Merge pull request #969 from opendatalab/release-0.9.3

Release 0.9.3

Merge pull request #969 from opendatalab/release-0.9.3
Release 0.9.3
845a3ff0 · Xiaomeng Zhao · GitHub · d0558abb · 6083e109 · 845a3ff0
Unverified Commit 845a3ff0 authored Nov 15, 2024 by Xiaomeng Zhao Committed by GitHub Nov 15, 2024
20 changed files
--- a/next_docs/en/user_guide/data/read_api.rst
+++ b/next_docs/en/user_guide/data/read_api.rst
@@ -18,6 +18,8 @@ Read the contet from jsonl which may located on local machine or remote s3. if y
 .. code:: python
+    from magic_pdf.data.io.read_api import *
    # read jsonl from local machine 
    datasets = read_jsonl("tt.jsonl", None)
@@ -33,6 +35,8 @@ Read pdf from path or directory.
 .. code:: python
+    from magic_pdf.data.io.read_api import *
    # read pdf path
    datasets = read_local_pdfs("tt.pdf")
@@ -47,10 +51,11 @@ Read images from path or directory
 .. code:: python 
+    from magic_pdf.data.io.read_api import *
    # read from image path 
    datasets = read_local_images("tt.png")
    # read files from directory that endswith suffix in suffixes array 
    datasets = read_local_images("images/", suffixes=["png", "jpg"])

--- a/next_docs/en/user_guide/install/boost_with_cuda.rst
+++ b/next_docs/en/user_guide/install/boost_with_cuda.rst
@@ -9,16 +9,18 @@ appropriate guide based on your system:
 -  :ref:`ubuntu_22_04_lts_section`
 -  :ref:`windows_10_or_11_section`
+-  Quick Deployment with Docker
-  Quick Deployment with Docker > Docker requires a GPU with at least
+.. admonition:: Important
-   16GB of VRAM, and all acceleration features are enabled by default.
+   :class: tip
-.. note:: 
+   Docker requires a GPU with at least 16GB of VRAM, and all acceleration features are enabled by default.
-   Before running this Docker, you can use the following command to
+   Before running this Docker, you can use the following command to check if your device supports CUDA acceleration on Docker. 
-   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
+   .. code-block:: bash
+      bash  docker run --rm --gpus=all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi
 .. code:: sh
@@ -42,8 +44,9 @@ Ubuntu 22.04 LTS
 If you see information similar to the following, it means that the
 NVIDIA drivers are already installed, and you can skip Step 2.
-Notice:``CUDA Version`` should be >= 12.1, If the displayed version
+.. note::
-number is less than 12.1, please upgrade the driver.
+   ``CUDA Version`` should be >= 12.1, If the displayed version number is less than 12.1, please upgrade the driver.
 .. code:: text
@@ -105,8 +108,10 @@ Specify Python version 3.10.
   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
-❗ After installation, make sure to check the version of ``magic-pdf``
+.. admonition:: Important
-using the following command:
+    :class: tip
+    ❗ After installation, make sure to check the version of ``magic-pdf`` using the following command:
 .. code:: sh
@@ -127,7 +132,10 @@ 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.
-   The user directory for Linux is “/home/username”.
+.. admonition:: TIP
+    :class: tip
+    The user directory for Linux is “/home/username”.
 8. First Run
 ~~~~~~~~~~~~
@@ -137,7 +145,7 @@ Download a sample file from the repository and test it.
 .. code:: sh
   wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
-   magic-pdf -p small_ocr.pdf
+   magic-pdf -p small_ocr.pdf -o ./output
 9. Test CUDA Acceleration
 ~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -145,10 +153,6 @@ Download a sample file from the repository and test it.
 If your graphics card has at least **8GB** of VRAM, follow these steps
 to test CUDA acceleration:
-   ❗ Due to the extremely limited nature of 8GB VRAM for running this
-   application, you need to close all other programs using VRAM to
-   ensure that 8GB of VRAM is available when running this application.
 1. Modify the value of ``"device-mode"`` in the ``magic-pdf.json``
   configuration file located in your home directory.
@@ -162,7 +166,7 @@ to test CUDA acceleration:
   .. code:: sh
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
 10. Enable CUDA Acceleration for OCR
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -178,7 +182,9 @@ to test CUDA acceleration:
   .. code:: sh
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
 .. _windows_10_or_11_section:
@@ -218,16 +224,16 @@ Python version must be 3.10.
   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
-..
+.. admonition:: Important
+    :class: tip
-   ❗️After installation, verify the version of ``magic-pdf``:
+    ❗️After installation, verify the version of ``magic-pdf``:
-   .. code:: bash
+    .. code:: bash
      magic-pdf --version
-   If the version number is less than 0.7.0, please report it in the
+    If the version number is less than 0.7.0, please report it in the issues section.
