LAYOUTREADER

Introduction

LAYOUTREADER is a model designed for predicting reading order. It processes bounding boxes (bboxes) extracted from PDFs or detected by Optical Character Recognition (OCR) systems and arranges them into a readable sequence.

Architecture

LAYOUTREADER utilizes the layoutlmv3 architecture, integrating token classification capabilities with the transformers library. It is implemented in PyTorch and supports safetensors for secure tensor handling.

Training

Specific details about the training process for LAYOUTREADER are not provided in the available documentation. For comprehensive information, please refer to the GitHub repository.

Guide: Running Locally

1. Clone the Repository:
   Clone the LAYOUTREADER repository from GitHub.

   git clone https://github.com/ppaanngggg/layoutreader.git
   

2. Install Dependencies:
   Navigate to the project directory and install the necessary dependencies, typically using pip.

   cd layoutreader
   pip install -r requirements.txt
   

3. Run the Model:
   Execute the model using the provided scripts or commands in the repository.

4. Cloud GPUs:
   For optimal performance, especially with large datasets, consider using cloud GPU services such as Google Cloud, AWS, or Azure.

License

The licensing information for LAYOUTREADER is not specified in the documentation. Please check the GitHub repository for more details.