handwritten-text-recognition

Handwritten Text Recognition (HTR) system implemented with TensorFlow.

OCR engine for all the languages

Connectionist Temporal Classification (CTC) decoder with dictionary and language model.

Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.

TensorFlow convolutional recurrent neural network (CRNN) for text recognition

Powerful handwritten text recognition. A simple-to-use, unofficial implementation of the paper "TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models".

Page to PAGE Layout Analysis Tool

Apply different text recognition services to images of handwritten documents.

End-to-end model training and deployment reference for handwritten Chinese text recognition, and can also be extended to other languages.

✏ ☁ The easy way to integrate text handwriting recognition in your web app.

Handwritten text recognition using transformers.

Lightweight CRNN for OCR (including handwritten text) with depthwise separable convolutions and spatial transformer module [keras+tf]

Public implementation of our CVPR Paper "OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page TextRecognition by learning to unfold"

Official implementation for ICDAR 2021 best poster paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"

Official implementation for ECCV 2022 paper "CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition"

Detect and read handwritten words on scanned pages.

(Pattern Recognition) Pytorch implementation of “HTR-VT: Handwritten Text Recognition with Vision Transformer”

Easter2.0: IMPROVING CONVOLUTIONAL MODELS FOR HANDWRITTEN TEXT RECOGNITION

Handwritten Kazakh and Russian (HKR) database for text recognition

OCR Tamil is a powerful tool that can detect and recognize text in Tamil images with high accuracy on Natural Scenes