-   issues section.
 5. Download Models
 ~~~~~~~~~~~~~~~~~~
@@ -242,7 +248,10 @@ 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】 .
-   The user directory for Windows is “C:/Users/username”.
+.. admonition:: Tip
+    :class: tip
+    The user directory for Windows is “C:/Users/username”.
 7. First Run
 ~~~~~~~~~~~~
@@ -252,7 +261,7 @@ Download a sample file from the repository and test it.
 .. code:: powershell
     wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
-     magic-pdf -p small_ocr.pdf
+     magic-pdf -p small_ocr.pdf -o ./output
 8. Test CUDA Acceleration
 ~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -260,27 +269,23 @@ Download a sample file from the repository and test it.
 If your graphics card has at least 8GB of VRAM, follow these steps to
 test CUDA-accelerated parsing performance.
-   ❗ Due to the extremely limited nature of 8GB VRAM for running this
+1. **Overwrite the installation of torch and torchvision** supporting CUDA.
-   application, you need to close all other programs using VRAM to
-   ensure that 8GB of VRAM is available when running this application.
-1. **Overwrite the installation of torch and torchvision** supporting
-   CUDA.
-   ::
+.. code:: sh
-      pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
+   pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
-   ..
+.. admonition:: Important
+    :class: tip
-      ❗️Ensure the following versions are specified in the command:
+    ❗️Ensure the following versions are specified in the command:
-      ::
+    .. code:: sh
         torch==2.3.1 torchvision==0.18.1
-      These are the highest versions we support. Installing higher
+    These are the highest versions we support. Installing higher versions without specifying them will cause the program to fail.
-      versions without specifying them will cause the program to fail.
 2. **Modify the value of ``"device-mode"``** in the ``magic-pdf.json``
   configuration file located in your user directory.
@@ -295,7 +300,7 @@ test CUDA-accelerated parsing performance.
   ::
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
 9. Enable CUDA Acceleration for OCR
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -311,5 +316,4 @@ test CUDA-accelerated parsing performance.
   ::
-      magic-pdf -p small_ocr.pdf
+      magic-pdf -p small_ocr.pdf -o ./output
--- a/next_docs/en/user_guide/install/install.rst
+++ b/next_docs/en/user_guide/install/install.rst
 Install 
 ===============================================================
-If you encounter any installation issues, please first consult the FAQ.
+If you encounter any installation issues, please first consult the :doc:`../../additional_notes/faq`.
-If the parsing results are not as expected, refer to the Known Issues.
+If the parsing results are not as expected, refer to the :doc:`../../additional_notes/known_issues`.
-There are three different ways to experience MinerU
-Pre-installation Notice—Hardware and Software Environment Support
+.. admonition:: Warning
------------------------------------------------------------------
+    :class: tip
-To ensure the stability and reliability of the project, we only optimize
+    **Pre-installation Notice—Hardware and Software Environment Support**
-and test for specific hardware and software environments during
-development. This ensures that users deploying and running the project
+    To ensure the stability and reliability of the project, we only optimize
-on recommended system configurations will get the best performance with
+    and test for specific hardware and software environments during
-the fewest compatibility issues.
+    development. This ensures that users deploying and running the project
+    on recommended system configurations will get the best performance with
-By focusing resources on the mainline environment, our team can more
+    the fewest compatibility issues.
-efficiently resolve potential bugs and develop new features.
+    By focusing resources on the mainline environment, our team can more
-In non-mainline environments, due to the diversity of hardware and
+    efficiently resolve potential bugs and develop new features.
-software configurations, as well as third-party dependency compatibility
-issues, we cannot guarantee 100% project availability. Therefore, for
+    In non-mainline environments, due to the diversity of hardware and
-users who wish to use this project in non-recommended environments, we
+    software configurations, as well as third-party dependency compatibility
-suggest carefully reading the documentation and FAQ first. Most issues
+    issues, we cannot guarantee 100% project availability. Therefore, for
-already have corresponding solutions in the FAQ. We also encourage
+    users who wish to use this project in non-recommended environments, we
-community feedback to help us gradually expand support.
+    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.
