Wie man Iron Tesseract in C#35 verwendet
Iron Tesseract in C# wird verwendet, indem eine IronTesseract-Instanz erstellt, diese mit Sprache und OCR-Einstellungen konfiguriert und dann die Read()-Methode auf einem OcrInput-Objekt aufgerufen wird, das Ihre Bilder oder PDFs enthält. Dies konvertiert Bilder von Text in durchsuchbare PDFs mit dem optimierten Engine von Tesseract 5.
IronOCR bietet eine intuitive API zur Nutzung des angepassten und optimierten Tesseract 5, bekannt als Iron Tesseract. Durch die Verwendung von IronOCR und IronTesseract können Sie Bilder von Text und gescannte Dokumente in Text und durchsuchbare PDFs umwandeln. Die Bibliothek unterstützt 125 internationale Sprachen und umfasst erweiterte Funktionen wie Barcode-Lesen und Computer Vision.
Schnellstart: IronTesseract-Konfiguration in C# einrichten
Dieses Beispiel zeigt, wie IronTesseract mit spezifischen Einstellungen konfiguriert wird und OCR in einer einzigen Codezeile durchgeführt wird.
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Installieren Sie IronOCR mit NuGet Package Manager
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Kopieren Sie diesen Codeausschnitt und führen Sie ihn aus.
var result = new IronOcr.IronTesseract { Language = IronOcr.OcrLanguage.English, Configuration = new IronOcr.TesseractConfiguration { ReadBarCodes = false, RenderSearchablePdf = true, WhiteListCharacters = "ABCabc123" } }.Read(new IronOcr.OcrInput("image.png")); -
Bereitstellen zum Testen in Ihrer Live-Umgebung
Beginnen Sie noch heute, IronOCR in Ihrem Projekt zu verwenden, mit einer kostenlosen Testversion
Grundlegender OCR-Workflow
- Installieren Sie die OCR-Bibliothek mit NuGet, um Bilder zu lesen.
- Verwendung des benutzerdefinierten `Tesseract 5` zur Durchführung von OCR
- Laden Sie die gewünschten Dokumente, wie Bilder oder PDF-Dateien, zur Verarbeitung
- Geben Sie den extrahierten Text auf der Konsole oder in einer Datei aus
- Speichern Sie das Ergebnis als durchsuchbare PDF
Wie erstelle ich eine IronTesseract-Instanz?
Initialisieren Sie ein Tesseract-Objekt mit diesem Code:
:path=/static-assets/ocr/content-code-examples/how-to/irontesseract-initialize-irontesseract.cs
using IronOcr;
IronTesseract ocr = new IronTesseract();
Imports IronOcr
Dim ocr As New IronTesseract()
Sie können das Verhalten von IronTesseract anpassen, indem Sie verschiedene Sprachen auswählen, Barcodelesen aktivieren und Zeichen auf die Positiv-/Negativliste setzen. IronOCR bietet umfassende Konfigurationsoptionen zur Feinabstimmung Ihres OCR-Prozesses:
:path=/static-assets/ocr/content-code-examples/how-to/irontesseract-configure-irontesseract.cs
IronTesseract ocr = new IronTesseract
{
Configuration = new TesseractConfiguration
{
ReadBarCodes = false,
RenderHocr = true,
TesseractVariables = null,
WhiteListCharacters = null,
BlackListCharacters = "`ë|^",
},
MultiThreaded = false,
Language = OcrLanguage.English,
EnableTesseractConsoleMessages = true, // False as default
};
Dim ocr As New IronTesseract With {
.Configuration = New TesseractConfiguration With {
.ReadBarCodes = False,
.RenderHocr = True,
.TesseractVariables = Nothing,
.WhiteListCharacters = Nothing,
.BlackListCharacters = "`ë|^"
},
.MultiThreaded = False,
.Language = OcrLanguage.English,
.EnableTesseractConsoleMessages = True
}
Sobald es konfiguriert ist, können Sie die Tesseract-Funktionalität verwenden, um OcrInput-Objekte zu lesen. Die OcrInput-Klasse bietet flexible Methoden zum Laden verschiedener Eingabeformate:
:path=/static-assets/ocr/content-code-examples/how-to/irontesseract-read.cs
IronTesseract ocr = new IronTesseract();
using OcrInput input = new OcrInput();
input.LoadImage("attachment.png");
OcrResult result = ocr.Read(input);
string text = result.Text;
Dim ocr As New IronTesseract()
Using input As New OcrInput()
input.LoadImage("attachment.png")
Dim result As OcrResult = ocr.Read(input)
Dim text As String = result.Text
End Using
Für komplexe Szenarien können Sie die Multithreading-Funktionen nutzen, um mehrere Dokumente gleichzeitig zu verarbeiten, was die Leistung bei Stapelverarbeitungsvorgängen erheblich verbessert.
Was sind die erweiterten Tesseract-Konfigurationsvariablen?
Die IronOCR Tesseract-Schnittstelle ermöglicht die volle Kontrolle über die Tesseract-Konfigurationsvariablen über die IronOcr.TesseractConfiguration Klasse. Mit diesen erweiterten Einstellungen können Sie die OCR-Leistung für bestimmte Anwendungsfälle optimieren, z. B. Fixieren von Scans mit niedriger Qualität oder Lesen bestimmter Dokumenttypen.
Wie verwende ich die Tesseract-Konfiguration im Code?
:path=/static-assets/ocr/content-code-examples/how-to/irontesseract-tesseract-configuration.cs
using IronOcr;
using System;
IronTesseract Ocr = new IronTesseract();
Ocr.Language = OcrLanguage.English;
Ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.AutoOsd;
// Configure Tesseract Engine
Ocr.Configuration.TesseractVariables["tessedit_parallelize"] = false;
using var input = new OcrInput();
input.LoadImage("/path/file.png");
OcrResult Result = Ocr.Read(input);
Console.WriteLine(Result.Text);
Imports IronOcr
Imports System
Private Ocr As New IronTesseract()
Ocr.Language = OcrLanguage.English
Ocr.Configuration.PageSegmentationMode = TesseractPageSegmentationMode.AutoOsd
' Configure Tesseract Engine
Ocr.Configuration.TesseractVariables("tessedit_parallelize") = False
Dim input = New OcrInput()
input.LoadImage("/path/file.png")
Dim Result As OcrResult = Ocr.Read(input)
Console.WriteLine(Result.Text)
IronOCR bietet auch eine spezielle Konfiguration für verschiedene Dokumenttypen. So können Sie beispielsweise beim Lesen von Reisepässen oder bei der Verarbeitung von MICR-Schecks spezifische Vorverarbeitungsfilter und Bereichserkennung anwenden, um die Genauigkeit zu verbessern.
