTrE+yJBulvfvLT2A5ruenaVHyIks33npl/6C4s/ZLAM45SOi/1FtZPyFur1OYofBX3w7d54Bxm+E8db+nDr12ttmESZ4zludJEG5S7TO72YPlKZFyE+YCYUJTBZsMiNS5Sd7NlDmKM2Eg2JQg8awbglfqgbhArjxkS7dgp2RH6hc9AMLdZYUtZN5DJr4molC8BfKrEkPKEnEVjLbgW1fLy77ZVOJagoIcLIl+IxaQZGjiX597HopF5CkaXVMDO9Pyix3AFV3kw4lQLCbHuMovz8FallbcQIJ5Ta0vks9RnolbCK84BtjKRS5uA43hYoZcOBGIG2Epbv6CvFVQ8m8loh66WNySsnN7htL58LNp+NXT8/PhXiBXPMjLSxtwp8W9f/1AngRierBkA+kk/IpUSOeKByzn8y3kAAAfh//0oXgV4roHm/kz4E2z//zRc3/lgwBzbM2mJxQEa5pqgX7d1L0htrhx7LKxOZlKbwcAWyEOWqYSI8YPtgDQVjpB5nvaHaSnBaQSD6hweDi8PosxD6/PT09YY3xQA7LTCTKfYX+QHpA0GCcqmEHvr/cyfKQTEuwgbs2kPxJEB0iNjfJcCTPyocx+A0griHSmADiC91oNGVwJ69RudYe65vJmoqfpul0lrqXadW0jFKH5BKwAeCq+Den7s+3zfRJzA61/Uj/9H/VzLKTx9jFPPdXeeP+L7WEvDLAKAIoF8bPTKT0+TM7W8ePj3Rz/Yn3kOAp2f1Kf0Weony7pn/cPydvhQYV+eFOfmOu7VB/ViPe34/EN3RFHY/yRuT8ddCtMPH/McBAT5s+vRde/gf2c/sPsjLK+m5IBQF5tO+h2tTlBGnP6693JdsvofjOPnnEHkh2TnV/X1fBl9S5zrwuwF8NFrAVJVwCAPTe8gaJlomqlp0pv4Pjn98tJ/t/fL++6unpR1YGC2n/KCoa0tTLoKiEeUPDl94nj+5/Tv3/eT5vBQ60X1S0oZr+IWRR8Ldhu7AlLjPISlJcO9vrFotky9SpzDequlwEir5beYAc0R7D9KS1DXva0jhYRDXoExPdc6yw5GShkZXe9QdO/uOvHofxjrV/TNS6iMJS+4TcSTgk9n5agJdBQbB//IfF/HpvPt3Tbi7b6I6K0R72p6ajryEJrENW2bbeVUGjfgoals4L443c7BEE4mJO2SpbRngxQrAKRudRzGQ8jVOL2qDVjjI8K1gc3TIJ5KiFZ1q+gdsARPB4NQS4AjwVSt72DSoXNyOWUrU5mQ9nRYyjp89Xo7oRI6Bga9QNT1mQ/ptaJq5T/7WcgAZywR/XlPGAUDdet3LE+qS0TI+g+aJU8MIqjo0Kx8Ly+maxLjJmjQ18rA0YCkxLQbUZP1WqdmyQGJLUm7VnQFqodmXSqmRrdVpqdzk5LvmvgtEcW8PMGdaS23EOWyDVbACZzUJPaqMbjDxpA3Qrgl0AikimGDbqmyT8P8NOYiqrldF8rX+YN7TopX4UoHuSCYY7cgX4gHwclQKl1zhx0THf+tCAUValzjI7Wg9EhptrkIcfIJjA94evOn8B2eHaVzvBrnl2ig0So6hvPaz0IGcOvTHvUIlE2+prqAxLSQxZlU2stql1NqCCLdIiIN/i1DBEHUoElM9dBravbiAnKqgpi4IBkw+utSPIoBijDXJipSVV7MpOEJUAc5Qmm3BnUN+w3hteEieYKfRZSIUcXKMVf0u5wD4EwsUNVvZOtUT7A2GkffHjByWpHqvRBYrTV72a6j8zZ6W0DTE86Hn04bmyWX3Ri9WH7ZU6Q7h+ZHo0nHUAcsQvVhXRDZHChwiyi/hnPuOsSEF6Exk3o6Y9DT1eZ+6cASXk2Y9k+6EOQMDGm6WBK10wOQJCBwren86cPPWUcRAnTVjGcU1LBgs9FURiX/e6479yZcLwCBmTxiawEwrOcleuu12t3tbLv/N4RLYIBhYexm7Fcn4OJcn0+zc+s8/VfPeddZHAGN6TT8eGczHdR/Gts1/MzDkThr23zqrVfAMFT33Nx1RJsx1k5zuWILLnG/vsH+Fv5D4NTVcp1Gzo8AAAAAElFTkSuQmCC&labelColor=white)](https://huggingface.co/spaces/opendatalab/MinerU)
[![ModelScope](https://img.shields.io/badge/Demo_on_ModelScope-purple?logo=data:image/svg+xml;base64,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&labelColor=white)](https://www.modelscope.cn/studios/OpenDataLab/MinerU)
myhloli's avatar
myhloli committed
20
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/gist/myhloli/3b3a00a4a0a61577b6c30f989092d20d/mineru_demo.ipynb)
21
[![Paper](https://img.shields.io/badge/Paper-arXiv-green)](https://arxiv.org/abs/2409.18839)
22

