This project's objective is to allow ocr of any language and font (handwriting also). The basic idea is instead of relaying on a general algorithm trained on huge datasets, in this project the training (or transfer learning) will be done on the current dataset (i.e. first pages of a book)

• a basic tool for marking classifying and viewing the data is ready.
• a basic NN model for detecting letters added (based on EAST word detection network)
• a basic NN model for identifying letters added (simplest vanilla cnn used)
• for gui tkinter was used, for NN pytorch was used

• improve mvc
• add support for moving letters
• support marking just part of page
• add visualization for training and inference process
• add duplication detection

• investigate strange loss graphs
• chose wisely networks
• add gt page visualization (boxes as image)

• ignore misses and false of lettres detection in boundary

• split letters by logic in train
• add automatic letters clustering
• add support for punctuation (also nikud like in hebrew)

• add lettres on page into words and lines tool
• detect spaces