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* TLDR-589_expand_table_data_improve_table_comparition (#409)

* TLDR-608 update benchmark (#411)

* TLDR-599 re-label datasets (#412)

* TLDR-616 add parsing parameters saving to tasker, fix bugs

* TXT images creator fixed

* Fix tasker for diplomas

* Fix tests, speed up txt_images_creator

* TLDR-619 fixed html table parsing (#413)

* fixed html table parsing

* fixed code according to PR comments

* optimized imports

---------

Co-authored-by: Alexander Golodkov <[email protected]>

* TLDR-615 update README.md (#414)

* TLDR-615 update README.md

* Update README.md

* update web_interface.png

* TLDR-615 added structure examples

* TLDR-615 added structure examples png

* new version 2.1.1 (#416)

---------

Co-authored-by: Bogatenkova Anastasiya <[email protected]>
Co-authored-by: Alexander Golodkov <[email protected]>
Co-authored-by: Alexander Golodkov <[email protected]>
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2 changes: 1 addition & 1 deletion .github/workflows/test_labeling.yaml
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name: CI
name: CI labeling

# Controls when the action will run.
on:
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148 changes: 41 additions & 107 deletions README.md
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Expand Up @@ -36,6 +36,31 @@ In 2022, the system won a grant to support the development of promising AI proje
* Using Tesseract, an actively developed OCR engine from Google, together with image preprocessing methods.
* Utilizing modern machine learning approaches for detecting a document orientation, detecting single/multicolumn document page, detecting bold text and extracting hierarchical structure based on the classification of features extracted from document images.

## Document format description
The system processes different document formats. The main formats are listed below:

| Format group | Description |
|-----------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Office formats | DOCX, XLSX, PPTX and formats that canbe converted to them. Handling of these for-mats is held by analysis of format inner rep-resentation and using specialized libraries ([python-docx](https://python-docx.readthedocs.io/en/latest/), [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/)) |
| HTML, EML, MHTML | HTML documents are parsed using tagsanalysis, HTML handler is used for han-dling documents of other formats in thisgroup |
| TXT | Only raw textual content is analyzed |
| Archives | Attachments of the archive are analyzed | |
| PDF,document images | Copyable PDF documents (with a textual layer) can be handled using [pdfminer-six](https://pdfminersix.readthedocs.io/en/latest/) library or [tabby](https://github.com/sunveil/ispras_tbl_extr) software. Non-copyable PDF documents or imagesare handled using [Tesseract-OCR](https://github.com/tesseract-ocr/tesseract), machine learning methods (including neural network methods) and [image processing methods](https://opencv.org/) |

## Examples of processed scanned documents
* Dedoc can only process scanned black and white documents, such as technical specifications, regulations, articles, etc.
<img src="docs/source/_static/doc_examples.png" alt="Document examples" style="width:800px;"/>
<!--![Document examples](docs/source/_static/doc_examples.png){:height="150px"}-->
* In particular, dedoc recognizes tabular information only from tables with explicit boundaries. Here are examples of documents that can be processed by an dedoc's image handler:
<img src="docs/source/_static/example_table.jpg" alt="Table parsing example" style="width:600px;"/>
<!--![Table Example](docs/source/_static/example_table.jpg)-->
* The system also automatically detects and corrects the orientation of scanned documents

## Example of structure extractor
<img src="docs/source/_static/str_ext_example_law.png" alt="Law structure example"/>
<img src="docs/source/_static/str_ext_example_tz.png" alt="Tz structure example"/>


## Impact
This project may be useful as a first step of automatic document analysis pipeline (e.g. before the NLP part).
Dedoc is in demand for information analytic systems, information leak monitoring systems, as well as for natural language processing systems.
Expand All @@ -44,6 +69,20 @@ The library is intended for application use by developers of systems for automat
# Online-Documentation
Relevant documentation of the dedoc is available [here](https://dedoc.readthedocs.io/en/latest/)

# Demo
You can try dedoc's demo: https://dedoc-readme.hf.space.

We have a video to demonstrate how to use the system: https://www.youtube.com/watch?v=ZUnPYV8rd9A.

![Web_interface](docs/source/_static/web_interface.png)

![dedoc_demo](docs/source/_static/dedoc_short.gif)

# Some our publications

* Article on [Habr](https://habr.com/ru/companies/isp_ras/articles/779390/), where we describe our system in detail
* [Our article](https://aclanthology.org/2022.fnp-1.13.pdf) from the FINTOC 2022 competition. We are the winners :smiley: :trophy:!

# Installation instructions
****************************************
This project has REST Api and you can run it in Docker container.
Expand Down Expand Up @@ -105,113 +144,8 @@ If you don't want to use docker for running the application, it's possible to ru
However, it isn't suitable for any operating system (`Ubuntu 20+` is recommended) and
there may be not enough machine's resources for its work.
You should have `python` (`python3.8`, `python3.9` are recommended) and `pip` installed.

