TESSERACT(1)

NAME
tesseract - command-line OCR engine

SYNOPSIS

tesseract FILE OUTPUTBASE [OPTIONS]... [CONFIGFILE]...

DESCRIPTION

tesseract(1) is a commercial quality OCR engine originally developed at HP between 1985 and 1995. In 1995, this engine was among the top 3 evaluated by UNLV. It was open-sourced by HP and UNLV in 2005, and has been developed at Google until 2018.

IN/OUT ARGUMENTS

FILE
    The name of the input file. This can either be an image file or a text file.
    Most image file formats (anything readable by Leptonica) are supported.
    A text file lists the names of all input images (one image name per line). The results will be combined in a single file for each output file format (txt, pdf, hocr, xml).
    If FILE is stdin or - then the standard input is used.

OUTPUTBASE
    The basename of the output file (to which the appropriate extension will be appended). By default the output will be a text file with .txt added to the basename unless there are one or more parameters set which explicitly specify the desired output.
    If OUTPUTBASE is stdout or - then the standard output is used.

OPTIONS

-c CONFIGVAR=VALUE
    Set value for parameter CONFIGVAR to VALUE. Multiple -c arguments are allowed.

--dpi N
    Specify the resolution N in DPI for the input image(s). A typical value for N is 300. Without this option, the resolution is read from the metadata included in the image. If an image does not include that information, Tesseract tries to guess it.

-l LANG, -l SCRIPT
    The language or script to use. If none is specified, eng (English) is assumed. Multiple languages may be specified, separated by plus characters. Tesseract uses 3-character ISO 639-2 language codes (see LANGUAGES AND SCRIPTS).

--psm N
    Set Tesseract to only run a subset of layout analysis and assume a certain form of image. The options for N are:

        0 = Orientation and script detection (OSD) only.
        1 = Automatic page segmentation with OSD.
        2 = Automatic page segmentation, but no OSD, or OCR. (not implemented)
        3 = Fully automatic page segmentation, but no OSD. (Default)
        4 = Assume a single column of text of variable sizes.
        5 = Assume a single uniform block of vertically aligned text.
        6 = Assume a single uniform block of text.
        7 = Treat the image as a single text line.
        8 = Treat the image as a single word.
        9 = Treat the image as a single word in a circle.
        10 = Treat the image as a single character.
        11 = Sparse text. Find as much text as possible in no particular order.
        12 = Sparse text with OSD.
        13 = Raw line. Treat the image as a single text line,
             bypassing hacks that are Tesseract-specific.

--oem N
    Specify OCR Engine mode. The options for N are:

        0 = Original Tesseract only.
        1 = Neural nets LSTM only.
        2 = Tesseract + LSTM.
        3 = Default, based on what is available.

--tessdata-dir PATH
    Specify the location of tessdata path.

--user-patterns FILE
    Specify the location of user patterns file.

--user-words FILE
    Specify the location of user words file.

CONFIGFILE
    The name of a config to use. The name can be a file in tessdata/configs or tessdata/tessconfigs, or an absolute or relative file path. A config is a plain text file which contains a list of parameters and their values, one per line, with a space separating parameter from value.
    Interesting config files include:

        • alto — Output in ALTO format (OUTPUTBASE.xml).

        • hocr — Output in hOCR format (OUTPUTBASE.hocr).

        • page — Output in PAGE format (OUTPUTBASE.page.xml). The output can be customized with the flags: page_xml_polygon — Create polygons instead of bounding boxes (default: true) page_xml_level — Create the PAGE file on 0=linelevel or 1=wordlevel (default: 0)

        • pdf — Output PDF (OUTPUTBASE.pdf).

        • tsv — Output TSV (OUTPUTBASE.tsv).

        • txt — Output plain text (OUTPUTBASE.txt).

        • get.images — Write processed input images to file (OUTPUTBASE.processedPAGENUMBER.tif).

        • logfile — Redirect debug messages to file (tesseract.log).

        • lstm.train — Output files used by LSTM training (OUTPUTBASE.lstmf).

        • makebox — Write box file (OUTPUTBASE.box).

        • quiet — Redirect debug messages to /dev/null.

It is possible to select several config files, for example tesseract image.png demo alto hocr pdf txt will create four output files demo.alto, demo.hocr, demo.pdf and demo.txt with the OCR results.

Nota bene: The options -l LANG, -l SCRIPT and --psm N must occur before any CONFIGFILE.

SINGLE OPTIONS

-h, --help
    Show help message.

