- 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.
- Automatically recognize and convert tables in the document to LaTeX or HTML format.
- 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.
- Supports both CPU and GPU environments.
- Compatible with Windows, Linux, and Mac platforms.
## Quick Start
If you encounter any installation issues, please first consult the <ahref="#faq">FAQ</a>. </br>
If the parsing results are not as expected, refer to the <ahref="#known-issues">Known Issues</a>. </br>
There are three different ways to experience MinerU:
There are multiple different ways to experience MinerU:
-[Online Demo (No Installation Required)](#online-demo)
-[Quick CPU Demo (Windows, Linux, Mac)](#quick-cpu-demo)
-[Linux/Windows + CUDA](#Using-GPU)
> [!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>
<tdcolspan="3"rowspan="2">Operating System</td>
</tr>
<tr>
<td>Ubuntu 22.04 LTS</td>
<td>Windows 10 / 11</td>
<td>macOS 11+</td>
</tr>
<tr>
<tdcolspan="3">CPU</td>
<td>x86_64(unsupported ARM Linux)</td>
<td>x86_64(unsupported ARM Windows)</td>
<td>x86_64 / arm64</td>
</tr>
<tr>
<tdcolspan="3">Memory</td>
<tdcolspan="3">16GB or more, recommended 32GB+</td>
</tr>
<tr>
<tdcolspan="3">Python Version</td>
<tdcolspan="3">3.10(Please make sure to create a Python 3.10 virtual environment using conda)</td>
10G VRAM or more can enable layout, formula recognition, OCR acceleration and table recognition acceleration simultaneously
</td>
</tr>
</table>
### Online Demo
...
...
@@ -251,85 +170,8 @@ You can modify certain configurations in this file to enable or disable features
}
```
### 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:
├── some_pdf_middle.json # MinerU intermediate processing result
├── some_pdf_model.json # model inference result
├── some_pdf_origin.pdf # original PDF file
├── some_pdf_spans.pdf # smallest granularity bbox position information diagram
└── some_pdf_content_list.json # Rich text JSON arranged in reading order
```
> [!TIP]
> For more information about the output files, please refer to the [Output File Description](docs/output_file_en_us.md).
### API
Processing files from local disk
...
...
@@ -386,24 +228,6 @@ TODO
-[ ] [Chemical formula recognition](docs/chemical_knowledge_introduction/introduction.pdf)
- [ ] Geometric shape recognition
# 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.
- Only one level of headings is supported; hierarchical headings are not currently supported.
- 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.
