# Table Transformer Library

Original repository: https://github.com/microsoft/table-transformer

## Introduction
This is the Table Transformer Model developed by Brandon Smock et al. of Microsoft AI. This repository consists of **Table Structure Recognition (TATR)** for detecting and extracting table infomation into popular formats such as CSV or HTML table, plus text recognition using EasyOCR.

## Installation
```
pip install table-transformer
```

## Usage

The full model usage can be found here:

```
from table_transformer import TableExtractionPipeline

pipe = TableExtractionPipeline(det_device="cpu", str_device="cpu",
                 det_model_path=".\path\to\pubtables1m_detection_detr_r18.pth",
                 str_model_path=".\path\to\TATR-v1.1-Pub-msft.pth")

img = "\path\to\image.jpg"

table_objects, table_cells_coordinates, table_cells_text = pipe(img)

print(table_cells_text[0])  # Should be DataFrame
```


## Evaluation

With structure recognition, the original author has evaluated the v1.0 model on PubTables-1M with great results. With other datasets such as PubTabNet, the score is quite good.

You can check out the score and run the evaluation with your own dataset in [this](https://colab.research.google.com/drive/1-1yRr9djVi5OxITrSf3iZsg__MNE5hN5?usp=sharing) link.

## Version history
- v1.0.6: Added Table Detection, ending up with a full Table Extraction Pipeline, fixed bug.
- v1.0.3: Removed unnecessary code and added new functionalities.
- v1.0.2: Initial version.


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table-transformer

Table Transformer Library

Introduction

Installation

Usage

Evaluation

Version history

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