--help-extra
    Show extra help for advanced users.

--help-psm
    Show page segmentation modes.

--help-oem
    Show OCR Engine modes.

-v, --version
    Returns the current version of the tesseract(1) executable.

--list-langs
    List available languages for tesseract engine. Can be used with --tessdata-dir PATH.

--print-parameters
    Print tesseract parameters.

LANGUAGES AND SCRIPTS

To recognize some text with Tesseract, it is normally necessary to specify the language(s) or script(s) of the text (unless it is English text which is supported by default) using -l LANG or -l SCRIPT.

Selecting a language automatically also selects the language specific character set and dictionary (word list).

Selecting a script typically selects all characters of that script which can be from different languages. The dictionary which is included also contains a mix from different languages. In most cases, a script also supports English. So it is possible to recognize a language that has not been specifically trained for by using traineddata for the script it is written in.

More than one language or script may be specified by using +. Example: tesseract myimage.png myimage -l eng+deu+fra.

provides fast language and script models which are also part of Linux distributions.

For Tesseract 4, tessdata_fast includes traineddata files for the following languages:

afr (Afrikaans), amh (Amharic), ara (Arabic), asm (Assamese), aze (Azerbaijani), aze_cyrl (Azerbaijani - Cyrillic), bel (Belarusian), ben (Bengali), bod (Tibetan), bos (Bosnian), bre (Breton), bul (Bulgarian), cat (Catalan; Valencian), ceb (Cebuano), ces (Czech), chi_sim (Chinese simplified), chi_tra (Chinese traditional), chr (Cherokee), cos (Corsican), cym (Welsh), dan (Danish), deu (German), deu_latf (German Fraktur Latin), div (Dhivehi), dzo (Dzongkha), ell (Greek, Modern, 1453-), eng (English), enm (English, Middle, 1100-1500), epo (Esperanto), equ (Math / equation detection module), est (Estonian), eus (Basque), fas (Persian), fao (Faroese), fil (Filipino), fin (Finnish), fra (French), frm (French, Middle, ca.1400-1600), fry (West Frisian), gla (Scottish Gaelic), gle (Irish), glg (Galician), grc (Greek, Ancient, to 1453), guj (Gujarati), hat (Haitian; Haitian Creole), heb (Hebrew), hin (Hindi), hrv (Croatian), hun (Hungarian), hye (Armenian), iku (Inuktitut), ind (Indonesian), isl (Icelandic), ita (Italian), ita_old (Italian - Old), jav (Javanese), jpn (Japanese), kan (Kannada), kat (Georgian), kat_old (Georgian - Old), kaz (Kazakh), khm (Central Khmer), kir (Kirghiz; Kyrgyz), kmr (Kurdish Kurmanji), kor (Korean), kor_vert (Korean vertical), lao (Lao), lat (Latin), lav (Latvian), lit (Lithuanian), ltz (Luxembourgish), mal (Malayalam), mar (Marathi), mkd (Macedonian), mlt (Maltese), mon (Mongolian), mri (Maori), msa (Malay), mya (Burmese), nep (Nepali), nld (Dutch; Flemish), nor (Norwegian), oci (Occitan post 1500), ori (Oriya), osd (Orientation and script detection module), pan (Panjabi; Punjabi), pol (Polish), por (Portuguese), pus (Pushto; Pashto), que (Quechua), ron (Romanian; Moldavian; Moldovan), rus (Russian), san (Sanskrit), sin (Sinhala; Sinhalese), slk (Slovak), slv (Slovenian), snd (Sindhi), spa (Spanish; Castilian), spa_old (Spanish; Castilian - Old), sqi (Albanian), srp (Serbian), srp_latn (Serbian - Latin), sun (Sundanese), swa (Swahili), swe (Swedish), syr (Syriac), tam (Tamil), tat (Tatar), tel (Telugu), tgk (Tajik), tha (Thai), tir (Tigrinya), ton (Tonga), tur (Turkish), uig (Uighur; Uyghur), ukr (Ukrainian), urd (Urdu), uzb (Uzbek), uzb_cyrl (Uzbek - Cyrillic), vie (Vietnamese), yid (Yiddish), yor (Yoruba)

To use a non-standard language pack named foo.traineddata, set the TESSDATA_PREFIX environment variable so the file can be found at TESSDATA_PREFIX/tessdata/foo.traineddata and give Tesseract the argument -l foo.