 .. raw:: html
-   <style>
+    <style>
-      table, th, td {
+        table, th, td {
-      border: 1px solid black;
+        border: 1px solid black;
-      border-collapse: collapse;
+        border-collapse: collapse;
-      }
+        }
-   </style>
+    </style>
-   <table>
+    <table>
-    <tr>
+        <tr>
-        <td colspan="3" rowspan="2">Operating System</td>
+            <td colspan="3" rowspan="2">Operating System</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td>Ubuntu 22.04 LTS</td>
+            <td>Ubuntu 22.04 LTS</td>
-        <td>Windows 10 / 11</td>
+            <td>Windows 10 / 11</td>
-        <td>macOS 11+</td>
+            <td>macOS 11+</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="3">CPU</td>
+            <td colspan="3">CPU</td>
-        <td>x86_64</td>
+            <td>x86_64(unsupported ARM Linux)</td>
-        <td>x86_64</td>
+            <td>x86_64(unsupported ARM Windows)</td>
-        <td>x86_64 / arm64</td>
+            <td>x86_64 / arm64</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="3">Memory</td>
+            <td colspan="3">Memory</td>
-        <td colspan="3">16GB or more, recommended 32GB+</td>
+            <td colspan="3">16GB or more, recommended 32GB+</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="3">Python Version</td>
+            <td colspan="3">Python Version</td>
-        <td colspan="3">3.10</td>
+            <td colspan="3">3.10(Please make sure to create a Python 3.10 virtual environment using conda)</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="3">Nvidia Driver Version</td>
+            <td colspan="3">Nvidia Driver Version</td>
-        <td>latest (Proprietary Driver)</td>
+            <td>latest (Proprietary Driver)</td>
-        <td>latest</td>
+            <td>latest</td>
-        <td>None</td>
+            <td>None</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="3">CUDA Environment</td>
+            <td colspan="3">CUDA Environment</td>
-        <td>Automatic installation [12.1 (pytorch) + 11.8 (paddle)]</td>
+            <td>Automatic installation [12.1 (pytorch) + 11.8 (paddle)]</td>
-        <td>11.8 (manual installation) + cuDNN v8.7.0 (manual installation)</td>
+            <td>11.8 (manual installation) + cuDNN v8.7.0 (manual installation)</td>
-        <td>None</td>
+            <td>None</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td rowspan="2">GPU Hardware Support List</td>
+            <td rowspan="2">GPU Hardware Support List</td>
-        <td colspan="2">Minimum Requirement 8G+ VRAM</td>
+            <td colspan="2">Minimum Requirement 8G+ VRAM</td>
-        <td colspan="2">3060ti/3070/3080/3080ti/4060/4070/4070ti<br>
+            <td colspan="2">3060ti/3070/4060<br>
-        8G VRAM enables layout, formula recognition acceleration and OCR acceleration</td>
+            8G VRAM enables layout, formula recognition acceleration and OCR acceleration</td>
-        <td rowspan="2">None</td>
+            <td rowspan="2">None</td>
-    </tr>
+        </tr>
-    <tr>
+        <tr>
-        <td colspan="2">Recommended Configuration 16G+ VRAM</td>
+            <td colspan="2">Recommended Configuration 10G+ VRAM</td>
-        <td colspan="2">3090/3090ti/4070ti super/4080/4090<br>
+            <td colspan="2">3080/3080ti/3090/3090ti/4070/4070ti/4070tisuper/4080/4090<br>
-        16G VRAM or more can enable layout, formula recognition, OCR acceleration and table recognition acceleration simultaneously
+            10G VRAM or more can enable layout, formula recognition, OCR acceleration and table recognition acceleration simultaneously
-        </td>
+            </td>
-    </tr>
+        </tr>
-   </table>
+    </table>
 Create an environment

--- a/next_docs/en/user_guide/quick_start/command_line.rst
+++ b/next_docs/en/user_guide/quick_start/command_line.rst
@@ -55,5 +55,8 @@ directory. The output file list is as follows:
   ├── some_pdf_spans.pdf                   # smallest granularity bbox position information diagram
   └── some_pdf_content_list.json           # Rich text JSON arranged in reading order
-For more information about the output files, please refer to the :doc:`../tutorial/output_file_description`
+.. admonition:: Tip
+   :class: tip
+   For more information about the output files, please refer to the :doc:`../tutorial/output_file_description`
