755 Open source projects that are alternatives of or similar to Bert_ocr.pytorch

keras复现场景文本检测网络CPTN: 《Detecting Text in Natural Image with Connectionist Text Proposal Network》；欢迎试用，关注，并反馈问题...

Digitizes numbers from videos & images of seven segment displays

Natural Language Processing Tutorial for Deep Learning Researchers

[AKBC 19] Improving Relation Extraction by Pre-trained Language Representations

SwiftyTesseract Real-Time Engine

Large-scale pretraining for dialogue

Android based Vocal Vision for Visually Impaired. Object Detection, Voice Assistance, Optical Character Reader, Read Aloud, Face Recognition, Landmark Recognition, Image Labelling etc.

使用基于Transformer的预训练模型在ACE2005数据集上进行事件抽取任务

PHP ETL (Extract / Transform / Load) library with SOLID principles + almost no dependency.

speech-to-text in pytorch

This provides a sample code using vue.js running on ASP.NET Core

The module extracts text from image using the tesseract-OCR engine. Generally, text present in the images are blur or are of uneven sizes. The image is pre-processed for better comprehension by OCR. This module first makes bounding box for text in images and then normalizes it to 300 dpi, suitable for OCR engine to read.

A stupid OCR for malayalam language

using rnn (lstm or gru) and ctc to convert line image into text, based on torch7 and warp-ctc

An OCR (Optical Character Recognition) bot for Mastodon (and compatible) instances

⭐️ The native node.js bindings to the Tesseract OCR project.

MoEL: Mixture of Empathetic Listeners

This is an implementation of Show, Attend and Read with tensorflow

Transformer-XL for Jazz music composition. Paper: "The Jazz Transformer on the Front Line: Exploring the Shortcomings of AI-Composed Music through Quantitative Measures", ISMIR 2020

A Node.js wrapper for the Tesseract OCR API

Scan, index, and archive all of your paper documents

主流ocr算法研究实验性的项目，目前实现了CNN+BLSTM+CTC架构

OCR implementation with Golang

(CRNN) Chinese Characters Recognition.

中文长文本分类、短句子分类、多标签分类、两句子相似度（Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short），字词句向量嵌入层（embeddings）和网络层（graph）构建基类，FastText，TextCNN，CharCNN，TextRNN, RCNN, DCNN, DPCNN, VDCNN, CRNN, Bert, Xlnet, Albert, Attention, DeepMoji, HAN, 胶囊网络-CapsuleNet, Transformer-encode, Seq2seq, SWEM, LEAM, TextGCN

A pytorch re-implementation of Real-time Scene Text Detection with Differentiable Binarization

Witwicky: An implementation of Transformer in PyTorch.

reference tensorflow code for named entity tagging

Handwritten text recognition with Keras

A Pytorch implementation of Sparsely-Gated Mixture of Experts, for massively increasing the parameter count of language models

Data Mining Historical Newspaper Metadata (METS/ALTO formats)

Anyline React Native Module for iOS and Android

Trains a Neural Network to read handwritten digits (OCR). Uses synaptic for Node.js, socket.io and MongoDB

📇 A Simple OCR Application built on Electron, Vue.js & Tesseract.js

A Tensorflow model for text recognition (CNN + seq2seq with visual attention) available as a Python package and compatible with Google Cloud ML Engine.

FormBuilder + class-transformer + class-validator = dynamic form group builder for Angular10+

Distributed, fault tolerant batch processing for Natural Language Applications and Search, using remote partitioning

Machine-readable zone/travel document (MRZ / MRTD) detector and recognizer using deep learning

这是我自己做的一个类似滴滴打车的Android出行项目，主要针对滴滴等出行平台一直饱受质疑的“人车不符”问题，以及当前越发火热的或计划和出海战略，给出行项目增加了下面几个功能： 1. RFID识别验证功能：在司机证件或者车内识别硬件嵌入RFID识别芯片，乘客使用手机读取到芯片信息，并且通过网络发送到出行平台数据库进行验证（我用JNI加了一个C语言的MD5加密算法对识别到的信息进行了加密）。如果不是合规的“人”或“车”，则不能完成订单并向平台或监管单位汇报当前位置。（为了方便读者测试，可以使用手机读取任何一个加密或非加密RFID芯片，比如银行卡、公交卡等，我在代码中的验证前阶段把芯片信息都换成我自己的司机信息，确保读者测试时可以收到服务器的回复） 2. 海外版功能：点击切换当前语言。 3. 司机证件号码识别功能：读取司机证件上的证件号码，也可以用来与出行平台数据库的接单司机信息进行。I complete this whole project on my own . Including Android application programming，web server ( Apache + PHP + MySQL), and UI. 1．Map route planing。You can use mobile phone choose pick up & destination address，application provide address name hint and draw optimized route for user , then call car for you. 2．RFID authentication function：User can use application to scan driver license or other RFID hardware, then use NDK MD5 algorithm encrypt RFID number, and send it to Web Server Database, check with driver information and authenticate ID number , if ID number coherent with driver info , send back driver information to User and continue call car order . record user location and alert if ID not coherent. 3．Driver License Number Recognition : Application can recognize driver license digit number ,and also can send to web server for authentication & feed back result to user.

GPT2 for Chinese chitchat/用于中文闲聊的GPT2模型(实现了DialoGPT的MMI思想)

Generate text images for training deep learning ocr model

Indonesian Language Models and its Usage

使用 pytesseract ocr 识别 18 位身份证号

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Application to check authenticity of Twitter screenshots. Written in Python 🐍

A small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.

A PHP wrapper for the Tesseract OCR engine

Transformers without Tears: Improving the Normalization of Self-Attention

A photo OCR project aims to output DMS messages contained in sign structure images.

Forked from weinman/cnn_lstm_ctc_ocr for the ICPR MTWI 2018 challenge 1

Lightweight document management system packed with all the features you can expect from big expensive solutions

NanoNets OCR API Example for Python

Keras implementation of BERT with pre-trained weights

Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)

An Implementation of Transformer (Attention Is All You Need) in DyNet

GraphQL implementation with power of Laravel

Sane command-line scan-to-pdf script on Linux with OCR and deskew support

Android OCR example application which uses Google Text Recognition API

Datasets I have created for scientific summarization, and a trained BertSum model