| Name | toolri JSON |
| Version |
1.0.1
JSON |
| download |
| home_page | None |
| Summary | A tool for extracting, labeling and linking entities in document images for Information Extraction tasks. |
| upload_time | 2024-08-09 20:57:08 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# ToolRI
ToolRI was created to simplify and standardize the creation of samples for the task of Information Extraction in document images. The tool allows text extraction by OCR, the creation of document entities and their labeling and linking. The project was created purely with Python and can be run on any desktop platform. The graphical user interface is implemented thanks to the amazing <a href="https://github.com/tomschimansky/customtkinter">CustomTkinter</a> library.
## Instalation
### PyPi
Install the ToolRI package with `pip`:
pip install toolri
### Source
Clone the ToolRI repository with:
git clone https://github.com/Victorgonl/ToolRI
And install using `pip`:
pip install ./ToolRI/
## Standalone
### Download
You can download a portable binary of the tool to start using right away. Download and run a version on the <a href="https://github.com/Victorgonl/ToolRI/releases">releases</a> page of the ToolRI repository.
### Build
To build the standalone version of ToolRI into a portable binary, clone the repository:
git clone https://github.com/Victorgonl/ToolRI
Change current directory to `./ToolRI`:
cd ./ToolRI
Install all the dependencies found on `requirements.txt`:
pip install -r requirements.txt
And run the script `toolri_build.py`:
python3 toolri_build.py
The binary will be available on `dist` folder.
## Documentation
***Under construction.*** :construction:
## Tesseract OCR
To be able to use the OCR function in ToolRI, Tesseract OCR must be installed separately.
***For now, OCR is configured for English and Portuguese languages only, but it will be updated soon for all languages available.*** :construction:
### Debian based
Use the command:
sudo apt-get install tesseract-ocr tesseract-ocr-eng tesseract-ocr-por
### Windows
- Download and run the installer available at https://github.com/UB-Mannheim/tesseract/wiki.
- Make sure to install Tesseract on `C:\Program Files\Tesseract-OCR\` (the default directory) due to a predefined configuration in current ToolRI version.
## Usage
ToolRI was developed and used to create the <a href="https://github.com/LabRI-Information-Retrieval-Lab/UFLA-FORMS">UFLA-FORMS</a> dataset. Download the dataset to try the tool on the available samples or create a new metadata for any document image available.
### Example
import toolri
image = toolri.load_image("document_image.jpg")
labels = [
toolri.ToolRILabel(name="QUESTION", color="#004B80", links=["ANSWER"], is_visible=True),
toolri.ToolRILabel(name="ANSWER", color="#00943E", links=[], is_visible=True)
]
data = toolri.toolri(image=image, data=data, labels=labels)
toolri.draw_data_on_image(image=image, data=data, labels=labels).show()
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"description": "# ToolRI\n\nToolRI was created to simplify and standardize the creation of samples for the task of Information Extraction in document images. The tool allows text extraction by OCR, the creation of document entities and their labeling and linking. The project was created purely with Python and can be run on any desktop platform. The graphical user interface is implemented thanks to the amazing <a href=\"https://github.com/tomschimansky/customtkinter\">CustomTkinter</a> library.\n\n## Instalation\n\n### PyPi\n\nInstall the ToolRI package with `pip`:\n\n pip install toolri\n\n### Source\n\nClone the ToolRI repository with:\n\n git clone https://github.com/Victorgonl/ToolRI\n\nAnd install using `pip`:\n\n pip install ./ToolRI/\n\n## Standalone\n\n### Download\n\nYou can download a portable binary of the tool to start using right away. Download and run a version on the <a href=\"https://github.com/Victorgonl/ToolRI/releases\">releases</a> page of the ToolRI repository.\n\n### Build\n\nTo build the standalone version of ToolRI into a portable binary, clone the repository:\n\n git clone https://github.com/Victorgonl/ToolRI\n\nChange current directory to `./ToolRI`:\n\n cd ./ToolRI\n\nInstall all the dependencies found on `requirements.txt`:\n\n pip install -r requirements.txt\n\nAnd run the script `toolri_build.py`:\n\n python3 toolri_build.py\n\nThe binary will be available on `dist` folder.\n\n## Documentation\n\n***Under construction.*** :construction:\n\n## Tesseract OCR\n\nTo be able to use the OCR function in ToolRI, Tesseract OCR must be installed separately.\n\n***For now, OCR is configured for English and Portuguese languages only, but it will be updated soon for all languages available.*** :construction:\n\n### Debian based\n\nUse the command:\n\n sudo apt-get install tesseract-ocr tesseract-ocr-eng tesseract-ocr-por\n\n### Windows\n\n- Download and run the installer available at https://github.com/UB-Mannheim/tesseract/wiki.\n\n- Make sure to install Tesseract on `C:\\Program Files\\Tesseract-OCR\\` (the default directory) due to a predefined configuration in current ToolRI version.\n\n## Usage\n\nToolRI was developed and used to create the <a href=\"https://github.com/LabRI-Information-Retrieval-Lab/UFLA-FORMS\">UFLA-FORMS</a> dataset. Download the dataset to try the tool on the available samples or create a new metadata for any document image available.\n\n### Example\n\n import toolri\n\n image = toolri.load_image(\"document_image.jpg\")\n\n labels = [\n toolri.ToolRILabel(name=\"QUESTION\", color=\"#004B80\", links=[\"ANSWER\"], is_visible=True),\n toolri.ToolRILabel(name=\"ANSWER\", color=\"#00943E\", links=[], is_visible=True)\n ]\n\n data = toolri.toolri(image=image, data=data, labels=labels)\n\n toolri.draw_data_on_image(image=image, data=data, labels=labels).show()\n",
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