Beispielkonfiguration für Finanzdokumente:
:path=/static-assets/ocr/content-code-examples/how-to/iron-tesseract-6.cs
// Example: Configure for financial documents
IronTesseract ocr = new IronTesseract
{
Language = OcrLanguage.English,
Configuration = new TesseractConfiguration
{
PageSegmentationMode = TesseractPageSegmentationMode.SingleBlock,
TesseractVariables = new Dictionary<string, object>
{
["tessedit_char_whitelist"] = "0123456789.$,",
["textord_heavy_nr"] = false,
["edges_max_children_per_outline"] = 10
}
}
};
// Apply preprocessing filters for better accuracy
using OcrInput input = new OcrInput();
input.LoadPdf("financial-document.pdf");
input.Deskew();
input.EnhanceResolution(300);
OcrResult result = ocr.Read(input);
Imports IronOcr
' Example: Configure for financial documents
Dim ocr As New IronTesseract With {
.Language = OcrLanguage.English,
.Configuration = New TesseractConfiguration With {
.PageSegmentationMode = TesseractPageSegmentationMode.SingleBlock,
.TesseractVariables = New Dictionary(Of String, Object) From {
{"tessedit_char_whitelist", "0123456789.$,"},
{"textord_heavy_nr", False},
{"edges_max_children_per_outline", 10}
}
}
}
' Apply preprocessing filters for better accuracy
Using input As New OcrInput()
input.LoadPdf("financial-document.pdf")
input.Deskew()
input.EnhanceResolution(300)
Dim result As OcrResult = ocr.Read(input)
End Using
Was ist die vollständige Liste aller Tesseract-Konfigurationsvariablen?
Diese können mit IronTesseract.Configuration.TesseractVariables["key"] = value; gesetzt werden. Die Konfigurationsvariablen ermöglichen eine Feinabstimmung des OCR-Verhaltens für optimale Ergebnisse bei Ihren spezifischen Dokumenten. Eine ausführliche Anleitung zur Optimierung der OCR-Leistung finden Sie in unserem fast OCR configuration guide.
| Tesseract-Konfigurationsvariable | Default | Bedeutung |
|---|---|---|
| Anzahl der CP-Ebenen klassifizieren | 3 | Anzahl der Klassenbeschneidungsebenen |
| textord_debug_tabfind | 0 | Suche auf der Registerkarte "Debuggen" |
| textord_debug_bugs | 0 | Aktivieren Sie die Ausgabe von Fehlern in der Tab-Suche. |
| textord_testregion_left | -1 | Linke Kante des Rechtecks für Debug-Berichte |
| textord_testregion_top | -1 | Oberkante des Rechtecks für Debug-Berichte |
| textord_testregion_right | 2147483647 | Rechter Rand des Debug-Rechtecks |
| textord_testregion_bottom | 2147483647 | Unterkante des Debug-Rechtecks |
| textord_tabfind_show_partitions | 0 | Partitionsgrenzen anzeigen, warten, falls >1 |
| Devanagari-Split-Debug-Level | 0 | Debug-Level für den geteilten Shiro-Rekha-Prozess. |
| edges_max_children_per_outline | 10 | Maximale Anzahl von Kindern innerhalb einer Zeichenkontur |
| edges_max_children_layers | 5 | Maximale Anzahl verschachtelter Kindebenen innerhalb einer Charakterkontur |
| edges_children_per_grandchild | 10 | Wichtigkeitsverhältnis für Umrisse |
| edges_children_count_limit | 45 | Maximale Anzahl an Löchern im Blob |
| edges_min_nonhole | 12 | Minimale Pixelanzahl für potenzielle Charaktere im Feld |
| Kantenpfadflächenverhältnis | 40 | Max lensq/area for acceptable child outline |
| textord_fp_chop_error | 2 | Maximal zulässige Biegung von Chop-Zellen |
| textord_tabfind_show_images | 0 | Show image blobs |
| textord_skewsmooth_offset | 4 | Für den Glättungsfaktor |
| textord_skewsmooth_offset2 | 1 | Für den Glättungsfaktor |
| textord_test_x | -2147483647 | Koordinator des Testpunktes |
| textord_test_y | -2147483647 | Koordinator des Testpunktes |
| textword_min_blobs_in_row | 4 | Minimale Anzahl an Blobs vor der Gradientenzählung |
| textord_spline_minblobs | 8 | Min blobs in each spline segment |
| textord_spline_medianwin | 6 | Size of window for spline segmentation |
| textord_max_blob_overlaps | 4 | Max number of blobs a big blob can overlap |
| textord_min_xheight | 10 | Min credible pixel xheight |
| textord_lms_line_trials | 12 | Number of linew fits to do |
| oldbl_holed_losscount | 10 | Max lost before fallback line used |
| pitsync_linear_version | 6 | Use new fast algorithm |
| pitsync_fake_depth | 1 | Max advance fake generation |
| textord_tabfind_show_strokewidths | 0 | Show stroke widths |
| textord_dotmatrix_gap | 3 | Max pixel gap for broken pixed pitch |
| textord_debug_block | 0 | Block to do debug on |
| textord_pitch_range | 2 | Max range test on pitch |
| textord_words_veto_power | 5 | Rows required to outvote a veto |
| equationdetect_save_bi_image | 0 | Save input bi image |
| equationdetect_save_spt_image | 0 | Save special character image |
| equationdetect_save_seed_image | 0 | Save the seed image |
| equationdetect_save_merged_image | 0 | Save the merged image |
| poly_debug | 0 | Debug old poly |
| poly_wide_objects_better | 1 | More accurate approx on wide things |
| wordrec_display_splits | 0 | Display splits |
| textord_debug_printable | 0 | Make debug windows printable |
| textord_space_size_is_variable | 0 | If true, word delimiter spaces are assumed to have variable width, even though characters have fixed pitch. |
| textord_tabfind_show_initial_partitions | 0 | Show partition bounds |
| textord_tabfind_show_reject_blobs | 0 | Show blobs rejected as noise |
| textord_tabfind_show_columns | 0 | Show column bounds |
| textord_tabfind_show_blocks | 0 | Show final block bounds |
| textord_tabfind_find_tables | 1 | run table detection |
