Skip to content

GitLab

Unverified Commit 784c61a2 authored by Xiaomeng Zhao's avatar Xiaomeng Zhao Committed by GitHub
Browse files

Merge pull request #906 from icecraft/feat/add_en_docs 

Feat/add en docs
parents 5f794533 91f8cbe2
Hide whitespace changes
Inline Side-by-side
Showing with 405 additions and 69 deletions
docs/zh_cn/user_guide/tutorial.rst 0 → 100644
View file @ 784c61a2
教程
===========
让我们通过构建一个最小项目来学习 MinerU
.. toctree::
:maxdepth: 1
:caption: 教程
tutorial/output_file_description
docs/zh_cn/user_guide/tutorial/output_file_description.rst 0 → 100644
View file @ 784c61a2
输出文件格式介绍
===============
``magic-pdf`` 命令执行后除了输出和 markdown
有关的文件以外，还会生成若干个和 markdown
无关的文件。现在将一一介绍这些文件
some_pdf_layout.pdf
~~~~~~~~~~~~~~~~~~~
每一页的 layout 均由一个或多个框组成。
每个框左上脚的数字表明它们的序号。此外 layout.pdf
框内用不同的背景色块圈定不同的内容块。
.. figure:: ../../_static/image/layout_example.png
:alt: layout 页面示例
layout 页面示例
some_pdf_spans.pdf
~~~~~~~~~~~~~~~~~~
根据 span 类型的不同，采用不同颜色线框绘制页面上所有
span。该文件可以用于质检，可以快速排查出文本丢失、行间公式未识别等问题。
.. figure:: ../../_static/image/spans_example.png
:alt: span 页面示例
span 页面示例
some_pdf_model.json
~~~~~~~~~~~~~~~~~~~
结构定义
^^^^^^^^
.. code:: python
from pydantic import BaseModel, Field
from enum import IntEnum
class CategoryType(IntEnum):
title = 0 # 标题
plain_text = 1 # 文本
abandon = 2 # 包括页眉页脚页码和页面注释
figure = 3 # 图片
figure_caption = 4 # 图片描述
table = 5 # 表格
table_caption = 6 # 表格描述
table_footnote = 7 # 表格注释
isolate_formula = 8 # 行间公式
formula_caption = 9 # 行间公式的标号
embedding = 13 # 行内公式
isolated = 14 # 行间公式
text = 15 # ocr 识别结果
class PageInfo(BaseModel):
page_no: int = Field(description="页码序号，第一页的序号是 0", ge=0)
height: int = Field(description="页面高度", gt=0)
width: int = Field(description="页面宽度", ge=0)
class ObjectInferenceResult(BaseModel):
category_id: CategoryType = Field(description="类别", ge=0)
poly: list[float] = Field(description="四边形坐标, 分别是 左上，右上，右下，左下 四点的坐标")
score: float = Field(description="推理结果的置信度")
latex: str | None = Field(description="latex 解析结果", default=None)
html: str | None = Field(description="html 解析结果", default=None)
class PageInferenceResults(BaseModel):
layout_dets: list[ObjectInferenceResult] = Field(description="页面识别结果", ge=0)
page_info: PageInfo = Field(description="页面元信息")
# 所有页面的推理结果按照页码顺序依次放到列表中即为 minerU 推理结果
inference_result: list[PageInferenceResults] = []
poly 坐标的格式 [x0, y0, x1, y1, x2, y2, x3, y3],
分别表示左上、右上、右下、左下四点的坐标 |poly 坐标示意图|
示例数据
^^^^^^^^
.. code:: json
[
{
"layout_dets": [
{
"category_id": 2,
"poly": [
99.1906967163086,
100.3119125366211,
730.3707885742188,
100.3119125366211,
730.3707885742188,
245.81326293945312,
99.1906967163086,
245.81326293945312
],
"score": 0.9999997615814209
}
],
"page_info": {
"page_no": 0,
"height": 2339,
"width": 1654
}
},
{
"layout_dets": [
{
"category_id": 5,
"poly": [
99.13092803955078,
2210.680419921875,
497.3183898925781,
2210.680419921875,
497.3183898925781,
2264.78076171875,
99.13092803955078,
2264.78076171875
],
"score": 0.9999997019767761
}
],
"page_info": {
"page_no": 1,
"height": 2339,
"width": 1654
}
}
]
some_pdf_middle.json
~~~~~~~~~~~~~~~~~~~~
+-----------+----------------------------------------------------------+
| 字段名 | 解释 |
+===========+==========================================================+
| pdf_info | list，每个 |
| | 元素都是一个dict,这个dict是每一页pdf的解析结果，详见下表 |
+-----------+----------------------------------------------------------+
| \_p | ocr \| txt，用来标识本次解析的中间态使用的模式 |
| arse_type | |
+-----------+----------------------------------------------------------+
| \_ver | string, 表示本次解析使用的 magic-pdf 的版本号 |
| sion_name | |