For Tesseract 4, tessdata_fast includes traineddata files for the following scripts:

Arabic, Armenian, Bengali, Canadian_Aboriginal, Cherokee, Cyrillic, Devanagari, Ethiopic, Fraktur, Georgian, Greek, Gujarati, Gurmukhi, HanS (Han simplified), HanS_vert (Han simplified, vertical), HanT (Han traditional), HanT_vert (Han traditional, vertical), Hangul, Hangul_vert (Hangul vertical), Hebrew, Japanese, Japanese_vert (Japanese vertical), Kannada, Khmer, Lao, Latin, Malayalam, Myanmar, Oriya (Odia), Sinhala, Syriac, Tamil, Telugu, Thaana, Thai, Tibetan, Vietnamese.

The same languages and scripts are available from tessdata_best provides slow language and script models. These models are needed for training. They also can give better OCR results, but the recognition takes much more time.

Both tessdata_fast and tessdata_best only support the LSTM OCR engine.

There is a third repository, with models which support both the Tesseract 3 legacy OCR engine and the Tesseract 4 LSTM OCR engine.

CONFIG FILES AND AUGMENTING WITH USER DATA

Tesseract config files consist of lines with parameter-value pairs (space separated). The parameters are documented as flags in the source code like the following one in tesseractclass.h:

STRING_VAR_H(tessedit_char_blacklist, "", "Blacklist of chars not to recognize");

These parameters may enable or disable various features of the engine, and may cause it to load (or not load) various data. For instance, let’s suppose you want to OCR in English, but suppress the normal dictionary and load an alternative word list and an alternative list of patterns — these two files are the most commonly used extra data files.

If your language pack is in /path/to/eng.traineddata and the hocr config is in /path/to/configs/hocr then create three new files:

/path/to/eng.user-words:

the
quick
brown
fox
jumped

/path/to/eng.user-patterns:

1-\d\d\d-GOOG-411
www.\n\\\*.com

/path/to/configs/bazaar:

load_system_dawg     F
load_freq_dawg       F
user_words_suffix    user-words
user_patterns_suffix user-patterns

Now, if you pass the word bazaar as a CONFIGFILE to Tesseract, Tesseract will not bother loading the system dictionary nor the dictionary of frequent words and will load and use the eng.user-words and eng.user-patterns files you provided. The former is a simple word list, one per line. The format of the latter is documented in dict/trie.h on read_pattern_list().

PARAMETERS

Tesseract parameters control the behaviour of the OCR engine and can be set using the -c option (e.g. -c tessedit_char_whitelist=0123456789) or by placing them in a CONFIGFILE. The example above restricts recognized characters to digits only. Run --print-parameters to list all available parameters with their current values and short descriptions.

The engine column indicates which OCR engine modes support a parameter:
Both — works with both the LSTM and Legacy engines;
LSTM — only applies to the neural-network LSTM engine (OEM 1 or 2);
Legacy — only applies to the legacy Tesseract engine (OEM 0 or 2).

  OUTPUT FORMAT PARAMETERS

tessedit_create_txt (bool, default: 0) [Both]
    Write plain-text output to a .txt file. This is the default output format when no config file or -c option overrides it.

tessedit_create_hocr (bool, default: 0) [Both]
    Write hOCR output to a .hocr file. hOCR is an HTML-based format that encodes the OCR results together with their bounding boxes and confidences. Use the hocr config file to enable this format. See the hOCR specification at for details of the output format.

hocr_font_info (bool, default: 0) [Both]
    Add per-word font metadata to hOCR output. When enabled, each word span includes x_font (font name) and x_fsize (point size) attributes in its title field. Font information is derived from the recognition results and is most reliable with the Legacy OCR engine; the LSTM engine may produce less precise font names.

hocr_char_boxes (bool, default: 0) [Both]
    Add per-character bounding-box coordinates to hOCR output as ocrx_cinfo spans. Note that character-level bounding boxes may be less precise when using the LSTM engine, because LSTM operates at the line level and character positions are approximated from the line result. See also lstm_choice_mode for LSTM-specific character alternative output.

tessedit_create_alto (bool, default: 0) [Both]
    Write ALTO XML output to a .xml file. ALTO (Analyzed Layout and Text Object) is a standard XML schema for describing the layout and content of pages. Use the alto config file to enable this format.

tessedit_create_page_xml (bool, default: 0) [Both]
    Write PAGE XML output to a .page.xml file. PAGE (Page Analysis and Ground Truth Elements) is a standard XML format widely used in digital humanities projects, library and archive workflows, and document annotation tools such as Transkribus and eScriptorium. See for the specification. Use the page config file to enable this format.

