A Faster LayoutReader Model based on LayoutLMv3, Sort OCR bboxes to reading order.
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Updated
Aug 15, 2025 - Python
A Faster LayoutReader Model based on LayoutLMv3, Sort OCR bboxes to reading order.
Welcome to the LayoutLMv3 Fine-Tuning project! 🚀 This project focuses on extracting structured data from invoices and PDFs using LayoutLMv3, PaddleOCR, and Label Studio. The system extracts key fields like invoice number, date, vendor GSTIN, PAN, product description, rate, quantity, and amount.
The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. This repository is actively maintained, and new features are continuously being added.
FastAPI application for document classification using a multimodal LayoutLM model, designed to classify PDF documents into RVL-DCIP categories.
An OCR-based invoice processing system built with FastAPI for extracting and managing invoice data.
LayoutLMv3 applied to a VQA problem with infographics.
AI-powered Gov. ID classifier using OCR, BERT, ResNet, and LayoutLMv3 for Aadhar, PAN, Passport, and other scanned IDs.
python tool designed to convert PDF2IMG, annotate images and maintaining databases particularly for fine-tuning LayoutLMv3
Offline Intelligent Document Parser Extracts structured data from invoices, receipts, and scanned documents using OCR + AI models (FLAN-T5, LayoutLM). Works offline. Exports to JSON, Excel, and SQLite.
Fine-tuning LayoutLMv3 on the SROIE dataset to build a receipt understanding model
LAGER - Layout Aware Graph Based Entity Recognition model (Accepted to LREC-COLING 2024)
End-to-end computer vision + NLP system for automated bank cheque verification — LayoutLMv3 encoder fused with a LoRA fine-tuned TinyLlama decoder to extract payee, amounts, date & signature as structured JSON, with automated fraud checks and a Streamlit demo.
六个渐进式实验走通文档智能演进:Tesseract → PaddleOCR → 自建 Agentic 管线 → LandingAI ADE → RAG。含表格/图表/手写体等高难度文档实战与视觉溯源
Bachelor thesis: automated classification & metadata extraction of German technical drawings by fine-tuning Donut and LayoutLMv3
Explainable Multimodal Identity Verification using LayoutLMv3, LoRA and Document AI
Privacy-first financial document processing engine for invoices, receipts, and expense vouchers. Combines Tesseract OCR, spatial token alignment, deterministic financial validation, human-in-the-loop review, and optional LayoutLMv3 for local document extraction.
Intelligent Document Processing: LayoutLMv3 fine-tuning (PyTorch) alongside rule, LLM and transformer QA backends, with OCR, Swiss validation (IBAN/MWST), human-in-the-loop review, MLflow, Prometheus and Kubernetes.
Multi-modal document understanding for legal and financial PDFs: hybrid LayoutLMv3 + Donut + rules extraction with confidence scoring, a trained document classifier, table extraction, and semantic search.
Multiservice document intelligence prototype with OCR, LayoutLMv3, Pinecone retrieval, LLM routing, monitoring, and public-corpus SEC evaluation.
Research-oriented Document AI using LayoutLMv3 + EasyOCR for multimodal document understanding, entity extraction, and robustness evaluation.
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