update master

.github/workflows/release.yaml

@@ -41,7 +41,7 @@ jobs:
       - name: Push to dockerhub
         if: ${{ success() }}
         run: |
-          docker build -f docker/Dockerfile -t dedocproject/dedoc:$GITHUB_REF_NAME .
+          docker build -f Dockerfile -t dedocproject/dedoc:$GITHUB_REF_NAME .
           docker login -u ${{ secrets.DOCKERHUB_USERNAME }} -p ${{ secrets.DOCKERHUB_PASSWORD }}
           docker tag dedocproject/dedoc:$GITHUB_REF_NAME dedocproject/dedoc:latest
           docker push dedocproject/dedoc:$GITHUB_REF_NAME

README.md

@@ -4,10 +4,15 @@
 
 ![Dedoc](https://github.com/ispras/dedoc/raw/master/dedoc_logo.png)
 
-Dedoc is an open universal system for converting documents to a unified output format. It extracts a document’s logical structure and content, its tables, text formatting and metadata. The document’s content is represented as a tree storing headings and lists of any level. Dedoc can be integrated in a document contents and structure analysis system as a separate module.
+Dedoc is an open universal system for converting documents to a unified output format. 
+It extracts a document’s logical structure and content, its tables, text formatting and metadata. 
+The document’s content is represented as a tree storing headings and lists of any level. 
+Dedoc can be integrated in a document contents and structure analysis system as a separate module.
 
 ## Features and advantages
-Dedoc is implemented in Python and works with semi-structured data formats (DOC/DOCX, ODT, XLS/XLSX, CSV, TXT, JSON) and none-structured data formats like images (PNG, JPG etc.), archives (ZIP, RAR etc.), PDF and HTML formats. Document structure extraction is fully automatic regardless of input data type. Metadata and text formatting is also extracted automatically. 
+Dedoc is implemented in Python and works with semi-structured data formats (DOC/DOCX, ODT, XLS/XLSX, CSV, TXT, JSON) and none-structured data formats like images (PNG, JPG etc.), archives (ZIP, RAR etc.), PDF and HTML formats. 
+Document structure extraction is fully automatic regardless of input data type. 
+Metadata and text formatting are also extracted automatically. 
 
 In 2022, the system won a grant to support the development of promising AI projects from the [Innovation Assistance Foundation (Фонд содействия инновациям)](https://fasie.ru/).
 
@@ -16,45 +21,189 @@ In 2022, the system won a grant to support the development of promising AI proje
 * Support for extracting document structure out of nested documents having different formats. 
 * Extracting various text formatting features (indentation, font type, size, style etc.). 
 * Working with documents of various origin (statements of work, legal documents, technical reports, scientific papers) allowing flexible tuning for new domains. 
-* Working with PDF documents containinng a text layer:
-  * Support to automatically determine the correctness of the text layer in PDF documents; 
-  * Extract containing and formatting from PDF-documents with a text layer using the developed interpreter of the virtual stack machine for printing graphics according to the format specification. 
-Extracting table data from DOC/DOCX, PDF, HTML, CSV and image formats:
+* Working with PDF documents containing a textual layer:
+  * Support to automatically determine the correctness of the textual layer in PDF documents; 
+  * Extract containing and formatting from PDF-documents with a textual layer using the developed interpreter of the virtual stack machine for printing graphics according to the format specification. 
+* Extracting table data from DOC/DOCX, PDF, HTML, CSV and image formats:
   * Recognizing a physical structure and a cell text for complex multipage tables having explicit borders with the help of contour analysis. 
 * Working with scanned documents (image formats and PDF without text layer):
   * 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.
 
+## 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.
+The library is intended for application use by developers of systems for automatic analysis and structuring of electronic documents, including for further search in electronic documents. 
 
-This project may be useful as a first step of automatic document analysis pipeline (e.g. before the NLP part)
+# Online-Documentation
+Relevant documentation of the dedoc is available [here](https://dedoc.readthedocs.io/en/latest/)
 
-This project has REST Api and you can run it in Docker container
-To read full Dedoc documentation run the project and go to localhost:1231.
-
+# Installation instructions
+****************************************
+This project has REST Api and you can run it in Docker container.
+Also, dedoc can be installed as a library via `pip`.
+There are two ways to install and run dedoc as a web application or a library that are described below.
 
-## Run the project
-How to build and run the project
 
-Ensure you have Git and Docker installed
-
-Clone the project 
+## Install and run dedoc using docker 
+
+You should have [`git`] (https://git-scm.com) and [`docker`](https://www.docker.com) installed for running dedoc by this method.
+This method is more flexible because it doesn't depend on the operating system and other user's limitations,
+still, the docker application should be installed and configured properly.
+
+If you don't need to change the application configuration, you may use the built docker image as well.
+
+### 1. Pull the image
 ```bash
-git clone https://github.com/ispras/dedoc.git
+docker pull dedocproject/dedoc
+```
 
-cd dedoc/
+### 2. Run the container
+```bash
+docker run -p 1231:1231 --rm dedocproject/dedoc python3 /dedoc_root/dedoc/main.py
 ```
-
-Ensure you have Docker installed.
-Start 'Dedoc' on the port 1231:
- ```bash
+
+Go to [dockerhub](https://hub.docker.com/r/dedocproject/dedoc) to get more information about available dedoc images.
+
+If you need to change some application settings, you may update `config.py` according to your needs and re-build the image. 
+You can build and run image:
+
+### 1. Clone the repository
+```bash
+git clone https://github.com/ispras/dedoc
+```
+
+### 2. Go to the `dedoc` directory
+```bash
+cd dedoc
+```
+
+### 3. Build the image and run the application
+```bash
 docker-compose up --build
 ```
 
