A Repo For Document AI

Improved file parsing for LLM’s

Table Transformer (TATR) is a deep learning model for extracting tables from unstructured documents (PDFs and images). This is also the official repository for the PubTables-1M dataset and GriTS evaluation metric.

This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"

Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and Table Structure Recognition:

Table Detection and Extraction Using Deep Learning ( It is built in Python, using Luminoth, TensorFlow<2.0 and Sonnet.)

ICDAR 2019: MaskRCNN on PubLayNet datasets. Paragraph detection, table detection, figure detection,...

A Curated List of Awesome Table Structure Recognition (TSR) Research. Including models, papers, datasets and codes. Continuously updating.

CDeC-Net: Composite Deformable Cascade Network for Table Detection in Document Images

Doc2Graph transforms documents into graphs and exploit a GNN to solve several tasks.

This repository contains a 403 images dataset for table detection in documents.

Deep learning, Convolutional neural networks, Image processing, Document processing, Table detection, Page object detection, Table classification. https://www.sciencedirect.com/science/article/pii/S0925231221018142

Integrate AI-powered Document Analysis Pipelines

Google Colab Demo of CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents

Table detection (TD) and table structure recognition (TSR) using Yolov5/Yolov8, cand you can get the same (even better) result compared with Table Transformer (TATR) with smaller models.

Graphical Object Detection in Document Images

Table Detection using Deep Learning

Official PyTorch implementation of PyramidTabNet: Transformer-based Table Recognition in Image-based Documents

Using a MaskRCNN model trained on the PublayNet dataset with ML.Net in C# / .Net for Document layout analysis and page segmmentation task.

Build a RAG preprocessing pipeline