pdfpig

Document Layout Analysis resources repos for development with PdfPig.

A Fast, Cross-Platform Pdf Reader

Extract tables from PDF files (port of tabula-java)

Cross-platform C# library to render PDF as images

A C# library to extract tabular data from PDFs (port of camelot Python version using PdfPig).

Proof of concept of training a simple Region Classifier using PdfPig and ML.NET (LightGBM). The objective is to classify each text block in a pdf document page as either title, text, list, table and image.

A step-by-step C# implementation of the Docstrum algorithm

RAG application built with .NET 8, Semantic Kernel, Azure OpenAI, Qdrant, Docker, and PdfPig for multilingual question answering over private PDF documents.

Proof of concept of a simple SVM Region Classifier using PdfPig and Accord.Net. The objective is to classify each text block in a pdf document page as either title, text, list, table and image.

Local-first PDF reader and editor: annotate, fill forms, edit text, redact, encrypt, OCR and organize pages. C# with Uno Platform, SkiaSharp and PdfPig; runs on desktop and in the browser. Libraries ship as NuGet packages.

AI Resume Analyzer: Azure OpenAI-powered ATS Scoring & Skill Gap Detection

🔬 Proof of Concept of extracting content from PDF files using multiple PDF libraries

A full-stack web app that turns Fighting Fantasy-style gamebook PDFs into playable adventures. Built with .NET 8 (Clean Architecture + EF Core/PostgreSQL) and React 19 (Vite + Tailwind), featuring layout-aware PDF parsing, real user accounts, a chronicle-style reader, and a character sheet. Still under development ;)

PDF layout intelligence for .NET — structured extraction tuned for RAG and LLM pipelines.

Free offline Windows PDF editor built for non-technical users — redaction that really deletes the text, fill & sign, page organising and OCR. No account, no upload, no subscription.

Semantic PDF and DOCX diff CLI and GitHub Action for deterministic document regression testing in CI.

DocuFlow is a modern, distributed document processing platform built on .NET Clean Architecture. It leverages Azure's AI capabilities to automatically extract, categorize, and analyze data from various document types.

This project implements a production-style RAG ingestion and retrieval pipeline in .NET 8 using Azure OpenAI, Azure AI Search, and Azure Blob Storage, with an accompanying retrieval benchmark comparing chunk sizes using Recall@K, Precision@K, MRR, and Hit@K.

.NET 10 class library that extracts structured flight data (OFP + Crew Briefing) from flight-planning PDFs — compile-time field extensibility, three-tier error model, async API.

C#/.NET solution for extracting and matching structured flight data from Operational Flight Plan and Crew Briefing PDFs, with error handling and xUnit tests.