-Start Dedoc with tests:
- ```bash
+### 4. Run container with tests
+```bash
 test="true" docker-compose up --build
- ```
+```
+
+If you need to change some application settings, you may update `config.py` according to your needs and re-build the image.
+
+
+## Install dedoc using pip
+
+If you don't want to use docker for running the application, it's possible to run dedoc locally.
+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:
+```bash
+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:
+```bash
+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:
+```bash
+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:
+
+```bash
+pip install dedoc
+```
+
+Or you can install dedoc with torch and torchvision included:
+
+```bash
+pip install "dedoc[torch]"
+```
+
+## Install and run dedoc from sources
+
+If you want to run dedoc as a service from sources. it's possible to run dedoc locally.
+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: 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`:
+
+```bash
+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`:
+
+```bash
+# 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 (1166 example). [Install instruction from sources](#Install-and-run-dedoc-from-sources) and launch with environment: 
+```bash
+DOCREADER_PORT=1166 python dedoc/main.py -c ./dedoc/config.py
+```
 
-Now you can go to the localhost:1231 and look at the docs and examples.
+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
+``` 
 
-You can change the port and host in the config file 'dedoc/config.py'
+Go [here](https://dedoc.readthedocs.io/en/latest/getting_started/installation.html) to get more details about dedoc installation.

VERSION

@@ -1 +1 @@
-0.11.1
+0.11.2

docs/source/changelog.rst

@@ -1,6 +1,17 @@
 Changelog
 =========
 
+v0.11.2 (2023-09-06)
+--------------------
+Release note: `v0.11.2 <https://github.com/ispras/dedoc/releases/tag/v0.11.2>`_
+
+* Remove plexus-utils-1.1.jar.
+* Update installation documentation.
+* Add documentation for Tesseract OCR installation.
+* Add documentation for annotations.
+* Add documentation for secure torch.
+* Fix examples.
+
 v0.11.1 (2023-08-30)
 --------------------
 Release note: `v0.11.1 <https://github.com/ispras/dedoc/releases/tag/v0.11.1>`_

docs/source/getting_started/installation.rst

@@ -59,27 +59,54 @@ Install dedoc using pip
 If you don't want to use docker for running the application, it's possible to run dedoc locally.
 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+ is recommended) and `pip` installed.
+You should have `python` (python3.8, python3.9 are recommended) and `pip` installed.
 
+.. _install_packages:
 
-1. Install `libreoffice` and `djvulibre-bin` packages:
+1. Install necessary packages:
+******************************
 
   .. code-block:: bash
 
-    sudo apt-get install -y libreoffice djvulibre-bin
+    sudo apt-get install -y libreoffice djvulibre-bin unzip unrar
 
-These packages are used by converters (doc, odt to docx; xls, ods to xlsx; ppt, odp to pptx; djvu to pdf).
+`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.
 
+.. _install_tesseract:
 
 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.
+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:
+
+  .. code-block:: bash
+
+    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:
+
+    .. code-block:: bash
+
+       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_library_via_pip:
 
 3. Install the dedoc library via pip.
-To fulfil all the library requirements, you should have `torch~=1.11.0` and `torchvision~=0.12.0` installed.
-You can install suitable for you versions of these libraries and install dedoc using pip command:
+*************************************
+You need `torch~=1.11.0` and `torchvision~=0.12.0` installed.
+If you already have torch and torchvision in your environment:
 
   .. code-block:: bash
 
@@ -90,3 +117,69 @@ Or you can install dedoc with torch and torchvision included:
   .. code-block:: bash
 
     pip install "dedoc[torch]"
+
+Install and run dedoc from sources
+----------------------------------
+
+If you want to run dedoc as a service from sources. it's possible to run dedoc locally.
+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: according to instructions :ref:`install_packages`
+
+2. Build Tesseract from sources according to instructions :ref:`install_tesseract`
+
+3. We recommend to install python's virtual environment (for example, via `virtualenvwrapper`)
+
+Below are the instructions for installing the package `virtualenvwrapper`:
+
+  .. code-block:: bash
+
+    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`:
+
+  .. code-block:: bash
+
+    # 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
+
+
+Install trusted torch (verified version)
+----------------------------------------------
+
+You can install a trusted library `torch` (as a verified version of the library, verified by tools developed by the Ivannikov Institute for System Programming of the Russian Academy of Sciences).
+
+First you need to install two required packages.:
+
+    .. code-block:: bash
+
+       sudo apt-get install -y mpich intel-mkl
+
+Second you need to install torch and torchvision from built wheels:
+
+For `python3.8`:
+  .. code-block:: bash
+
+     pip install https://github.com/ispras/dedockerfiles/raw/master/wheels/torch-1.11.0a0+git137096a-cp38-cp38-linux_x86_64.whl
+     pip install https://github.com/ispras/dedockerfiles/raw/master/wheels/torchvision-0.12.0a0%2B9b5a3fe-cp38-cp38-linux_x86_64.whl
+
+For `python3.9`:
+  .. code-block:: bash
+
+    pip install https://github.com/ispras/dedockerfiles/raw/master/wheels/torch-1.11.0a0+git137096a-cp39-cp39-linux_x86_64.whl
+    pip install https://github.com/ispras/dedockerfiles/raw/master/wheels/torchvision-0.12.0a0%2B9b5a3fe-cp39-cp39-linux_x86_64.whl