page_xml_polygon (bool, default: 1) [Both]
    When writing PAGE XML output, create polygon outlines around text regions instead of simple bounding boxes.

page_xml_level (int, default: 0) [Both]
    Granularity of PAGE XML output: 0 = line level, 1 = word level.

tessedit_create_tsv (bool, default: 0) [Both]
    Write tab-separated-values output to a .tsv file. Each recognized word is output as one row with its bounding box, confidence and text. Use the tsv config file to enable this format.

tessedit_create_pdf (bool, default: 0) [Both]
    Write a searchable PDF to a .pdf file. The PDF contains the original image with an invisible text layer for copy-paste and searching. Use the pdf config file to enable this format.

textonly_pdf (bool, default: 0) [Both]
    Write a text-only PDF (no image, only invisible text) to a .pdf file.

tessedit_create_boxfile (bool, default: 0) [Both]
    Write a Tesseract box file (.box) that lists each recognized character with its bounding box, one per line. Can be produced by either engine. These files are primarily used as ground truth for legacy engine training.

tessedit_create_wordstrbox (bool, default: 0) [Both]
    Write a WordStr-format box file (.box). Similar to tessedit_create_boxfile but records whole words instead of individual characters.

tessedit_create_lstmbox (bool, default: 0) [LSTM]
    Write an LSTM box file (.box) suitable for LSTM training.

preserve_interword_spaces (bool, default: 0) [Both]
    Preserve multiple consecutive inter-word spaces in the output instead of collapsing them to a single space.

  CHARACTER SET PARAMETERS

tessedit_char_whitelist (string, default: "") [Both]
    Restrict the set of characters that Tesseract will recognize to only those listed in this string (allowlist). For example, setting this to 0123456789 will make Tesseract return only digits. An empty value (the default) means all characters in the trained data are allowed.

tessedit_char_blacklist (string, default: "") [Both]
    Prevent Tesseract from recognizing the characters listed in this string. Characters in this list will never appear in the output. This exclusion list is applied after the allowlist (tessedit_char_whitelist).

tessedit_char_unblacklist (string, default: "") [Both]
    Re-allow specific characters that were excluded by tessedit_char_blacklist. Characters in this list override the exclusion list and apply to both the LSTM and Legacy engines.

  IMAGE PROCESSING PARAMETERS

thresholding_method (int, default: 0) [Both]
    Select the algorithm used to convert a greyscale image to binary before OCR: 0 = Otsu global thresholding (default); 1 = LeptonicaOtsu (tiled Otsu, better for uneven lighting); 2 = Sauvola local adaptive thresholding (best for heavily degraded documents).

thresholding_window_size (double, default: 0.33) [Both]
    Window size (multiplied by image DPI) used to compute local statistics for the Sauvola thresholding method (thresholding_method = 2).

thresholding_kfactor (double, default: 0.34) [Both]
    Sensitivity factor for Sauvola thresholding (thresholding_method = 2). Controls how much the local variance reduces the threshold. Typical range: 0.2 — 0.5. Higher values produce more aggressive thresholding.

thresholding_tile_size (double, default: 0.33) [Both]
    Desired tile size (multiplied by image DPI) for the LeptonicaOtsu tiled thresholding method (thresholding_method = 1).

thresholding_smooth_kernel_size (double, default: 0) [Both]
    Kernel size for smoothing the threshold array produced by LeptonicaOtsu (thresholding_method = 1). Use 0 for no smoothing.

thresholding_score_fraction (double, default: 0.1) [Both]
    Fraction of the maximum Otsu score used by LeptonicaOtsu (thresholding_method = 1). Use 0.0 for standard Otsu behaviour; 0.1 is recommended for better robustness.

tessedit_do_invert (bool, default: 1) [Both]
    Deprecated — will be removed in a future release. When enabled, Tesseract tries OCR on an inverted (white-on-black) copy of lines whose mean confidence falls below invert_threshold and keeps the result with higher confidence. To disable automatic inversion, set invert_threshold = 0 rather than setting this parameter to 0.

invert_threshold (double, default: 0.7) [Both]
    Mean confidence threshold below which Tesseract will also attempt OCR on the inverted image. Lower values make inversion less likely. Set to 0 to disable automatic inversion entirely (preferred over setting tessedit_do_invert = 0, which is deprecated).

