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* # 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

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

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.

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.