### 1. Install necessary packages:
```shell
sudo apt-get install -y libreoffice djvulibre-bin unzip unrar
```

`libreoffice` and `djvulibre-bin` packages are used by converters (doc, odt to docx; xls, ods to xlsx; ppt, odp to pptx; djvu to pdf).
If you don't need converters, you can skip this step.
`unzip` and `unrar` packages are used in the process of extracting archives.

### 2. Install `Tesseract OCR 5` framework:
You can try any tutorial for this purpose or look [`here`](https://github.com/ispras/dedockerfiles/blob/master/dedoc_p3.9_base.Dockerfile)
to get the example of Tesseract installing for dedoc container or use next commands for building Tesseract OCR 5 from sources:

#### 2.1. Install compilers and libraries required by the Tesseract OCR:
```shell
sudo apt-get update
sudo apt-get install -y automake binutils-dev build-essential ca-certificates clang g++ g++-multilib gcc-multilib libcairo2 libffi-dev \
libgdk-pixbuf2.0-0 libglib2.0-dev libjpeg-dev libleptonica-dev libpango-1.0-0 libpango1.0-dev libpangocairo-1.0-0 libpng-dev libsm6 \
libtesseract-dev libtool libxext6 make pkg-config poppler-utils pstotext shared-mime-info software-properties-common swig zlib1g-dev
```
#### 2.2. Build Tesseract from sources:
```shell
sudo add-apt-repository -y ppa:alex-p/tesseract-ocr-devel
sudo apt-get update --allow-releaseinfo-change
sudo apt-get install -y tesseract-ocr tesseract-ocr-rus
git clone --depth 1 --branch 5.0.0-beta-20210916 https://github.com/tesseract-ocr/tesseract/
cd tesseract && ./autogen.sh && sudo ./configure && sudo make && sudo make install && sudo ldconfig && cd ..
export TESSDATA_PREFIX=/usr/share/tesseract-ocr/5/tessdata/
```

## Install the dedoc library via pip.

You need `torch~=1.11.0` and `torchvision~=0.12.0` installed. If you already have torch and torchvision in your environment:

```shell
pip install dedoc
```

Or you can install dedoc with torch and torchvision included:

```shell
pip install "dedoc[torch]"
```
Installation instructions via pip are available [here](https://dedoc.readthedocs.io/en/latest/getting_started/installation.html#install-dedoc-using-pip).

## Install and run dedoc from sources
You can also install and run dedoc locally from sources using [this](https://dedoc.readthedocs.io/en/latest/getting_started/installation.html#install-and-run-dedoc-from-sources) instruction.

If you want to run dedoc as a service from sources, it's possible to run dedoc locally.
However, it is suitable not for all operating systems (`Ubuntu 20+` is recommended) and
there may be not enough machine's resources for its work.
You should have `python` (`python3.8`, `python3.9` are recommended) and `pip` installed.

### 1. Install necessary packages: according to instructions [install necessary packages](#1-Install-necessary-packages)

### 2. Build Tesseract from sources according to instructions [Install Tesseract OCR-5 framework](#2-Install-Tesseract-OCR-5-framework)

### 3. We recommend to install python's virtual environment (for example, via `virtualenvwrapper`)

Below are the instructions for installing the package `virtualenvwrapper`:

```shell
sudo pip3 install virtualenv virtualenvwrapper
mkdir ~/.virtualenvs
export WORKON_HOME=~/.virtualenvs
echo "export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3.8" >> ~/.bashrc
echo ". /usr/local/bin/virtualenvwrapper.sh" >> ~/.bashrc
source ~/.bashrc
mkvirtualenv dedoc_env
```

### 4. Install python's requirements and launch dedoc service on default port `1231`:

```shell
# clone dedoc project
git clone https://github.com/ispras/dedoc.git
cd dedoc
# check on your's python environment
workon dedoc_env
export PYTHONPATH=$PYTHONPATH:$(pwd)
pip install -r requirements.txt
pip install torch=1.11.0 torchvision==0.12.0 -f https://download.pytorch.org/whl/torch_stable.html
python dedoc/main.py -c ./dedoc/config.py
```
Now you can go to the `localhost:1231` and look at the docs and examples.

## Option: You can change the port of service:
You need to change environment `DOCREADER_PORT`

1. For local service launching on `your_port` (e.g. `1166`). Install ([installation instruction](#Install-and-run-dedoc-from-sources)) and launch with environment:
```shell
DOCREADER_PORT=1166 python dedoc/main.py -c ./dedoc/config.py
```

2. For service launching in docker-container you need to change port value in `DOCREADER_PORT` env and field `ports` in `docker-compose.yml` file:
```yaml
...
dedoc:
...
ports:
- your_port_number:your_port_number
environment:
DOCREADER_PORT: your_port_number
...
test:
...
environment:
DOCREADER_PORT: your_port_number
```
Go [here](https://dedoc.readthedocs.io/en/latest/getting_started/installation.html) to get more details about dedoc installation.
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2.1
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