myhloli's avatar
myhloli committed
23

xuchao's avatar
xuchao committed
24
<a href="https://trendshift.io/repositories/11174" target="_blank"><img src="https://trendshift.io/api/badge/repositories/11174" alt="opendatalab%2FMinerU | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
drunkpig's avatar
drunkpig committed
25

xuchao's avatar
xuchao committed
26
<!-- language -->
27

xuchao's avatar
xuchao committed
28
[English](README.md) | [简体中文](README_zh-CN.md)
赵小蒙's avatar
赵小蒙 committed
29

xuchao's avatar
xuchao committed
30
<!-- hot link -->
31

徐超's avatar
徐超 committed
32
<p align="center">
xuchao's avatar
xuchao committed
33
<a href="https://github.com/opendatalab/PDF-Extract-Kit">PDF-Extract-Kit: High-Quality PDF Extraction Toolkit</a>🔥🔥🔥
34
35
<br>
<br>
36
<a href="https://mineru.net/client?source=github">
37
Easier to use: Just grab MinerU Desktop. No coding, no login, just a simple interface and smooth interactions. Enjoy it without any fuss!</a>🚀🚀🚀
38

徐超's avatar
徐超 committed
39
40
</p>

xuchao's avatar
xuchao committed
41
<!-- join us -->
42

徐超's avatar
徐超 committed
43
<p align="center">
44
    👋 join us on <a href="https://discord.gg/Tdedn9GTXq" target="_blank">Discord</a> and <a href="http://mineru.space/s/V85Yl" target="_blank">WeChat</a>
徐超's avatar
徐超 committed
45
</p>
赵小蒙's avatar
赵小蒙 committed
46