user_defined_dpi (int, default: 0) [Both]
    Override the resolution of the input image in DPI. Use this when the image metadata contains an incorrect or missing DPI value. A value of 0 means the resolution is read from the image metadata or guessed automatically. This parameter is equivalent to the --dpi command-line option; when --dpi is given on the command line it simply sets this parameter.

textord_heavy_nr (bool, default: 0) [Both]
    Aggressively remove noise blobs during page layout analysis. When disabled (the default), Tesseract applies a moderate noise threshold that preserves most legitimate characters. Enabling this raises the threshold significantly, which can improve results on scans with heavy speckle or background noise, but may also remove small legitimate characters such as punctuation marks, diacritics, or small symbols. Useful when OCR-ing degraded or low-quality document scans where accuracy on punctuation is less important than overall text extraction.

  DICTIONARY PARAMETERS

load_system_dawg (bool, default: 1) [Both]
    Load the main system word list (DAWG) from the traineddata file. Disabling this can speed up recognition and may improve results when OCR-ing content that does not resemble natural language (e.g. codes, identifiers).

load_freq_dawg (bool, default: 1) [Both]
    Load the list of frequent words from the traineddata file.

load_unambig_dawg (bool, default: 1) [Legacy]
    Load the list of unambiguous words from the traineddata file.

load_punc_dawg (bool, default: 1) [Legacy]
    Load the dawg containing punctuation patterns from the traineddata file.

load_number_dawg (bool, default: 1) [Legacy]
    Load the dawg containing number patterns from the traineddata file.

load_bigram_dawg (bool, default: 1) [Legacy]
    Load the dawg containing special word bigrams from the traineddata file.

user_words_file (string, default: "") [Both]
    Path to a plain-text file containing additional words (one per line) that Tesseract should treat as valid dictionary words.

user_words_suffix (string, default: "") [Both]
    Filename suffix (relative to the tessdata directory) for a per-language file of additional valid words. For example, setting this to user-words causes Tesseract to look for eng.user-words when using the English model.

user_patterns_file (string, default: "") [Both]
    Path to a plain-text file containing additional pattern strings (one per line) that Tesseract should accept as valid words. In the pattern language, backslash-escaped sequences specify character classes: \d = any digit; \c = any letter; \a = any lowercase letter; \A = any uppercase letter; \n = any alphanumeric character; \p = any punctuation character. All other characters match themselves. For example, 1-\d\d\d-GOOG-411 matches a phone-number-like string. These are structural templates, not regular expressions. For the full pattern syntax, see dict/trie.h in the Tesseract source.

user_patterns_suffix (string, default: "") [Both]
    Filename suffix (relative to the tessdata directory) for a per-language file of additional patterns.

  LSTM ENGINE PARAMETERS

These parameters are only meaningful when using the LSTM OCR engine (--oem 1 or --oem 2).

lstm_use_matrix (bool, default: 1) [LSTM]
    Use the ratings matrix and beam search during LSTM decoding. Disabling this reverts to a simpler, faster greedy decoding strategy that may be adequate for very clean, high-quality images but generally gives lower accuracy.

lstm_choice_mode (int, default: 0) [LSTM]
    Enables alternative character hypotheses in hOCR output (requires tessedit_create_hocr = 1): 0 = disabled (default); 1 = include per-timestep alternative choices; 2 = extract alternative choices from the CTC output mapped per character. See also hocr_char_boxes for character bounding-box output.

lstm_choice_iterations (int, default: 5) [LSTM]
    Number of cascading beam-search iterations used when lstm_choice_mode is non-zero.

lstm_rating_coefficient (double, default: 5) [LSTM]
    Scaling factor applied to LSTM character ratings. Smaller values produce higher (better) confidence scores and preserve more information before the zero cut-off. The default value is 5.

  LEGACY ENGINE PARAMETERS

The following parameters apply only when using the legacy Tesseract engine (--oem 0 or --oem 2, requires a traineddata file that includes the legacy model such as those from

tessedit_enable_bigram_correction (bool, default: 1) [Legacy]
    Apply bigram-based correction to improve recognition of adjacent word pairs that commonly appear together (e.g. "is a", "in the", "New York"). The correction uses a bigram dictionary from the traineddata file to re-score word hypotheses in context.

tessedit_enable_dict_correction (bool, default: 0) [Legacy]
    Use the dictionary to post-correct uncertain word hypotheses.

tessedit_fix_fuzzy_spaces (bool, default: 1) [Legacy]
    Try to fix spaces that were ambiguously classified as inter-word or inter-character gaps.

