A Repo For Document AI

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"

整理目前开源的最优表格识别模型，完善前后处理，模型转换为ONNX | Organize the currently open-source optimal table recognition models, improve pre-processing and post-processing, and convert the models to ONNX.

Dedoc is a library (service) for automate documents parsing and bringing to a uniform format. It automatically extracts content, logical structure, tables, and meta information from textual electronic documents. (Parse document; Document content extraction; Logical structure extraction; PDF parser; Scanned document parser; DOCX parser; HTML parser

基于序列表格识别算法推理库，集成PP-Structure和modelscope等表格识别算法。

A curated list of resources dedicated to table recognition

ACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.

文档方向分类

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

Complex data extraction and orchestration framework designed for processing unstructured documents. It integrates AI-powered document pipelines (GenAI, LLM, VLLM) into your applications, supporting various tasks such as document cleanup, optical character recognition (OCR), classification, splitting, named entity recognition, and form processing

Table Structure Recognition

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

A Unified Toolkit for Deep Learning-Based Table Extraction

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

Extracting Tabular Data from Image to Excel files

A curated list of resources on Table Structure Recognition

Compute benchmark of table structure recognition.

利用Swin-Unet(Swin Transformer Unet)实现对文档图片里表格结构的识别，Swin-unet (Swin Transformer Unet) is used to identify the document table structure

GLM-OCRを使ったローカルOCRサーバー（FastAPI + Web UI / 画像・PDF対応）

code for participation in ICDAR2021 Table Recognition track (Team Name: LTIAYN = Kaen Context)