microsoft/table-transformer

Health v2 · maintenance only

Adoption not part of the score

2939 stars · 315 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Table Transformer (TATR) is a deep learning object detection model from Microsoft for detecting, recognizing, and extracting tables from unstructured documents like PDFs and images, outputting HTML or CSV. It is also the official repository for the PubTables-1M dataset and the GriTS evaluation metric.

Use cases

• extract tables from pdf documents
• detect tables in scanned images
• convert table images to html or csv
• recognize table structure in unstructured documents
• train a custom table extraction model
• evaluate table structure recognition models with grits
• download pubtables-1m dataset for research

When to choose

• you need state-of-the-art table detection and structure recognition from PDFs or images
• you want pre-trained weights trained on the large PubTables-1M dataset
• you need a research-grade model with training and evaluation code included

When to avoid

• you need a turnkey end-to-end document parser with OCR included - text extraction must be supplied separately
• you need pre-trained weights for document domains outside those covered by released models
• you want a simple no-GPU inference solution

Facets

library · maturity active

machine-learning computer-vision ocr pdf image-processing parser computer-vision pdf machine-learning data-science python cross-platform table-detection table-structure-recognition object-detection pubtables-1m grits document-understanding pytorch natural-language-processing

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markdown · JSON · MCP: product_card(name="microsoft/table-transformer")