+-----------+----------------------------------------------------------+
**pdf_info** 字段结构说明
+--------------+-------------------------------------------------------+
| 字段名 | 解释 |
+==============+=======================================================+
| pr | pdf预处理后，未分段的中间结果 |
| eproc_blocks | |
+--------------+-------------------------------------------------------+
| l | 布局分割的结果， |
| ayout_bboxes | 含有布局的方向（垂直、水平），和bbox，按阅读顺序排序 |
+--------------+-------------------------------------------------------+
| page_idx | 页码，从0开始 |
+--------------+-------------------------------------------------------+
| page_size | 页面的宽度和高度 |
+--------------+-------------------------------------------------------+
| \ | 布局树状结构 |
| _layout_tree | |
+--------------+-------------------------------------------------------+
| images | list，每个元素是一个dict，每个dict表示一个img_block |
+--------------+-------------------------------------------------------+
| tables | list，每个元素是一个dict，每个dict表示一个table_block |
+--------------+-------------------------------------------------------+
| interli | list，每个元素 |
| ne_equations | 是一个dict，每个dict表示一个interline_equation_block |
+--------------+-------------------------------------------------------+
| disc | List, 模型返回的需要drop的block信息 |
| arded_blocks | |
+--------------+-------------------------------------------------------+
| para_blocks | 将preproc_blocks进行分段之后的结果 |
+--------------+-------------------------------------------------------+
上表中 ``para_blocks``
是个dict的数组，每个dict是一个block结构，block最多支持一次嵌套
**block**
外层block被称为一级block，一级block中的字段包括
====== ===============================================
字段名 解释
====== ===============================================
type block类型（table|image）
bbox block矩形框坐标
blocks list，里面的每个元素都是一个dict格式的二级block
====== ===============================================
一级block只有”table”和”image”两种类型，其余block均为二级block
二级block中的字段包括
+-----+----------------------------------------------------------------+
| 字 | 解释 |
| 段 | |
| 名 | |
+=====+================================================================+
| t | block类型 |
| ype | |
+-----+----------------------------------------------------------------+
| b | block矩形框坐标 |
| box | |
+-----+----------------------------------------------------------------+
| li | list，每个元素都是一个dict表示的line，用来描述一行信息的构成 |
| nes | |
+-----+----------------------------------------------------------------+
二级block的类型详解
================== ==============
type desc
================== ==============
image_body 图像的本体
image_caption 图像的描述文本
image_footnote 图像的脚注
table_body 表格本体
table_caption 表格的描述文本
table_footnote 表格的脚注
text 文本块
title 标题块
index 目录块
list 列表块
interline_equation 行间公式块
================== ==============
**line**
line 的 字段格式如下
+----+-----------------------------------------------------------------+
| 字 | 解释 |
| 段 | |
| 名 | |
+====+=================================================================+
| bb | line的矩形框坐标 |
| ox | |
+----+-----------------------------------------------------------------+
| s | list， |
| pa | 每个元素都是一个dict表示的span，用来描述一个最小组成单元的构成 |
| ns | |
+----+-----------------------------------------------------------------+
**span**
+------------+---------------------------------------------------------+
| 字段名 | 解释 |
+============+=========================================================+
| bbox | span的矩形框坐标 |
+------------+---------------------------------------------------------+
| type | span的类型 |
+------------+---------------------------------------------------------+
| content \| | 文本类型的span使用content，图表类使用img_path |