| Devanagari-Split-Debugimage | 0 | Whether to create a debug image for split shiro-rekha process. |
| textord_show_fixed_cuts | 0 | Draw fixed pitch cell boundaries |
| kanten_benutzen_neue_außenlinie_komplexität | 0 | Use the new outline complexity module |
| edges_debug | 0 | turn on debugging for this module |
| kanten_Kinder_fix | 0 | Remove boxy parents of char-like children |
| gapmap_debug | 0 | Say which blocks have tables |
| gapmap_nutzen_enden | 0 | Use large space at start and end of rows |
| gapmap_kein_isoliertes_quanta | 0 | Ensure gaps not less than 2quanta wide |
| textord_heavy_nr | 0 | Vigorously remove noise |
| textord_show_initial_rows | 0 | Display row accumulation |
| textord_show_parallel_rows | 0 | Display page correlated rows |
| textord_show_expanded_rows | 0 | Display rows after expanding |
| textord_show_final_rows | 0 | Display rows after final fitting |
| textord_show_final_blobs | 0 | Display blob bounds after pre-ass |
| textord_test_landscape | 0 | Tests refer to land/port |
| textord_parallel_baselines | 1 | Force parallel baselines |
| textord_straight_baselines | 0 | Force straight baselines |
| textord_alt_baselines | 1 | Use old baseline algorithm |
| textord_old_xheight | 0 | Use old xheight algorithm |
| textord_fix_xheight_bug | 1 | Use spline baseline |
| textord_fix_makerow_bug | 1 | Prevent multiple baselines |
| textord_debug_xheights | 0 | Test xheight algorithms |
| textord_biased_skewcalc | 1 | Bias skew estimates with line length |
| textord_interpolating_skew | 1 | Interpolate across gaps |
| textord_new_initial_xheight | 1 | Use test xheight mechanism |
| textord_debug_blob | 0 | Print test blob information |
| textord_really_old_xheight | 0 | Use original wiseowl xheight |
| textord_oldbl_debug | 0 | Debug old baseline generation |
| textord_debug_baselines | 0 | Debug baseline generation |
| textord_oldbl_paradef | 1 | Use para default mechanism |
| textord_oldbl_split_splines | 1 | Split stepped splines |
| textord_oldbl_merge_parts | 1 | Merge suspect partitions |
| oldbl_corrfix | 1 | Improve correlation of heights |
| oldbl_xhfix | 0 | Fix bug in modes threshold for xheights |
| textord_ocropus_mode | 0 | Make baselines for ocropus |
| textord_tabfind_only_strokewidths | 0 | Only run stroke widths |
| textord_tabfind_show_initialtabs | 0 | Show tab candidates |
| textord_tabfind_show_finaltabs | 0 | Show tab vectors |
| textord_show_tables | 0 | Show table regions |
| textord_tablefind_show_mark | 0 | Debug table marking steps in detail |
| textord_tablefind_show_stats | 0 | Show page stats used in table finding |
| textord_tablefind_recognize_tables | 0 | Enables the table recognizer for table layout and filtering. |
| textord_all_prop | 0 | All doc is proportial text |
| textord_debug_pitch_test | 0 | Debug on fixed pitch test |
| textord_disable_pitch_test | 0 | Turn off dp fixed pitch algorithm |
| textord_fast_pitch_test | 0 | Do even faster pitch algorithm |
| textord_debug_pitch_metric | 0 | Write full metric stuff |
| textord_show_row_cuts | 0 | Draw row-level cuts |
| textord_show_page_cuts | 0 | Draw page-level cuts |
| textord_pitch_cheat | 0 | Use correct answer for fixed/prop |
| textord_blockndoc_fixed | 0 | Attempt whole doc/block fixed pitch |
| textord_show_initial_words | 0 | Display separate words |
| textord_show_new_words | 0 | Display separate words |
| textord_show_fixed_words | 0 | Display forced fixed pitch words |
| textord_blocksall_fixed | 0 | Moan about prop blocks |
| textord_blocksall_prop | 0 | Moan about fixed pitch blocks |
| textord_blocksall_testing | 0 | Dump stats when moaning |
| textord_test_mode | 0 | Do current test |
| textord_pitch_rowsimilarity | 0.08 | Fraction of xheight for sameness |
| Wörter_Anfangsbuchstaben_kleingeschrieben | 0.5 | Max initial cluster size |
| Wörter_Anfangsbuchstaben_groß | 0.15 | Min initial cluster spacing |
| words_default_prop_nonspace | 0.25 | Fraction of xheight |
| words_default_fixed_space | 0.75 | Fraction of xheight |
| words_default_fixed_limit | 0.6 | Allowed size variance |
| textord_words_definite_spread | 0.3 | Non-fuzzy spacing region |
| textord_spacesize_ratiofp | 2.8 | Min ratio space/nonspace |
| textord_spacesize_ratioprop | 2 | Min ratio space/nonspace |
| textord_fpiqr_ratio | 1.5 | Pitch IQR/Gap IQR threshold |
| textord_max_pitch_iqr | 0.2 | Xh fraction noise in pitch |
| textord_fp_min_width | 0.5 | Min width of decent blobs |
| textord_unterline_offset | 0.1 | Fraction of x to ignore |
| ambigs_debug_level | 0 | Debug level for unichar ambiguities |
| Debug-Level klassifizieren | 0 | Classify debug level |
| classify_norm_method | 1 | Normalization Method ... |
| matcher_debug_level | 0 | Matcher Debug Level |
| matcher_debug_flags | 0 | Matcher Debug Flags |
| Lern-Debug-Level klassifizieren | 0 | Learning Debug Level: |
| matcher_permanent_classes_min | 1 | Min # of permanent classes |
| matcher_min_examples_for_prototyping | 3 | Reliable Config Threshold |
| matcher_sufficient_examples_ for_prototyping | 5 | Enable adaption even if the ambiguities have not been seen |
| classify_adapt_proto_threshold | 230 | Threshold for good protos during adaptive 0-255 |
| classify_adapt_feature_threshold | 230 | Threshold for good features during adaptive 0-255 |
| Schwellenwert für den Klassenbereinigungsmechanismus | 229 | Class Pruner Threshold 0-255 |
