Augmenter that apply ocr error simulation to textual input.
OcrAug(name='OCR_Aug', aug_char_min=1, aug_char_max=10, aug_char_p=0.3, aug_word_p=0.3, aug_word_min=1, aug_word_max=10, stopwords=None, tokenizer=None, reverse_tokenizer=None, verbose=0, stopwords_regex=None, min_char=1)¶
Augmenter that simulate ocr error by random values. For example, OCR may recognize I as 1 incorrectly. Pre-defined OCR mapping is leveraged to replace character by possible OCR error.
- aug_char_p (float) – Percentage of character (per token) will be augmented.
- aug_char_min (int) – Minimum number of character will be augmented.
- aug_char_max (int) – Maximum number of character will be augmented. If None is passed, number of augmentation is calculated via aup_char_p. If calculated result from aug_p is smaller than aug_max, will use calculated result from aup_char_p. Otherwise, using aug_max.
- aug_word_p (float) – Percentage of word will be augmented.
- aug_word_min (int) – Minimum number of word will be augmented.
- aug_word_max (int) – Maximum number of word will be augmented. If None is passed, number of augmentation is calculated via aup_word_p. If calculated result from aug_p is smaller than aug_max, will use calculated result from aug_word_p. Otherwise, using aug_max.
- min_char (int) – If word less than this value, do not draw word for augmentation
- stopwords (list) – List of words which will be skipped from augment operation.
- stopwords_regex (str) – Regular expression for matching words which will be skipped from augment operation.
- tokenizer (func) – Customize tokenization process
- reverse_tokenizer (func) – Customize reverse of tokenization process
- name (str) – Name of this augmenter
>>> import nlpaug.augmenter.char as nac >>> aug = nac.OcrAug()
augment(data, n=1, num_thread=1)¶
- data (object/list) – Data for augmentation. It can be list of data (e.g. list of string or numpy) or single element (e.g. string or numpy)
- n (int) – Default is 1. Number of unique augmented output. Will be force to 1 if input is list of data
- num_thread (int) – Number of thread for data augmentation. Use this option when you are using CPU and n is larger than 1
>>> augmented_data = aug.augment(data)