xuchao's avatar
xuchao committed
47
</div>
赵小蒙's avatar
赵小蒙 committed
48

xuchao's avatar
xuchao committed
49
# Changelog
50
51
52
53
54
55
56
57
58
59

- 2025/02/24 Release 1.2.0: This version includes several fixes and improvements to enhance parsing efficiency and accuracy:
  - Performance Optimization
    - Increased classification speed for PDF documents in auto mode.
  - Parsing Optimization
    - Improved parsing logic for documents containing watermarks, significantly enhancing the parsing results for such documents.
    - Enhanced the matching logic for multiple images/tables and captions within a single page, improving the accuracy of image-text matching in complex layouts.
  - Bug Fixes
    - Fixed an issue where image/table spans were incorrectly filled into text blocks under certain conditions.
    - Resolved an issue where title blocks were empty in some cases.
myhloli's avatar
myhloli committed
60
- 2025/01/22 1.1.0 released. In this version we have focused on improving parsing accuracy and efficiency:
61
62
63
64
65
66
  - Model capability upgrade (requires re-executing the [model download process](docs/how_to_download_models_en.md) to obtain incremental updates of model files)
    - The layout recognition model has been upgraded to the latest `doclayout_yolo(2501)` model, improving layout recognition accuracy.
    - The formula parsing model has been upgraded to the latest `unimernet(2501)` model, improving formula recognition accuracy.
  - Performance optimization
    - On devices that meet certain configuration requirements (16GB+ VRAM), by optimizing resource usage and restructuring the processing pipeline, overall parsing speed has been increased by more than 50%.
  - Parsing effect optimization
67
    - Added a new heading classification feature (testing version, enabled by default) to the online demo([mineru.net](https://mineru.net/OpenSourceTools/Extractor)/[huggingface](https://huggingface.co/spaces/opendatalab/MinerU)/[modelscope](https://www.modelscope.cn/studios/OpenDataLab/MinerU)), which supports hierarchical classification of headings, thereby enhancing document structuring.
68
- 2025/01/10 1.0.1 released. This is our first official release, where we have introduced a completely new API interface and enhanced compatibility through extensive refactoring, as well as a brand new automatic language identification feature:
69
70
71
72
  - New API Interface
    - For the data-side API, we have introduced the Dataset class, designed to provide a robust and flexible data processing framework. This framework currently supports a variety of document formats, including images (.jpg and .png), PDFs, Word documents (.doc and .docx), and PowerPoint presentations (.ppt and .pptx). It ensures effective support for data processing tasks ranging from simple to complex.
    - For the user-side API, we have meticulously designed the MinerU processing workflow as a series of composable Stages. Each Stage represents a specific processing step, allowing users to define new Stages according to their needs and creatively combine these stages to customize their data processing workflows.
  - Enhanced Compatibility
73
    - By optimizing the dependency environment and configuration items, we ensure stable and efficient operation on ARM architecture Linux systems.
74
75
76
    - We have deeply integrated with Huawei Ascend NPU acceleration, providing autonomous and controllable high-performance computing capabilities. This supports the localization and development of AI application platforms in China. [Ascend NPU Acceleration](docs/README_Ascend_NPU_Acceleration_zh_CN.md)
  - Automatic Language Identification
    - By introducing a new language recognition model, setting the `lang` configuration to `auto` during document parsing will automatically select the appropriate OCR language model, improving the accuracy of scanned document parsing.
myhloli's avatar
myhloli committed
77
78
79
- 2024/11/22 0.10.0 released. Introducing hybrid OCR text extraction capabilities,
  - Significantly improved parsing performance in complex text distribution scenarios such as dense formulas, irregular span regions, and text represented by images.
  - Combines the dual advantages of accurate content extraction and faster speed in text mode, and more precise span/line region recognition in OCR mode.
myhloli's avatar
myhloli committed
80
- 2024/11/15 0.9.3 released. Integrated [RapidTable](https://github.com/RapidAI/RapidTable) for table recognition, improving single-table parsing speed by more than 10 times, with higher accuracy and lower GPU memory usage.
81
- 2024/11/06 0.9.2 released. Integrated the [StructTable-InternVL2-1B](https://huggingface.co/U4R/StructTable-InternVL2-1B) model for table recognition functionality.
82
83
84
85
- 2024/10/31 0.9.0 released. This is a major new version with extensive code refactoring, addressing numerous issues, improving performance, reducing hardware requirements, and enhancing usability:
  - Refactored the sorting module code to use [layoutreader](https://github.com/ppaanngggg/layoutreader) for reading order sorting, ensuring high accuracy in various layouts.
  - Refactored the paragraph concatenation module to achieve good results in cross-column, cross-page, cross-figure, and cross-table scenarios.
  - Refactored the list and table of contents recognition functions, significantly improving the accuracy of list blocks and table of contents blocks, as well as the parsing of corresponding text paragraphs.
86
  - Refactored the matching logic for figures, tables, and descriptive text, greatly enhancing the accuracy of matching captions and footnotes to figures and tables, and reducing the loss rate of descriptive text to near zero.
87
88
89
90
91
92
  - Added multi-language support for OCR, supporting detection and recognition of 84 languages.For the list of supported languages, see [OCR Language Support List](https://paddlepaddle.github.io/PaddleOCR/latest/en/ppocr/blog/multi_languages.html#5-support-languages-and-abbreviations).
  - Added memory recycling logic and other memory optimization measures, significantly reducing memory usage. The memory requirement for enabling all acceleration features except table acceleration (layout/formula/OCR) has been reduced from 16GB to 8GB, and the memory requirement for enabling all acceleration features has been reduced from 24GB to 10GB.
  - Optimized configuration file feature switches, adding an independent formula detection switch to significantly improve speed and parsing results when formula detection is not needed.
  - Integrated [PDF-Extract-Kit 1.0](https://github.com/opendatalab/PDF-Extract-Kit):
    - Added the self-developed `doclayout_yolo` model, which speeds up processing by more than 10 times compared to the original solution while maintaining similar parsing effects, and can be freely switched with `layoutlmv3` via the configuration file.
    - Upgraded formula parsing to `unimernet 0.2.1`, improving formula parsing accuracy while significantly reducing memory usage.
93
    - Due to the repository change for `PDF-Extract-Kit 1.0`, you need to re-download the model. Please refer to [How to Download Models](docs/how_to_download_models_en.md) for detailed steps.
sfk's avatar
sfk committed
94
- 2024/09/27 Version 0.8.1 released, Fixed some bugs, and providing a [localized deployment version](projects/web_demo/README.md) of the [online demo](https://opendatalab.com/OpenSourceTools/Extractor/PDF/) and the [front-end interface](projects/web/README.md).
drunkpig's avatar
drunkpig committed
95
- 2024/09/09: Version 0.8.0 released, supporting fast deployment with Dockerfile, and launching demos on Huggingface and Modelscope.
96
- 2024/08/30: Version 0.7.1 released, add paddle tablemaster table recognition option
xuchao's avatar
xuchao committed
97
98
99
100
101
- 2024/08/09: Version 0.7.0b1 released, simplified installation process, added table recognition functionality
- 2024/08/01: Version 0.6.2b1 released, optimized dependency conflict issues and installation documentation
- 2024/07/05: Initial open-source release