| Multiplikator für Klassenbeschneidung | 15 | Class Pruner Multiplier 0-255: |
| classify_cp_cutoff_strength | 7 | Class Pruner CutoffStrength: |
| classify_integer_matcher_multiplier | 10 | Integer Matcher Multiplier 0-255: |
| dawg_debug_level | 0 | Set to 1 for general debug info, to 2 for more details, to 3 to see all the debug messages |
| hyphen_debug_level | 0 | Debug level for hyphenated words. |
| stopper_smallword_size | 2 | Size of dict word to be treated as non-dict word |
| stopper_debug_level | 0 | Stopper debug level |
| tessedit_truncate_wordchoice_log | 10 | Max words to keep in list |
| max_permuter_attempts | 10000 | Maximum number of different character choices to consider during permutation. This limit is especially useful when user patterns are specified, since overly generic patterns can result in dawg search exploring an overly large number of options. |
| repair_unchopped_blobs | 1 | Fix blobs that aren't chopped |
| chop_debug | 0 | Chop debug |
| chop_split_length | 10000 | Split Length |
| chop_same_distance | 2 | Same distance |
| chop_min_outline_points | 6 | Min Number of Points on Outline |
| Schnittnaht-Pilzgröße | 150 | Max number of seams in seam_pile |
| Innenwinkel | -50 | Min Inside Angle Bend |
| chop_min_outline_area | 2000 | Min Outline Area |
| chop_centered_maxwidth | 90 | Width of (smaller) chopped blobs above which we don't care that a chop is not near the center. |
| chop_x_y_weight | 3 | X / Y length weight |
| wordrec_debug_level | 0 | Debug level for wordrec |
| wordrec_max_join_chunks | 4 | Max number of broken pieces to associate |
| segsearch_debug_level | 0 | SegSearch debug level |
| segsearch_max_pain_points | 2000 | Maximum number of pain points stored in the queue |
| segsearch_max_futile_classifications | 20 | Maximum number of pain point classifications per chunk that did not result in finding a better word choice. |
| sprache_modell_debug_level | 0 | Language model debug level |
| sprache_modell_ngramm_ordnung | 8 | Maximum order of the character ngram model |
| language_model_viterbi_list_ max_num_prunable | 10 | Maximum number of prunable (those for which PrunablePath() is true) entries in each viterbi list recorded in BLOB_CHOICEs |
| sprache_modell_viterbi_liste_max_grösse | 500 | Maximum size of viterbi lists recorded in BLOB_CHOICEs |
| minimale Verbindungslänge des Sprachmodells | 3 | Minimum length of compound words |
| wordrec_display_segmentations | 0 | Display Segmentations |
| tessedit_pageseg_mode | 6 | Page seg mode: 0=osd only, 1=auto+osd, 2=auto_only, 3=auto, 4=column, 5=block_vert, 6=block, 7=line, 8=word, 9=word_circle, 10=char,11=sparse_text, 12=sparse_text+osd, 13=raw_line (Values from PageSegMode enum in tesseract/publictypes.h) |
| tessedit_ocr_engine_mode | 2 | Which OCR engine(s) to run (Tesseract, LSTM, both). Defaults to loading and running the most accurate available. |
| seiteneg_devanagari_split_strategy | 0 | Whether to use the top-line splitting process for Devanagari documents while performing page-segmentation. |
| ocr_devanagari_split_strategy | 0 | Whether to use the top-line splitting process for Devanagari documents while performing ocr. |
| bidi_debug | 0 | Debug level for BiDi |
| applybox_debug | 1 | Debug level |
| applybox_page | 0 | Page number to apply boxes from |
| tessedit_bigram_debug | 0 | Amount of debug output for bigram correction. |
| Debug-Rauschentfernung | 0 | Debug reassignment of small outlines |
| noise_maxperblob | 8 | Max diacritics to apply to a blob |
| noise_maxperword | 16 | Max diacritics to apply to a word |
| debug_x_ht_level | 0 | Reestimate debug |
| qualität_min_initial_alphas_reqd | 2 | alphas in a good word |
| tessedit_tess_adaption_mode | 39 | Adaptation decision algorithm for tess |
| multilang_debug_level | 0 | Print multilang debug info. |
| absatz_debug_level | 0 | Print paragraph debug info. |
| tessedit_preserve_min_wd_len | 2 | Only preserve wds longer than this |
| crunch_rating_max | 10 | For adj length in rating per ch |
| crunch_pot_indikatoren | 1 | How many potential indicators needed |
| crunch_leave_lc_strings | 4 | Don't crunch words with long lower case strings |
| crunch_leave_uc_strings | 4 | Don't crunch words with long lower case strings |
| lange Wiederholungen | 3 | Crunch words with long repetitions |
| crunch_debug | 0 | As it says |
| fixsp_geraeuschfrei_limit | 1 | How many non-noise blbs either side? |
| fixsp_done_mode | 1 | What constitues done for spacing |
| debug_fix_space_level | 0 | Contextual fixspace debug |
| x_ht_akzeptanz_toleranz | 8 | Max allowed deviation of blob top outside of font data |
| x_ht_min_change | 8 | Min change in xht before actually trying it |
| superscript_debug | 0 | Debug level for sub & superscript fixer |
| jpg-Qualität | 85 | Set JPEG quality level |
| benutzerdefinierte DPI | 0 | Specify DPI for input image |
| min_characters_to_try | 50 | Specify minimum characters to try during OSD |
| suspect_level | 99 | Suspect marker level |
| suspect_short_words | 2 | Don't suspect dict wds longer than this |
| tessedit_reject_mode | 0 | Rejection algorithm |
| tessedit_image_border | 2 | Rej blbs near image edge limit |
| min_sane_x_ht_pixels | 8 | Reject any x-ht lt or eq than this |
| tessedit_page_number | -1 | -1 -> All pages, else specific page to process |
| tessedit_parallelisieren | 1 | Run in parallel where possible |
