Table Transformer

Table Transformer is an AI-powered document processing tool designed to detect and understand tables in document images. It uses transformer-based models to identify tables and recognize their structure, including rows, columns, headers, and cells. Table Transformer is suitable for developers, researchers, data analysts, document processing applications, and businesses working with structured information in documents.

Features of Table Transformer:

• Uses transformer-based AI models for table detection and structure recognition.
• Detects tables in document images and scanned documents.
• Recognizes rows, columns, headers, and cells within tables.
• Helps automate table structure analysis and document processing.
• Supports document intelligence and data extraction workflows.
• Can be integrated into Python-based document processing applications.
• Suitable for research, data analysis, automation, and document processing projects.
• Runs in a Docker-based environment for convenient deployment and management.

Table Transformer usage:

$ sudo su
$ python --version
$ pip show torch
$ pip show torchvision
$ pip show transformers
$python -c "import torch, transformers; print('PyTorch:', torch.__version__); print('Transformers:', transformers.__version__); print('CUDA available:', torch.cuda.is_available())"

Disclaimer: Table Transformer is developed by Microsoft and provided as an AI-based table detection and structure recognition model. Users are responsible for configuring and using the software in accordance with their organizational requirements and applicable licenses, terms, and policies.