<!-- TABLE OF CONTENT -->
102

xuchao's avatar
xuchao committed
103
104
105
106
107
108
109
110
111
112
113
114
<details open="open">
  <summary><h2 style="display: inline-block">Table of Contents</h2></summary>
  <ol>
    <li>
      <a href="#mineru">MinerU</a>
      <ul>
        <li><a href="#project-introduction">Project Introduction</a></li>
        <li><a href="#key-features">Key Features</a></li>
        <li><a href="#quick-start">Quick Start</a>
            <ul>
            <li><a href="#online-demo">Online Demo</a></li>
            <li><a href="#quick-cpu-demo">Quick CPU Demo</a></li>
myhloli's avatar
myhloli committed
115
            <li><a href="#using-gpu">Using GPU</a></li>
116
            <li><a href="#using-npu">Using NPU</a></li>
xuchao's avatar
xuchao committed
117
118
119
120
            </ul>
        </li>
        <li><a href="#usage">Usage</a>
            <ul>
myhloli's avatar
myhloli committed
121
            <li><a href="#command-line">Command Line</a></li>
xuchao's avatar
xuchao committed
122
            <li><a href="#api">API</a></li>
Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
123
            <li><a href="#deploy-derived-projects">Deploy Derived Projects</a></li>
xuchao's avatar
xuchao committed
124
125
126
127
128
129
            <li><a href="#development-guide">Development Guide</a></li>
            </ul>
        </li>
      </ul>
    </li>
    <li><a href="#todo">TODO</a></li>
myhloli's avatar
myhloli committed
130
131
    <li><a href="#known-issues">Known Issues</a></li>
    <li><a href="#faq">FAQ</a></li>
xuchao's avatar
xuchao committed
132
133
134
135
136
137
138
139
140
141
142
143
    <li><a href="#all-thanks-to-our-contributors">All Thanks To Our Contributors</a></li>
    <li><a href="#license-information">License Information</a></li>
    <li><a href="#acknowledgments">Acknowledgments</a></li>
    <li><a href="#citation">Citation</a></li>
    <li><a href="#star-history">Star History</a></li>
    <li><a href="#magic-doc">Magic-doc</a></li>
    <li><a href="#magic-html">Magic-html</a></li>
    <li><a href="#links">Links</a></li>
  </ol>
</details>

# MinerU
144

xuchao's avatar
xuchao committed
145
## Project Introduction
146

xuchao's avatar
xuchao committed
147
148
149
MinerU is a tool that converts PDFs into machine-readable formats (e.g., markdown, JSON), allowing for easy extraction into any format.
MinerU was born during the pre-training process of [InternLM](https://github.com/InternLM/InternLM). We focus on solving symbol conversion issues in scientific literature and hope to contribute to technological development in the era of large models.
Compared to well-known commercial products, MinerU is still young. If you encounter any issues or if the results are not as expected, please submit an issue on [issue](https://github.com/opendatalab/MinerU/issues) and **attach the relevant PDF**.
myhloli's avatar
myhloli committed
150

Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
151
https://github.com/user-attachments/assets/4bea02c9-6d54-4cd6-97ed-dff14340982c
myhloli's avatar
myhloli committed
152

myhloli's avatar
myhloli committed
153
154
155
156
157
158
159
## Key Features

- Remove headers, footers, footnotes, page numbers, etc., to ensure semantic coherence.
- Output text in human-readable order, suitable for single-column, multi-column, and complex layouts.
- Preserve the structure of the original document, including headings, paragraphs, lists, etc.
- Extract images, image descriptions, tables, table titles, and footnotes.
- Automatically recognize and convert formulas in the document to LaTeX format.
160
- Automatically recognize and convert tables in the document to HTML format.
myhloli's avatar
myhloli committed
161
162
163
164
- Automatically detect scanned PDFs and garbled PDFs and enable OCR functionality.
- OCR supports detection and recognition of 84 languages.
- Supports multiple output formats, such as multimodal and NLP Markdown, JSON sorted by reading order, and rich intermediate formats.
- Supports various visualization results, including layout visualization and span visualization, for efficient confirmation of output quality.
165
- Supports running in a pure CPU environment, and also supports GPU(CUDA)/NPU(CANN)/MPS acceleration
myhloli's avatar
myhloli committed
166
167
- Compatible with Windows, Linux, and Mac platforms.

xuchao's avatar
xuchao committed
168
169
## Quick Start

myhloli's avatar
myhloli committed
170
171
172
If you encounter any installation issues, please first consult the <a href="#faq">FAQ</a>. </br>
If the parsing results are not as expected, refer to the <a href="#known-issues">Known Issues</a>. </br>
There are three different ways to experience MinerU:
173

xuchao's avatar
xuchao committed
174
175
- [Online Demo (No Installation Required)](#online-demo)
- [Quick CPU Demo (Windows, Linux, Mac)](#quick-cpu-demo)
176
- Accelerate inference by using CUDA/CANN/MPS
177
178
  - [Linux/Windows + CUDA](#Using-GPU)
  - [Linux + CANN](#using-npu)
179
  - [MacOS + MPS](#using-mps)
myhloli's avatar
myhloli committed
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194

> [!WARNING]
> **Pre-installation Notice—Hardware and Software Environment Support**
>
> To ensure the stability and reliability of the project, we only optimize and test for specific hardware and software environments during development. This ensures that users deploying and running the project on recommended system configurations will get the best performance with the fewest compatibility issues.
>
> By focusing resources on the mainline environment, our team can more efficiently resolve potential bugs and develop new features.
>
> In non-mainline environments, due to the diversity of hardware and software configurations, as well as third-party dependency compatibility issues, we cannot guarantee 100% project availability. Therefore, for users who wish to use this project in non-recommended environments, we suggest carefully reading the documentation and FAQ first. Most issues already have corresponding solutions in the FAQ. We also encourage community feedback to help us gradually expand support.

<table>
    <tr>
        <td colspan="3" rowspan="2">Operating System</td>
    </tr>
    <tr>
195
        <td>Linux after 2019</td>
myhloli's avatar
myhloli committed
196
197
198
199
200
        <td>Windows 10 / 11</td>
        <td>macOS 11+</td>
    </tr>
    <tr>
        <td colspan="3">CPU</td>
201
        <td>x86_64 / arm64</td>
myhloli's avatar
myhloli committed
202
203
204
205
        <td>x86_64(unsupported ARM Windows)</td>
        <td>x86_64 / arm64</td>
    </tr>
    <tr>
206
        <td colspan="3">Memory Requirements</td>
myhloli's avatar
myhloli committed
207
208
        <td colspan="3">16GB or more, recommended 32GB+</td>
    </tr>
209
210
211
212
    <tr>
        <td colspan="3">Storage Requirements</td>
        <td colspan="3">20GB or more, with a preference for SSD</td>
    </tr>
myhloli's avatar
myhloli committed
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
    <tr>
        <td colspan="3">Python Version</td>
        <td colspan="3">3.10(Please make sure to create a Python 3.10 virtual environment using conda)</td>
    </tr>
    <tr>
        <td colspan="3">Nvidia Driver Version</td>
        <td>latest (Proprietary Driver)</td>
        <td>latest</td>
        <td>None</td>
    </tr>
    <tr>
        <td colspan="3">CUDA Environment</td>
        <td>Automatic installation [12.1 (pytorch) + 11.8 (paddle)]</td>
        <td>11.8 (manual installation) + cuDNN v8.7.0 (manual installation)</td>
        <td>None</td>
    </tr>
229
230
231
232
233
234
    <tr>
        <td colspan="3">CANN Environment(NPU support)</td>
        <td>8.0+(Ascend 910b)</td>
        <td>None</td>
        <td>None</td>
    </tr>
myhloli's avatar
myhloli committed
235
236
    <tr>
        <td rowspan="2">GPU Hardware Support List</td>
237
238
239
        <td colspan="2">GPU VRAM 8GB or more</td>
        <td colspan="2">2080~2080Ti / 3060Ti~3090Ti / 4060~4090<br>
        8G VRAM can enable all acceleration features</td>
myhloli's avatar
myhloli committed
240
241
242
        <td rowspan="2">None</td>
    </tr>
</table>
xuchao's avatar
xuchao committed
243
244
245