| lstm_choice_mode | 2 | Allows to include alternative symbols choices in the hOCR output. Valid input values are 0, 1 and 2. 0 is the default value. With 1 the alternative symbol choices per timestep are included. With 2 alternative symbol choices are extracted from the CTC process instead of the lattice. The choices are mapped per character. |
| lstm_choice_iterations | 5 | Sets the number of cascading iterations for the Beamsearch in lstm_choice_mode. Note that lstm_choice_mode must be set to a value greater than 0 to produce results. |
| tosp_debug_level | 0 | Debug data |
| tosp_genug_space_samples_für_median | 3 | or should we use mean |
| tosp_redo_kern_limit | 10 | No.samples reqd to reestimate for row |
| tosp_few_samples | 40 | No.gaps reqd with 1 large gap to treat as a table |
| tosp_short_row | 20 | No.gaps reqd with few cert spaces to use certs |
| tosp_sanity_method | 1 | How to avoid being silly |
| textord_max_noise_size | 7 | Pixel size of noise |
| textord_baseline_debug | 0 | Baseline debug level |
| textord_noise_sizefraction | 10 | Fraction of size for maxima |
| textord_noise_translimit | 16 | Transitions for normal blob |
| textord_noise_sncount | 1 | super norm blobs to save row |
| Verwendung von Ambiguitäten zur Anpassung | 0 | Use ambigs for deciding whether to adapt to a character |
| priorisieren_Abteilung | 0 | Prioritize blob division over chopping |
| Klassifizierung aktivieren Lernen | 1 | Enable adaptive classifier |
| tess_cn_matching | 0 | Character Normalized Matching |
| tess_bn_matching | 0 | Baseline Normalized Matching |
| klassifizieren_adaptiven_Abgleich aktivieren | 1 | Enable adaptive classifier |
| classify_use_pre_adapted_templates | 0 | Use pre-adapted classifier templates |
| klassifizieren_speichern_angepasste_Vorlagen | 0 | Save adapted templates to a file |
| klassifizieren_adaptiven_Debugger aktivieren | 0 | Enable match debugger |
| nichtlineare Norm klassifizieren | 0 | Non-linear stroke-density normalization |
| disable_character_fragments | 1 | Do not include character fragments in the results of the classifier |
| klassifizieren_debug_character_fragments | 0 | Bring up graphical debugging windows for fragments training |
| matcher_debug_separate_windows | 0 | Use two different windows for debugging the matching: One for the protos and one for the features. |
| classify_bln_numeric_mode | 0 | Assume the input is numbers [0-9]. |
| load_system_dawg | 1 | Load system word dawg. |
| load_freq_dawg | 1 | Load frequent word dawg. |
| load_unambig_dawg | 1 | Load unambiguous word dawg. |
| load_punc_dawg | 1 | Load dawg with punctuation patterns. |
| load_number_dawg | 1 | Load dawg with number patterns. |
| load_bigram_dawg | 1 | Load dawg with special word bigrams. |
| benutze_nur_erste_uft8_schritt | 0 | Use only the first UTF8 step of the given string when computing log probabilities. |
| stopper_no_acceptable_choices | 0 | Make AcceptableChoice() always return false. Useful when there is a need to explore all segmentations |
| segment_nonalphabetisch_script | 0 | Don't use any alphabetic-specific tricks. Set to true in the traineddata config file for scripts that are cursive or inherently fixed-pitch |
| save_doc_words | 0 | Save Document Words |
| fragmente_in_Matrix_zusammenführen | 1 | Merge the fragments in the ratings matrix and delete them after merging |
| wordrec_enable_assoc | 1 | Associator Enable |
| erzwingt_Wortassoziation | 0 | force associator to run regardless of what enable_assoc is. This is used for CJK where component grouping is necessary. |
| chop_enable | 1 | Chop enable |
| chop_vertical_creep | 0 | Vertical creep |
| chop_new_seam_pile | 1 | Use new seam_pile |
| assume_fixed_pitch_char_segment | 0 | include fixed-pitch heuristics in char segmentation |
| wordrec_skip_no_truth_words | 0 | Only run OCR for words that had truth recorded in BlamerBundle |
| wordrec_debug_blamer | 0 | Print blamer debug messages |
| wordrec_run_blamer | 0 | Try to set the blame for errors |
| save_alt_choices | 1 | Save alternative paths found during chopping and segmentation search |
| language_model_ngram_on | 0 | Turn on/off the use of character ngram model |
| language_model_ngram_use_ only_first_uft8_step | 0 | Use only the first UTF8 step of the given string when computing log probabilities. |
| language_model_ngram_space_ delimited_language | 1 | Words are delimited by space |
| sprachmodell_nutze_sigmoide_gewissheit | 0 | Use sigmoidal score for certainty |
| tessedit_resegment_aus_boxen | 0 | Take segmentation and labeling from box file |
| tessedit_resegment_aus_line_boxes | 0 | Conversion of word/line box file to char box file |
| tessedit_train_from_boxes | 0 | Generate training data from boxed chars |
| tessedit_boxen_aus_boxen_herstellen | 0 | Generate more boxes from boxed chars |
| tessedit_train_line_recognizer | 0 | Break input into lines and remap boxes if present |
| tessedit_dump_pageseg_images | 0 | Dump intermediate images made during page segmentation |
| tessedit_do_invert | 1 | Try inverting the image in LSTMRecognizeWord |
| tessedit_ambigs_schulung | 0 | Perform training for ambiguities |
| tessedit_adaption_debug | 0 | Generate and print debug information for adaption |
| applybox_learn_chars_and_char_frags_mode | 0 | Learn both character fragments (as is done in the special low exposure mode) as well as unfragmented characters. |
