Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
-
Updated
Jan 23, 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
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
Doxaria OCR/HTR for medical insurance documents
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.
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
End to End Nepali Document OCR and automated Form-Filling.
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.
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.
A RunPod serverless worker for Microsoft TrOCR, a HuggingFace transformer-based OCR model specialized for single-line text recognition — both printed and handwritten.
Add a description, image, and links to the trocr topic page so that developers can more easily learn about it.
To associate your repository with the trocr topic, visit your repo's landing page and select "manage topics."