超轻量级中文ocr，支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M

A packaged and flexible version of the CRAFT text detector and Keras CRNN recognition model.

[python3.6] 运用tf实现自然场景文字检测,keras/pytorch实现ctpn+crnn+ctc实现不定长场景文字OCR识别

Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.

(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

Connectionist Temporal Classification (CTC) decoding algorithms: best path, beam search, lexicon search, prefix search, and token passing. Implemented in Python.

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

[验证码识别-部署] This project is based on CNN+BLSTM+CTC to realize verificationtion. This projeccode identificat is only for deployment models.

基于pytorch的ocr算法库，包括 psenet, pan, dbnet, sast , crnn

Tensorflow-based CNN+LSTM trained with CTC-loss for OCR

Pytorch implementation of CRNN (CNN + RNN + CTCLoss) for all language OCR.