GitLab

- Note the fix in version 0.6.2b1 for the network error during the first run of offline  deployment and clarify the model download requirement.
- Update the dependency installation guide for users on macOS with Intel CPUs.
- Indicate the resolution in version 0.6.2b1 for compatibility issues with paddlepaddle
  version 2.6.1 on certain Linux systems.

This change aims to make the FAQ more informative and easier to navigate for users
experiencing similar issues, providing direct solutions and links where applicable.

Update the download links for Anaconda in both Ubuntu and Windows CUDA
Acceleration documents to use the Tuna mirror. This change helps ensure that
users in China have faster access to the Anaconda distribution.

Update the README documents to clarify that the "models-dir" in the
configuration should be an absolute path. Also, provide additional guidance
for Windows users on how to correctly format the path to avoid common issues
with path escaping in JSON files.

Add instructions to download the magic-pdf.template.json file using wget on
Ubuntu and a PowerShell script on Windows in the respective README files.
This is to facilitate the setup process by providing direct download options,
replacing manual file transfers.

Update the install commands in both Ubuntu and Windows CUDA Acceleration
guides to specify Magic-PDF version 0.6.2b1, ensuring consistency andavoiding potential version mismatches.

Update the FAQ to clarify the dependency installation issue when using magic-pdf. Ensure
users are directed to install the specific version of magic-pdf that resolves the dependency
error, rather than listing all individual dependencies. This simplifies the troubleshooting process
and provides a direct solution for users encountering the "Required dependency not installed"
error.

Update the download methods for models in the Chinese documentation to reflect
the latest options available from ModelScope. Simplify the section titles and
revise download instructions for clarity and consistency.

Update the documentation to reflect the latest model download procedures, emphasis on
model file integrity checks, and expanded instructions for setting up CUDA accelerationon Ubuntu and Windows environments. The README files for various OS have been
enhanced with additional details to assist users in configuring and verifying their
environments for optimal performance.

* # add table recognition using struct-eqtable
## Changelog
31/07/20204
- Support table recognition. Table images will be converted into html.

### how to use the new feature:
set the attribute 'table-mode' to 'true' in magic-pdf.json

### caution:
it takes 200s to 500s to convert a single table image using cpu

* # add table recognition using struct-eqtable
## Changelog
31/07/20204
- Support table recognition. Table images will be converted into LaTex.

### how to use the new feature:
set the attribute 'table-mode' to 'true' in magic-pdf.json

### caution:
it takes 200s to 500s to convert a single table image using cpu

* # feat(model inference): add table recognition and convertion to LaTeX

# What's Changed

### New Features

- Add table content recognition, we use weights of [StructEqTable](https://github.com/UniModal4Reasoning/StructEqTable-Deploy) to convert table image to LaTex.

### Instruction

- pip install pypandoc struct-eqtable==0.1.0
- Download [StructEqTable weights](https://huggingface.co/wanderkid/PDF-Extract-Kit/tree/main/models/TabRec

) and put it under models/ directory.
- Edit 'table-mode' value to turn on table recognition function which is turned off by default.
- If you did not download any models before, refer to [how to download models](docs/how_to_download_models_zh_cn.md)。

* add table recognition and convertion to LaTeX

* add table recognition and conversion to LaTeX

* add table recognition and conversion to LaTeX

* add table recognition and conversion to LaTeX

---------
Co-authored-by: liukaiwen <liukaiwen@pjlab.org.cn>

- Fix the description of the 'poly' coordinate format in the output file documentation to correctly reflect the order of coordinates: left-top, right-top, right-bottom,
  left-bottom.
- Update various table-related descriptions for clarity and consistency, including
  field names and their corresponding explanations.
- Add version name field description in 'middle.json' structure to document the
  version of the magic-pdf used in the parsing process.
- Refactor the block and line description tables to improve readability and alignment
  with the rest of the documentation.

- Adjust command installation format for PaddlePaddle GPU.
- Clarify instruction numbering for testing OCR acceleration.

Update the Ubuntu CUDA Acceleration setup guide to reflect the correct user directory
path and improve the clarity of instructions. Remove references to Windows and macOS
as they are out of scope for this document. Ensure the configuration file copying
command is correctly represented for Linux users.

Update the link to the magic-pdf.template.json configuration template file in the
README_Ubuntu_CUDA_Acceleration_zh_CN.md document. The file path was previously
incorrect and has been amended to point to the correct location.

Update the instruction in README_Ubuntu_CUDA_Acceleration_zh_CN.md to reference
the correct section number for downloading the model weights. This change ensures
that users are directed to the correct location in the document for setting up the
model directory in the magic-pdf.json configuration.

docs: update Ubuntu CUDA acceleration guide for version 0.6.2- Add steps for Ubuntu 22.04 LTS installation.
- Detail the process of checking, installing, and configuring NVIDIA drivers.
- Include instructions for installing Anaconda and creating a specific environment.
- Provide guidance on installing magic-pdf and its dependencies.
- Add a note to verify magic-pdf version and report issues if necessary.
- Describe the process of downloading models and configuring the application.
- Include a sample command to run the application with CUDA acceleration.
- Add a note for enabling OCR CUDA acceleration with specific GPU requirements.

This update ensures users have the latest information for setting up CUDA accelerationwith magic-pdf on Ubuntu 22.04 LTS, specifically for version 0.6.2, and provides clearer
instructions on the installation and configuration process.

Restructured the how-to download models document for better clarity and
added sections on downloading models from ModelScope, including SDK and
Git download methods. Provided detailed steps for installing Git LFS and
checking model integrity after download. Also included recommendations
for moving the models to an SSD for better performance.

* feat: refractor cli command

* feat: add docs to describe the output files of cli

* feat: resove review comments

* feat: updat docs about middle.json

---------
Co-authored-by: shenguanlin <shenguanlin@pjlab.org.cn>

# What's Changed

### New Features

- Add table content recognition, we use weights of [StructEqTable](https://github.com/UniModal4Reasoning/StructEqTable-Deploy) to convert table image to LaTex.

### Instruction

- pip install pypandoc struct-eqtable==0.1.0
- Download [StructEqTable weights](https://huggingface.co/wanderkid/PDF-Extract-Kit/tree/main/models/TabRec) and put it under models/ directory.
- Edit 'table-mode' value to turn on table recognition function which is turned off by default.
- If you did not download any models before, refer to [how to download models](docs/how_to_download_models_zh_cn.md)。

Add detailed instructions for installing git lfs on Linux, macOS, and Windows
to facilitate users in downloading models from ModelScope repository. The guide
is included in the `how_to_download_models_zh_cn.md` document.

use git lfs clone to download model from ModelScope

Add new configuration options for custom model directories and device modeselection. This allows users to specify the directory where models are stored
and choose between CPU and GPU modes for model inference. The configurations
are read from a JSON file and can be easily extended to support additional
options in the future.