language_model_penalty_non_dict_word (double, default: 0.15) [Legacy]
    Penalty added to the score of word hypotheses that do not appear in the dictionary. Increase to bias recognition more strongly towards dictionary words.

language_model_penalty_non_freq_dict_word (double, default: 0.1) [Legacy]
    Additional penalty for words that are in the dictionary but not in the list of frequent words.

language_model_penalty_case (double, default: 0.1) [Legacy]
    Penalty applied when the capitalisation of a recognised word is inconsistent with the surrounding context.

language_model_penalty_script (double, default: 0.5) [Legacy]
    Penalty applied when a recognised character belongs to a different script from the surrounding text.

language_model_penalty_punc (double, default: 0.2) [Legacy]
    Penalty applied for punctuation usage that is inconsistent with the language model.

wordrec_enable_assoc (bool, default: 1) [Legacy]
    Enable the associator, which considers combinations of character fragments when forming word hypotheses. Disabling may speed up recognition at the cost of accuracy on fragmented characters.

  DEBUG PARAMETERS

debug_file (string, default: "") [Both]
    Redirect Tesseract debug/diagnostic output to this file instead of stderr. Set to /dev/null (or use the quiet config file) to suppress all debug output.

tessedit_write_params_to_file (string, default: "") [Both]
    If set to a filename, Tesseract will write the values of all its parameters to that file when it starts up. Useful for capturing the effective configuration for debugging or reproducibility.

ENVIRONMENT VARIABLES

TESSDATA_PREFIX
    If the TESSDATA_PREFIX is set to a path, then that path is used to find the tessdata directory with language and script recognition models and config files. Using --tessdata-dir PATH is the recommended alternative.

OMP_THREAD_LIMIT
    If the tesseract executable was built with multithreading support, it will normally use four CPU cores for the OCR process. While this can be faster for a single image, it gives bad performance if the host computer provides less than four CPU cores or if OCR is made for many images. Only a single CPU core is used with OMP_THREAD_LIMIT=1.

HISTORY

The engine was developed at Hewlett Packard Laboratories Bristol and at Hewlett Packard Co, Greeley Colorado between 1985 and 1994, with some more changes made in 1996 to port to Windows, and some C++izing in 1998. A lot of the code was written in C, and then some more was written in C++. The C++ code makes heavy use of a list system using macros. This predates STL, was portable before STL, and is more efficient than STL lists, but has the big negative that if you do get a segmentation violation, it is hard to debug.

Version 2.00 brought Unicode (UTF-8) support, six languages, and the ability to train Tesseract.

Tesseract was included in UNLV’s Fourth Annual Test of OCR Accuracy. See Since Tesseract 2.00, scripts are now included to allow anyone to reproduce some of these tests. See for more details.

Tesseract 3.00 added a number of new languages, including Chinese, Japanese, and Korean. It also introduced a new, single-file based system of managing language data.

Tesseract 3.02 added BiDirectional text support, the ability to recognize multiple languages in a single image, and improved layout analysis.

Tesseract 4 adds a new neural net (LSTM) based OCR engine which is focused on line recognition, but also still supports the legacy Tesseract OCR engine of Tesseract 3 which works by recognizing character patterns. Compatibility with Tesseract 3 is enabled by --oem 0. This also needs traineddata files which support the legacy engine, for example those from the tessdata repository (

For further details, see the release notes in the Tesseract documentation (

RESOURCES

Main web site:
User forum:
Documentation:
Information on training:

SEE ALSO

ambiguous_words(1), cntraining(1), combine_tessdata(1), dawg2wordlist(1), shape_training(1), mftraining(1), unicharambigs(5), unicharset(5), unicharset_extractor(1), wordlist2dawg(1)

AUTHOR

Tesseract development was led at Hewlett-Packard and Google by Ray Smith. The development team has included:

Ahmad Abdulkader, Chris Newton, Dan Johnson, Dar-Shyang Lee, David Eger, Eric Wiseblatt, Faisal Shafait, Hiroshi Takenaka, Joe Liu, Joern Wanke, Mark Seaman, Mickey Namiki, Nicholas Beato, Oded Fuhrmann, Phil Cheatle, Pingping Xiu, Pong Eksombatchai (Chantat), Ranjith Unnikrishnan, Raquel Romano, Ray Smith, Rika Antonova, Robert Moss, Samuel Charron, Sheelagh Lloyd, Shobhit Saxena, and Thomas Kielbus.

For a list of contributors see

COPYING

Licensed under the Apache License, Version 2.0