| applybox_learn_ngrams_mode | 0 | Each bounding box is assumed to contain ngrams. Only learn the ngrams whose outlines overlap horizontally. |
| tessedit_anzeigen_auswuerfe | 0 | Draw output words |
| tessedit_dump_choices | 0 | Dump char choices |
| tessedit_timing_debug | 0 | Print timing stats |
| tessedit_fix_fuzzy_spaces | 1 | Try to improve fuzzy spaces |
| tessedit_unrej_any_wd | 0 | Don't bother with word plausibility |
| tessedit_fix_hyphens | 1 | Crunch double hyphens? |
| tessedit_aktivieren_doc_dict | 1 | Add words to the document dictionary |
| tessedit_debug_fonts | 0 | Output font info per char |
| tessedit_debug_block_rejection | 0 | Block and Row stats |
| tessedit_enable_bigram_correction | 1 | Enable correction based on the word bigram dictionary. |
| tessedit_enable_dict_correction | 0 | Enable single word correction based on the dictionary. |
| Rauschunterdrückung aktivieren | 1 | Remove and conditionally reassign small outlines when they confuse layout analysis, determining diacritics vs noise |
| tessedit_minimal_rej_pass1 | 0 | Do minimal rejection on pass 1 output |
| tessedit_test_adaptation | 0 | Test adaption criteria |
| test_pt | 0 | Test for point |
| absatztextbasiert | 1 | Run paragraph detection on the post-text-recognition (more accurate) |
| lstm_gebrauch_matrix | 1 | Use ratings matrix/beam search with lstm |
| tessedit_gute_Qualität_unrej | 1 | Reduce rejection on good docs |
| tessedit_verwendet_abgewiesene_Räume | 1 | Reject spaces? |
| tessedit_preserve_blk_rej_perfect_wds | 1 | Only rej partially rejected words in block rejection |
| tessedit_preserve_row_rej_perfect_wds | 1 | Only rej partially rejected words in row rejection |
| tessedit_dont_blkrej_good_wds | 0 | Use word segmentation quality metric |
| tessedit_dont_rowrej_good_wds | 0 | Use word segmentation quality metric |
| tessedit_row_rej_good_docs | 1 | Apply row rejection to good docs |
| tessedit_reject_bad_qual_wds | 1 | Reject all bad quality wds |
| tessedit_debug_doc_rejection | 0 | Page stats |
| tessedit_debug_quality_metrics | 0 | Output data to debug file |
| bland_unrej | 0 | unrej potential with no checks |
| unlv_tilde_crunching | 0 | Mark v.bad words for tilde crunch |
| hocr_font_info | 0 | Add font info to hocr output |
| hocr_char_boxes | 0 | Add coordinates for each character to hocr output |
| crunch_early_merge_tess_fails | 1 | Before word crunch? |
| crunch_early_convert_bad_unlv_chs | 0 | Take out ~^ early? |
| crunch_terrible_garbage | 1 | As it says |
| crunch_leave_ok_strings | 1 | Don't touch sensible strings |
| crunch_accept_ok | 1 | Use acceptability in okstring |
| crunch_leave_accept_strings | 0 | Don't pot crunch sensible strings |
| crunch_include_numerals | 0 | Fiddle alpha figures |
| tessedit_prefer_joined_punct | 0 | Reward punctuation joins |
| tessedit_write_block_separators | 0 | Write block separators in output |
| tessedit_write_rep_codes | 0 | Write repetition char code |
| tessedit_write_unlv | 0 | Write .unlv output file |
| tessedit_create_txt | 0 | Write .txt output file |
| tessedit_create_hocr | 0 | Write .html hOCR output file |
| tessedit_create_alto | 0 | Write .xml ALTO file |
| tessedit_create_lstmbox | 0 | Write .box file for LSTM training |
| tessedit_create_tsv | 0 | Write .tsv output file |
| tessedit_create_wordstrbox | 0 | Write WordStr format .box output file |
| tessedit_create_pdf | 0 | Write .pdf output file |
| textonly_pdf | 0 | Create PDF with only one invisible text layer |
| suspect_constrain_1Il | 0 | UNLV keep 1Il chars rejected |
| tessedit_minimal_rejection | 0 | Only reject tess failures |
| tessedit_zero_rejection | 0 | Don't reject ANYTHING |
| tessedit_word_for_word | 0 | Make output have exactly one word per WERD |
| tessedit_zero_kelvin_rejection | 0 | Don't reject ANYTHING AT ALL |
| tessedit_rejection_debug | 0 | Adaption debug |
| tessedit_flip_0O | 1 | Contextual 0O O0 flips |
| rej_trust_doc_dawg | 0 | Use DOC dawg in 11l conf. detector |
| rej_1Il_verwendung_dict_word | 0 | Use dictword test |
| rej_1Il_trust_permuter_type | 1 | Don't double check |
| rej_use_tess_accepted | 1 | Individual rejection control |
| rej_use_tess_blanks | 1 | Individual rejection control |
| rej_use_good_perm | 1 | Individual rejection control |
| rej_benutzen_sensibel_wd | 0 | Extend permuter check |
| rej_alphas_in_number_perm | 0 | Extend permuter check |
| tessedit_create_boxfile | 0 | Output text with boxes |
| tessedit_write_images | 0 | Capture the image from the IPE |
| interaktiver Anzeigemodus | 0 | Run interactively? |
| tessedit_überschreibender_permuter | 1 | According to dict_word |
| tessedit_verwendet_primäre_Parameter_Modell | 0 | In multilingual mode use params model of the primary language |
| textord_tabfind_show_vlines | 0 | Debug line finding |
| textord_verwendung_cjk_fp_model | 0 | Use CJK fixed pitch model |
| poly_allow_detailed_fx | 0 | Allow feature extractors to see the original outline |
| tessedit_init_config_only | 0 | Only initialize with the config file. Useful if the instance is not going to be used for OCR but say only for layout analysis. |
| textord_equation_detect | 0 | Turn on equation detector |
| textord_tabfind_vertical_text | 1 | Enable vertical detection |
| textord_tabfind_force_vertical_text | 0 | Force using vertical text page mode |