### Online Demo

Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
246
Synced with dev branch updates:
247

Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
248
[![OpenDataLab](https://img.shields.io/badge/Demo_on_OpenDataLab-blue?logo=data:image/svg+xml;base64,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&labelColor=white)](https://mineru.net/OpenSourceTools/Extractor?source=github)
Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
249
250
[![HuggingFace](https://img.shields.io/badge/Demo_on_HuggingFace-yellow.svg?logo=data:image/png;base64,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&labelColor=white)](https://huggingface.co/spaces/opendatalab/MinerU)
[![ModelScope](https://img.shields.io/badge/Demo_on_ModelScope-purple?logo=data:image/svg+xml;base64,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&labelColor=white)](https://www.modelscope.cn/studios/OpenDataLab/MinerU)
xuchao's avatar
xuchao committed
251
252
253
254

### Quick CPU Demo

#### 1. Install magic-pdf
255

256
```bash
257
258
conda create -n mineru python=3.10
conda activate mineru
259
pip install -U "magic-pdf[full]" --extra-index-url https://wheels.myhloli.com
260
```
261

xuchao's avatar
xuchao committed
262
263
264
#### 2. Download model weight files

Refer to [How to Download Model Files](docs/how_to_download_models_en.md) for detailed instructions.
265

266
#### 3. Modify the Configuration File for Additional Configuration
xuchao's avatar
xuchao committed
267

268
269
After completing the [2. Download model weight files](#2-download-model-weight-files) step, the script will automatically generate a `magic-pdf.json` file in the user directory and configure the default model path.
You can find the `magic-pdf.json` file in your 【user directory】.
270

271
> [!TIP]
272
> The user directory for Windows is "C:\\Users\\username", for Linux it is "/home/username", and for macOS it is "/Users/username".
273

274
You can modify certain configurations in this file to enable or disable features, such as table recognition:
275

myhloli's avatar
myhloli committed
276

277
> [!NOTE]
278
> If the following items are not present in the JSON, please manually add the required items and remove the comment content (standard JSON does not support comments).
279

280
281
```json
{
282
283
    // other config
    "layout-config": {
284
        "model": "doclayout_yolo" // Please change to "layoutlmv3" when using layoutlmv3.
285
286
287
288
289
290
291
    },
    "formula-config": {
        "mfd_model": "yolo_v8_mfd",
        "mfr_model": "unimernet_small",
        "enable": true  // The formula recognition feature is enabled by default. If you need to disable it, please change the value here to "false".
    },
    "table-config": {
292
        "model": "rapid_table",  // Default to using "rapid_table", can be switched to "tablemaster" or "struct_eqtable".
293
        "sub_model": "slanet_plus",  // When the model is "rapid_table", you can choose a sub_model. The options are "slanet_plus" and "unitable"
294
        "enable": true, // The table recognition feature is enabled by default. If you need to disable it, please change the value here to "false".
xuchao's avatar
xuchao committed
295
296
        "max_time": 400
    }
297
298
299
}
```

myhloli's avatar
myhloli committed
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
### Using GPU

If your device supports CUDA and meets the GPU requirements of the mainline environment, you can use GPU acceleration. Please select the appropriate guide based on your system:

- [Ubuntu 22.04 LTS + GPU](docs/README_Ubuntu_CUDA_Acceleration_en_US.md)
- [Windows 10/11 + GPU](docs/README_Windows_CUDA_Acceleration_en_US.md)
- Quick Deployment with Docker
> [!IMPORTANT]
> Docker requires a GPU with at least 8GB of VRAM, and all acceleration features are enabled by default.
>
> Before running this Docker, you can use the following command to check if your device supports CUDA acceleration on Docker.
> 
> ```bash
> docker run --rm --gpus=all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi
> ```
  ```bash
316
  wget https://github.com/opendatalab/MinerU/raw/master/docker/global/Dockerfile -O Dockerfile
myhloli's avatar
myhloli committed
317
  docker build -t mineru:latest .
318
  docker run -it --name mineru --gpus=all mineru:latest /bin/bash -c "echo 'source /opt/mineru_venv/bin/activate' >> ~/.bashrc && exec bash"
myhloli's avatar
myhloli committed
319
320
321
  magic-pdf --help
  ```

322
323
324
### Using NPU

If your device has NPU acceleration hardware, you can follow the tutorial below to use NPU acceleration:
325

326
[Ascend NPU Acceleration](docs/README_Ascend_NPU_Acceleration_zh_CN.md)
327

328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
### Using MPS

If your device uses Apple silicon chips, you can enable MPS acceleration for certain supported tasks (such as layout detection and formula detection).

You can enable MPS acceleration by setting the `device-mode` parameter to `mps` in the `magic-pdf.json` configuration file.

```json
{
    // other config
    "device-mode": "mps"
}
```

> [!TIP]
> Since the formula recognition task cannot utilize MPS acceleration, you can disable the formula recognition feature in tasks where it is not needed to achieve optimal performance.
>
> You can disable the formula recognition feature by setting the `enable` parameter in the `formula-config` section to `false`.

xuchao's avatar
xuchao committed
346
## Usage
347

myhloli's avatar
myhloli committed
348
349
### Command Line

350
[Using MinerU via Command Line](https://mineru.readthedocs.io/en/latest/user_guide/usage/command_line.html)
myhloli's avatar
myhloli committed
351
352
353
354

> [!TIP]
> For more information about the output files, please refer to the [Output File Description](docs/output_file_en_us.md).

xuchao's avatar
xuchao committed
355
### API
赵小蒙's avatar
赵小蒙 committed
356

357
[Using MinerU via Python API](https://mineru.readthedocs.io/en/latest/user_guide/usage/api.html)
赵小蒙's avatar
赵小蒙 committed
358

赵小蒙's avatar
赵小蒙 committed
359

360
361
### Deploy Derived Projects

Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
362
Derived projects include secondary development projects based on MinerU by project developers and community developers,  
363
such as application interfaces based on Gradio, RAG based on llama, web demos similar to the official website, lightweight multi-GPU load balancing client/server ends, etc.
Xiaomeng Zhao's avatar
Xiaomeng Zhao committed
364
These projects may offer more features and a better user experience.  
365
366
367
For specific deployment methods, please refer to the [Derived Project README](projects/README.md)


xuchao's avatar
xuchao committed
368
### Development Guide
赵小蒙's avatar
赵小蒙 committed
369

xuchao's avatar
xuchao committed
370
TODO
赵小蒙's avatar
赵小蒙 committed
371

xuchao's avatar
xuchao committed
372
# TODO
赵小蒙's avatar
赵小蒙 committed
373

374
375
376
- [x] Reading order based on the model  
- [x] Recognition of `index` and `list` in the main text  
- [x] Table recognition
myhloli's avatar
myhloli committed
377
- [x] Heading Classification
378
379
380
- [ ] Code block recognition in the main text
- [ ] [Chemical formula recognition](docs/chemical_knowledge_introduction/introduction.pdf)
- [ ] Geometric shape recognition
赵小蒙's avatar
赵小蒙 committed
381

myhloli's avatar
myhloli committed
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
# Known Issues

- Reading order is determined by the model based on the spatial distribution of readable content, and may be out of order in some areas under extremely complex layouts.
- Vertical text is not supported.
- Tables of contents and lists are recognized through rules, and some uncommon list formats may not be recognized.
- Code blocks are not yet supported in the layout model.
- Comic books, art albums, primary school textbooks, and exercises cannot be parsed well.
- Table recognition may result in row/column recognition errors in complex tables.
- OCR recognition may produce inaccurate characters in PDFs of lesser-known languages (e.g., diacritical marks in Latin script, easily confused characters in Arabic script).
- Some formulas may not render correctly in Markdown.

