Module recognition 

Text recognition engines for OCR

Re-exports

pub use crate::utils::OcrError;

pub use crate::utils::Result;

pub use cnn_model::*;

pub use confidence::*;

pub use crnn::*;

pub use end_to_end_model::*;

pub use engine::*;

pub use hybrid_model::*;

pub use lstm::*;

pub use lstm_model::*;

pub use pattern::*;

pub use pattern_model::*;

pub use transformer_model::*;

pub use vit_model::*;

Modules

basic_ocr

Basic OCR engine implementation inspired by Tesseract

cnn_model

Convolutional Neural Network (CNN) model implementation for OCR

confidence

Confidence extraction and calibration for OCR recognition.

crnn

CRNN (Convolutional RNN) OCR model

ctc_decoder

CTC (Connectionist Temporal Classification) decoder

end_to_end_model

End-to-End OCR model implementation

engine

Modern recognition engine interface for OCR

font_attributes

Font attribute detection

hybrid_model

Hybrid OCR model implementation

lstm

LSTM-based recognition engine

lstm_model

LSTM-based OCR model implementation

pattern

Pattern matching recognition engine

pattern_model

Pattern-based OCR model implementation

tesseract_blob

Tesseract-style blob detection and analysis

tesseract_features

Tesseract-style feature extraction for character classification

tesseract_textline

Tesseract-style text line detection

transformer_model

Transformer-based OCR model implementation

vit_model

Vision Transformer (ViT) model implementation for OCR