| Zwischenwortabstände beibehalten | 0 | Preserve multiple interword spaces |
| pageseg_apply_music_mask | 1 | Detect music staff and remove intersecting components |
| textord_single_height_mode | 0 | Script has no xheight, so use a single mode |
| tosp_old_to_method | 0 | Space stats use prechopping? |
| tosp_old_to_constrain_sp_kn | 0 | Constrain relative values of inter and intra-word gaps for old_to_method. |
| tosp_only_use_prop_rows | 1 | Block stats to use fixed pitch rows? |
| tosp_force_wordbreak_on_punct | 0 | Force word breaks on punct to break long lines in non-space delimited langs |
| tosp_nutzen_vor_hacken | 0 | Space stats use prechopping? |
| tosp_alt_zu_bug_fix | 0 | Fix suspected bug in old code |
| tosp_block_use_cert_spaces | 1 | Only stat OBVIOUS spaces |
| tosp_row_use_cert_spaces | 1 | Only stat OBVIOUS spaces |
| tosp_narrow_blobs_not_cert | 1 | Only stat OBVIOUS spaces |
| tosp_row_use_cert_spaces1 | 1 | Only stat OBVIOUS spaces |
| tosp_wiederherstellung_isolierte_reihen_statistiken | 1 | Use row alone when inadequate cert spaces |
| tosp_nur_kleine_lücken_für_kern | 0 | Better guess |
| tosp_alle_flips_fuzzy | 0 | Pass ANY flip to context? |
| tosp_fuzzy_limit_all | 1 | Don't restrict kn->sp fuzzy limit to tables |
| textord_no_rejects | 0 | Don't remove noise blobs |
| textord_show_blobs | 0 | Display unsorted blobs |
| textord_show_boxes | 0 | Display unsorted blobs |
| textord_noise_rejwords | 1 | Reject noise-like words |
| textord_noise_rejrows | 1 | Reject noise-like rows |
| textord_noise_debug | 0 | Debug row garbage detector |
| classify_learn_debug_str | Class str to debug learning | |
| Benutzerwortdatei | A filename of user-provided words. | |
| Benutzerwortsuffix | A suffix of user-provided words located in tessdata. | |
| Benutzermusterdatei | A filename of user-provided patterns. | |
| Benutzermustersuffix | A suffix of user-provided patterns located in tessdata. | |
| Ausgabedatei für Mehrdeutigkeiten | Output file for ambiguities found in the dictionary | |
| Wort zum Debuggen | Word for which stopper debug information should be printed to stdout | |
| tessedit_char_blacklist | Blacklist of chars not to recognize | |
| tessedit_char_whitelist | Whitelist of chars to recognize | |
| tessedit_char_unblacklist | List of chars to override tessedit_char_blacklist | |
| tessedit_write_params_to_file | Write all parameters to the given file. | |
| applybox_exposure_pattern | .exp | Exposure value follows this pattern in the image filename. The name of the image files are expected to be in the form [lang].[fontname].exp [num].tif |
| chs_leading_punct('`" | Leitsatz | |
| chs_trailing_punct1 | ).,;:?! | 1st Trailing punctuation |
| chs_trailing_punct2)'`" | 2nd Trailing punctuation | |
| Umrisse_ungerade | %| | Nicht standardmäßige Anzahl von Umrissen |
| outlines_2ij!?%":; | Nicht standardmäßige Anzahl von Umrissen | |
| numerische_Zeichensetzung | ., | Punct. chs expected WITHIN numbers |
| unerkanntes_zeichen | | | Output char for unidentified blobs |
| ok_repeated_ch_non_alphanum_wds | -?*= | Allow NN to unrej |
| Konfliktgruppe_I_l_1 | Il1 [] | Il1 conflict set |
| Dateityp | .tif | Filename extension |
| tessedit_load_sublangs | List of languages to load with this one | |
| Seitentrennzeichen | Page separator (default is form feed control character) | |
| Zeichennormbereich klassifizieren | 0.2 | Character Normalization Range ... |
| klassifizieren_maximales_Bewertungsverhältnis | 1.5 | Veto ratio between classifier ratings |
| classify_max_certainty_margin | 5.5 | Veto difference between classifier certainties |
| matcher_good_threshold | 0.125 | Good Match (0-1) |
| matcher_zuverlässiges_adaptives_ergebnis | 0 | Great Match (0-1) |
| matcher_perfect_threshold | 0.02 | Perfect Match (0-1) |
| matcher_bad_match_pad | 0.15 | Bad Match Pad (0-1) |
| Matcher-Bewertungsmarge | 0.1 | New template margin (0-1) |
| matcher_avg_noise_size | 12 | Avg. noise blob length |
| matcher_clustering_max_angle_delta | 0.015 | Maximum angle delta for prototype clustering |
| Strafe für unpassende Schrottteile | 0 | Penalty to apply when a non-alnum is vertically out of its expected textline position |
| Bewertungsskala | 1.5 | Rating scaling factor |
| Gewissheitsskala | 20 | Certainty scaling factor |
| tessedit_class_miss_scale | 0.00390625 | Scale factor for features not used |
| klassifizieren_angepasster_Pruning-Faktor | 2.5 | Prune poor adapted results this much worse than best result |
| klassifizieren_angepasster_Beschneidungsschwellenwert | -1 | Threshold at which klassifizieren_angepasster_Pruning-Faktor starts |
| classify_character_fragments_ garbage_certainty_threshold | -3 | Exclude fragments that do not look like whole characters from training and adaption |
| speckle_large_max_size | 0.3 | Max large speckle size |
| Speckle-Bewertungsstrafe | 10 | Penalty to add to worst rating for noise |
| xheight_penalty_subscripts | 0.125 | Score penalty (0.1 = 10%) added if there are subscripts or superscripts in a word, but it is otherwise OK. |
| xheight_penalty_inconsistent | 0.25 | Score penalty (0.1 = 10%) added if an xheight is inconsistent. |
| segment_penalty_dict_frequent_word | 1 | Score multiplier for word matches which have good case and are frequent in the given language (lower is better). |
| segment_penalty_dict_case_ok | 1.1 | Score multiplier for word matches that have good case (lower is better). |