| img_path | 用来存储实际的文本或者截图路径信息 |
+------------+---------------------------------------------------------+
span 的类型有如下几种
================== ========
type desc
================== ========
image 图片
table 表格
text 文本
inline_equation 行内公式
interline_equation 行间公式
================== ========
**总结**
span是所有元素的最小存储单元
para_blocks内存储的元素为区块信息
区块结构为
一级block(如有)->二级block->line->span
.. _示例数据-1:
示例数据
^^^^^^^^
.. code:: json
{
"pdf_info": [
{
"preproc_blocks": [
{
"type": "text",
"bbox": [
52,
61.956024169921875,
294,
82.99800872802734
],
"lines": [
{
"bbox": [
52,
61.956024169921875,
294,
72.0000228881836
],
"spans": [
{
"bbox": [
54.0,
61.956024169921875,
296.2261657714844,
72.0000228881836
],
"content": "dependent on the service headway and the reliability of the departure ",
"type": "text",
"score": 1.0
}
]
}
]
}
],
"layout_bboxes": [
{
"layout_bbox": [
52,
61,
294,
731
],
"layout_label": "V",
"sub_layout": []
}
],
"page_idx": 0,
"page_size": [
612.0,
792.0
],
"_layout_tree": [],
"images": [],
"tables": [],
"interline_equations": [],
"discarded_blocks": [],
"para_blocks": [
{
"type": "text",
"bbox": [
52,
61.956024169921875,
294,
82.99800872802734
],
"lines": [
{
"bbox": [
52,
61.956024169921875,
294,
72.0000228881836
],
"spans": [
{
"bbox": [
54.0,
61.956024169921875,
296.2261657714844,
72.0000228881836
],
"content": "dependent on the service headway and the reliability of the departure ",
"type": "text",
"score": 1.0
}
]
}
]
}
]
}
],
"_parse_type": "txt",
"_version_name": "0.6.1"
}
.. |poly 坐标示意图| image:: ../../_static/image/poly.png
next_docs/en/additional_notes/changelog.rst deleted 100644 → 0
View file @ 5f794533
Changelog
=========
- 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>`__.
- 2024/09/09: Version 0.8.0 released, supporting fast deployment with
Dockerfile, and launching demos on Huggingface and Modelscope.
- 2024/08/30: Version 0.7.1 released, add paddle tablemaster table
recognition option
- 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
.. warning::
fix ``localized deployment version`` and ``front-end interface``
next_docs/en/additional_notes/known_issues.rst deleted 100644 → 0
View file @ 5f794533
Known Issues
============
- Reading order is based on the model’s sorting of text distribution in
space, which may become disordered under extremely complex layouts.
- Vertical text is not supported.
- Tables of contents and lists are recognized through rules; a few
uncommon list formats may not be identified.
- Only one level of headings is supported; hierarchical heading levels
are currently not supported.
- Code blocks are not yet supported in the layout model.
- Comic books, art books, elementary school textbooks, and exercise
books are not well-parsed yet
- Enabling OCR may produce better results in PDFs with a high density
of formulas
- If you are processing PDFs with a large number of formulas, it is
strongly recommended to enable the OCR function. When using PyMuPDF
to extract text, overlapping text lines can occur, leading to
inaccurate formula insertion positions.
next_docs/en/projects.rst deleted 100644 → 0
View file @ 5f794533
llama_index_rag
===============
gradio_app
============
other projects
===============
\ No newline at end of file
next_docs/en/user_guide/quick_start/extract_text.rst deleted 100644 → 0
View file @ 5f794533
Extract Content from Pdf
========================
.. code:: python
from magic_pdf.data.read_api import read_local_pdfs
from magic_pdf.pdf_parse_union_core_v2 import pdf_parse_union
from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment