Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
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Updated
Sep 15, 2026 - Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Powerful handwritten text recognition. A simple-to-use, unofficial implementation of the paper "TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models".
Handwritten mathematical symbols recognition with TrOCR
Modular OCR pipeline for live-camera documents/screens. Auto-aligns perspective, blocks obstructions, and extracts text using interchangeable deep-learning models.
AutoRegressive Transformer Model for Optical Character Recognition In Farasi
An image to text model base on transformer which can also be used on OCR task.
FrameReader is a full-fledged service for recognizing text on frames of video materials in Russian, training, deployment of computer vision models to solve the OCR problem. Optimization of models on the tensorrt engine
A safer way to organize your handwritten medical prescriptions with the functionality of blockchain.
A service for extracting and indexing archival document images
A handwriting recognition app built around the pretrained microsoft/trocr-base-handwritten model and "mltu" CRNN model. The project focuses on model comparison for education and future improvement.
Doxaria OCR/HTR for medical insurance documents
AI-powered automated grading system using TrOCR, Sentence-BERT, OpenCV, and Streamlit to evaluate handwritten answer sheets through semantic analysis, keyword matching, and diagram comparison.
An AI-powered Optical Character Recognition (OCR) platform specifically optimized for multi-line cursive handwriting using TrOCR, vertical center-density line segmentation, and spelling correction.
High-performance LPR system optimized for Indian license plates, achieving 97% character accuracy. Features a hybrid pipeline using YOLOv11 and Mamba-SSM (State Space Models) with built-in regex correction and Beam Search decoding.
This is a handwritten-equations to latex-equations converter, built using trocrbasestage1 model + CROHME dataset + custom-built SentencePiece Tokenizer (latex)
MNIST Sequence Image-to-text TrOCR transformer using Hugging Face
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