| segment_penalty_dict_case_bad | 1.3125 | Default score multiplier for word matches, which may have case issues (lower is better). |
| segment_penalty_dict_nonword | 1.25 | Score multiplier for glyph fragment segmentations which do not match a dictionary word (lower is better). |
| Gewissheitsskala | 20 | Certainty scaling factor |
| stopper_nondict_certainty_base | -2.5 | Certainty threshold for non-dict words |
| stopper_phase2_certainty_rejection_offset | 1 | Reject certainty offset |
| stopper_certainty_per_char | -0.5 | Certainty to add for each dict char above small word size. |
| stopper_allowable_character_badness | 3 | Max certaintly variation allowed in a word (in sigma) |
| doc_dict_pending_threshold | 0 | Worst certainty for using pending dictionary |
| doc_dict_certainty_threshold | -2.25 | Worst certainty for words that can be inserted into the document dictionary |
| tessedit_gewissheit_schwelle | -2.25 | Good blob limit |
| chop_split_dist_knob | 0.5 | Split length adjustment |
| chop_overlap_knob | 0.9 | Split overlap adjustment |
| chop_center_knob | 0.15 | Split center adjustment |
| chop_sharpness_knob | 0.06 | Split sharpness adjustment |
| chop_width_change_knob | 5 | Width change adjustment |
| chop_ok_split | 100 | OK split limit |
| chop_good_split | 50 | Good split limit |
| segsearch_max_char_wh_ratio | 2 | Maximales Zeichenbreiten-Höhen-Verhältnis |
Um optimale Ergebnisse zu erzielen, wird empfohlen, vor der Anwendung von OCR die Bildvorverarbeitungsfilter von IronOCR zu verwenden. Diese Filter können die Genauigkeit erheblich verbessern, insbesondere bei der Arbeit mit Scans niedriger Qualität oder komplexen Dokumenten wie Tabellen.
Häufig gestellte Fragen
Wie konfiguriere ich IronTesseract für OCR in C#?
Um IronTesseract zu konfigurieren, erstellen Sie eine IronTesseract-Instanz und legen Eigenschaften wie Sprache und Konfiguration fest. Sie können die OCR-Sprache (aus 125 unterstützten Sprachen) angeben, das Lesen von Barcodes aktivieren, die durchsuchbare PDF-Ausgabe konfigurieren und eine Whitelist für Zeichen festlegen. Zum Beispiel: var tesseract = new IronOcr.IronTesseract { Language = IronOcr.OcrLanguage.English, Configuration = new IronOcr.TesseractConfiguration { ReadBarCodes = false, RenderSearchablePdf = true } };
Welche Eingabeformate werden von IronTesseract unterstützt?
IronTesseract akzeptiert verschiedene Eingabeformate über die Klasse OcrInput. Sie können Bilder (PNG, JPG, etc.), PDF-Dateien und gescannte Dokumente verarbeiten. Die Klasse OcrInput bietet flexible Methoden zum Laden dieser verschiedenen Formate, so dass die OCR für praktisch jedes Dokument, das Text enthält, problemlos durchgeführt werden kann.
Kann ich mit IronTesseract BarCodes zusammen mit Text lesen?
Ja, IronTesseract verfügt über erweiterte Funktionen zum Lesen von Barcodes. Sie können die Barcode-Erkennung aktivieren, indem Sie ReadBarCodes = true in der TesseractConfiguration einstellen. Damit können Sie in einem einzigen OCR-Vorgang sowohl Text- als auch Barcodedaten aus demselben Dokument extrahieren.
Wie erstelle ich durchsuchbare PDFs aus gescannten Dokumenten?
IronTesseract kann gescannte Dokumente und Bilder in durchsuchbare PDFs umwandeln, indem in der TesseractConfiguration RenderSearchablePdf = true gesetzt wird. Dadurch werden PDF-Dateien erzeugt, in denen der Text auswählbar und durchsuchbar ist, während das Aussehen des Originaldokuments erhalten bleibt.
Welche Sprachen werden von IronTesseract für OCR unterstützt?
IronTesseract unterstützt 125 internationale Sprachen für die Texterkennung. Sie können die Sprache festlegen, indem Sie die Spracheigenschaft Ihrer IronTesseract-Instanz einstellen, z. B. IronOcr.OcrLanguage.English, Spanisch, Chinesisch, Arabisch und viele andere.
Kann ich einschränken, welche Zeichen bei der OCR erkannt werden?
Ja, IronTesseract erlaubt das Whitelisting und Blacklisting von Zeichen über die Eigenschaft WhiteListCharacters in TesseractConfiguration. Diese Funktion trägt zur Verbesserung der Genauigkeit bei, wenn Sie den erwarteten Zeichensatz kennen, z. B. wenn Sie die Erkennung auf alphanumerische Zeichen beschränken.
Wie führe ich OCR für mehrere Dokumente gleichzeitig durch?
IronTesseract unterstützt Multithreading-Funktionen für die Stapelverarbeitung. Sie können die parallele Verarbeitung nutzen, um mehrere Dokumente gleichzeitig zu OCR zu verarbeiten, was die Leistung bei der Verarbeitung großer Mengen von Bildern oder PDFs erheblich verbessert.
Welche Version von Tesseract wird von IronOCR verwendet?
IronOCR verwendet eine angepasste und optimierte Version von Tesseract 5, bekannt als Iron Tesseract. Diese optimierte Engine bietet im Vergleich zu Standard-Tesseract-Implementierungen eine verbesserte Genauigkeit und Leistung, wobei die Kompatibilität mit .NET-Anwendungen erhalten bleibt.
Wie kann IronOCR die Datenqualität verbessern?
IronOCR verbessert die Datenqualität durch seine fortschrittlichen Erkennungsalgorithmen und Bildkorrekturfunktionen, die sicherstellen, dass der Textextraktionsprozess sowohl zuverlässig als auch genau ist.
Gibt es eine kostenlose Testversion von IronOCR?
Ja, Iron Software bietet eine kostenlose Testversion von IronOCR an, die es den Benutzern ermöglicht, die Funktionen und Fähigkeiten zu testen, bevor sie eine Kaufentscheidung treffen.