# FAQ

[FAQ in Chinese](docs/FAQ_zh_cn.md)

[FAQ in English](docs/FAQ_en_us.md)

赵小蒙's avatar
赵小蒙 committed
399
400
# All Thanks To Our Contributors

401
<a href="https://github.com/opendatalab/MinerU/graphs/contributors">
赵小蒙's avatar
赵小蒙 committed
402
403
404
405
406
407
408
  <img src="https://contrib.rocks/image?repo=opendatalab/MinerU" />
</a>

# License Information

[LICENSE.md](LICENSE.md)

xuchao's avatar
xuchao committed
409
This project currently uses PyMuPDF to achieve advanced functionality. However, since it adheres to the AGPL license, it may impose restrictions on certain usage scenarios. In future iterations, we plan to explore and replace it with a more permissive PDF processing library to enhance user-friendliness and flexibility.
赵小蒙's avatar
赵小蒙 committed
410
411

# Acknowledgments
412

xuchao's avatar
xuchao committed
413
- [PDF-Extract-Kit](https://github.com/opendatalab/PDF-Extract-Kit)
414
- [DocLayout-YOLO](https://github.com/opendatalab/DocLayout-YOLO)
xuchao's avatar
xuchao committed
415
- [StructEqTable](https://github.com/UniModal4Reasoning/StructEqTable-Deploy)
416
- [RapidTable](https://github.com/RapidAI/RapidTable)
赵小蒙's avatar
赵小蒙 committed
417
418
- [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)
- [PyMuPDF](https://github.com/pymupdf/PyMuPDF)
419
- [layoutreader](https://github.com/ppaanngggg/layoutreader)
赵小蒙's avatar
赵小蒙 committed
420
421
- [fast-langdetect](https://github.com/LlmKira/fast-langdetect)
- [pdfminer.six](https://github.com/pdfminer/pdfminer.six)
赵小蒙's avatar
赵小蒙 committed
422

赵小蒙's avatar
赵小蒙 committed
423
424
425
# Citation

```bibtex
426
427
428
429
430
431
432
433
434
435
@misc{wang2024mineruopensourcesolutionprecise,
      title={MinerU: An Open-Source Solution for Precise Document Content Extraction}, 
      author={Bin Wang and Chao Xu and Xiaomeng Zhao and Linke Ouyang and Fan Wu and Zhiyuan Zhao and Rui Xu and Kaiwen Liu and Yuan Qu and Fukai Shang and Bo Zhang and Liqun Wei and Zhihao Sui and Wei Li and Botian Shi and Yu Qiao and Dahua Lin and Conghui He},
      year={2024},
      eprint={2409.18839},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2409.18839}, 
}

Conghui He's avatar
Conghui He committed
436
437
438
439
440
441
@article{he2024opendatalab,
  title={Opendatalab: Empowering general artificial intelligence with open datasets},
  author={He, Conghui and Li, Wei and Jin, Zhenjiang and Xu, Chao and Wang, Bin and Lin, Dahua},
  journal={arXiv preprint arXiv:2407.13773},
  year={2024}
}
赵小蒙's avatar
赵小蒙 committed
442
443
444
```

# Star History
赵小蒙's avatar
赵小蒙 committed
445

赵小蒙's avatar
赵小蒙 committed
446
447
448
449
450
451
<a>
 <picture>
   <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=opendatalab/MinerU&type=Date&theme=dark" />
   <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=opendatalab/MinerU&type=Date" />
   <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=opendatalab/MinerU&type=Date" />
 </picture>
myhloli's avatar
myhloli committed
452
</a>
qiangqiang199's avatar
qiangqiang199 committed
453

xuchao's avatar
xuchao committed
454
# Magic-doc
455

xuchao's avatar
xuchao committed
456
457
458
[Magic-Doc](https://github.com/InternLM/magic-doc) Fast speed ppt/pptx/doc/docx/pdf extraction tool

# Magic-html
459

xuchao's avatar
xuchao committed
460
461
[Magic-HTML](https://github.com/opendatalab/magic-html) Mixed web page extraction tool

qiangqiang199's avatar
qiangqiang199 committed
462
# Links
xuchao's avatar
xuchao committed
463

qiangqiang199's avatar
qiangqiang199 committed
464
465
- [LabelU (A Lightweight Multi-modal Data Annotation Tool)](https://github.com/opendatalab/labelU)
- [LabelLLM (An Open-source LLM Dialogue Annotation Platform)](https://github.com/opendatalab/LabelLLM)
qiangqiang199's avatar
qiangqiang199 committed
466
- [PDF-Extract-Kit (A Comprehensive Toolkit for High-Quality PDF Content Extraction)](https://github.com/opendatalab/PDF-Extract-Kit)