--- a/next_docs/en/user_guide/quick_start/extract_text.rst
+++ b/next_docs/en/user_guide/quick_start/extract_text.rst
-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
--- a/next_docs/zh_cn/_static/image/MinerU-logo-hq.png
+++ b/next_docs/zh_cn/_static/image/MinerU-logo-hq.png
--- a/next_docs/zh_cn/_static/image/MinerU-logo.png
+++ b/next_docs/zh_cn/_static/image/MinerU-logo.png
--- a/next_docs/zh_cn/_static/image/ReadTheDocs.svg
+++ b/next_docs/zh_cn/_static/image/ReadTheDocs.svg
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--- a/next_docs/zh_cn/_static/image/datalab_logo.png
+++ b/next_docs/zh_cn/_static/image/datalab_logo.png
--- a/next_docs/zh_cn/_static/image/flowchart_en.png
+++ b/next_docs/zh_cn/_static/image/flowchart_en.png
--- a/next_docs/zh_cn/_static/image/flowchart_zh_cn.png
+++ b/next_docs/zh_cn/_static/image/flowchart_zh_cn.png
--- a/next_docs/zh_cn/_static/image/layout_example.png
+++ b/next_docs/zh_cn/_static/image/layout_example.png
--- a/next_docs/zh_cn/_static/image/poly.png
+++ b/next_docs/zh_cn/_static/image/poly.png
--- a/next_docs/zh_cn/_static/image/project_panorama_en.png
+++ b/next_docs/zh_cn/_static/image/project_panorama_en.png
--- a/next_docs/zh_cn/_static/image/project_panorama_zh_cn.png
+++ b/next_docs/zh_cn/_static/image/project_panorama_zh_cn.png
--- a/next_docs/zh_cn/_static/image/spans_example.png
+++ b/next_docs/zh_cn/_static/image/spans_example.png
--- a/next_docs/zh_cn/_static/image/web_demo_1.png
+++ b/next_docs/zh_cn/_static/image/web_demo_1.png
--- a/next_docs/zh_cn/additional_notes/faq.rst
+++ b/next_docs/zh_cn/additional_notes/faq.rst
+常见问题解答
+============
+1.在较新版本的mac上使用命令安装pip install magic-pdf[full] zsh: no matches found: magic-pdf[full]
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+在 macOS 上，默认的 shell 从 Bash 切换到了 Z shell，而 Z shell 对于某些类型的字符串匹配有特殊的处理逻辑，这可能导致no matches found错误。 可以通过在命令行禁用globbing特性，再尝试运行安装命令
+.. code:: bash
+   setopt no_nomatch
+   pip install magic-pdf[full]
+2.使用过程中遇到_pickle.UnpicklingError: invalid load key, ‘v’.错误
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+可能是由于模型文件未下载完整导致，可尝试重新下载模型文件后再试。参考：https://github.com/opendatalab/MinerU/issues/143
+3.模型文件应该下载到哪里/models-dir的配置应该怎么填
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+模型文件的路径输入是在”magic-pdf.json”中通过
+.. code:: json
+   {
+     "models-dir": "/tmp/models"
+   }
+进行配置的。这个路径是绝对路径而不是相对路径，绝对路径的获取可在models目录中通过命令 “pwd” 获取。
+参考：https://github.com/opendatalab/MinerU/issues/155#issuecomment-2230216874
+4.在WSL2的Ubuntu22.04中遇到报错\ ``ImportError: libGL.so.1: cannot open shared object file: No such file or directory``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+WSL2的Ubuntu22.04中缺少\ ``libgl``\ 库，可通过以下命令安装\ ``libgl``\ 库解决：
+.. code:: bash
+   sudo apt-get install libgl1-mesa-glx
+参考：https://github.com/opendatalab/MinerU/issues/388
+5.遇到报错 ``ModuleNotFoundError : Nomodulenamed 'fairscale'``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+需要卸载该模块并重新安装
+.. code:: bash
+   pip uninstall fairscale
+   pip install fairscale
+参考：https://github.com/opendatalab/MinerU/issues/411
+6.在部分较新的设备如H100上，使用CUDA加速OCR时解析出的文字乱码。
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+cuda11对新显卡的兼容性不好，需要升级paddle使用的cuda版本
+.. code:: bash
+   pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu123/
+参考：https://github.com/opendatalab/MinerU/issues/558
+7.在部分Linux服务器上，程序一运行就报错 ``非法指令 (核心已转储)`` 或 ``Illegal instruction (core dumped)``
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+可能是因为服务器CPU不支持AVX/AVX2指令集，或cpu本身支持但被运维禁用了，可以尝试联系运维解除限制或更换服务器。
+参考：https://github.com/opendatalab/MinerU/issues/591 ，https://github.com/opendatalab/MinerU/issues/736
--- a/next_docs/zh_cn/additional_notes/glossary.rst
+++ b/next_docs/zh_cn/additional_notes/glossary.rst
+名词解释
+===========
+1. jsonl 
+    TODO: add description
+2. magic-pdf.json
+    TODO: add description
--- a/next_docs/zh_cn/additional_notes/known_issues.rst
+++ b/next_docs/zh_cn/additional_notes/known_issues.rst
+已知问题
+============
+-  阅读顺序基于模型对可阅读内容在空间中的分布进行排序，在极端复杂的排版下可能会部分区域乱序
+-  不支持竖排文字
+-  目录和列表通过规则进行识别，少部分不常见的列表形式可能无法识别
+-  标题只有一级，目前不支持标题分级
+-  代码块在layout模型里还没有支持
+-  漫画书、艺术图册、小学教材、习题尚不能很好解析
+-  表格识别在复杂表格上可能会出现行/列识别错误
+-  在小语种PDF上，OCR识别可能会出现字符不准确的情况（如拉丁文的重音符号、阿拉伯文易混淆字符等）
+-  部分公式可能会无法在markdown中渲染