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https://github.com/tesseract-ocr/tesseract.git
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23f1d16037
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@760 d0cd1f9f-072b-0410-8dd7-cf729c803f20
2206 lines
73 KiB
C++
2206 lines
73 KiB
C++
/**********************************************************************
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* File: baseapi.cpp
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* Description: Simple API for calling tesseract.
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* Author: Ray Smith
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* Created: Fri Oct 06 15:35:01 PDT 2006
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*
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* (C) Copyright 2006, Google Inc.
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** Licensed under the Apache License, Version 2.0 (the "License");
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** you may not use this file except in compliance with the License.
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** You may obtain a copy of the License at
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** http://www.apache.org/licenses/LICENSE-2.0
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** Unless required by applicable law or agreed to in writing, software
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** distributed under the License is distributed on an "AS IS" BASIS,
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** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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** See the License for the specific language governing permissions and
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** limitations under the License.
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*
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**********************************************************************/
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// Include automatically generated configuration file if running autoconf.
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#ifdef HAVE_CONFIG_H
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#include "config_auto.h"
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#endif
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#include "allheaders.h"
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#ifdef USING_GETTEXT
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#include <libintl.h>
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#include <locale.h>
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#define _(x) gettext(x)
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#else
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#define _(x) (x)
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#endif
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#include "baseapi.h"
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#include "resultiterator.h"
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#include "mutableiterator.h"
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#include "thresholder.h"
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#include "tesseractclass.h"
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#include "pageres.h"
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#include "paragraphs.h"
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#include "tessvars.h"
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#include "control.h"
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#include "pgedit.h"
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#include "paramsd.h"
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#include "output.h"
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#include "globals.h"
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#include "edgblob.h"
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#include "equationdetect.h"
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#include "tessbox.h"
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#include "imgs.h"
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#include "imgtiff.h"
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#include "makerow.h"
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#include "permute.h"
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#include "otsuthr.h"
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#include "osdetect.h"
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#include "params.h"
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#include "strngs.h"
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#ifdef _WIN32
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#include <windows.h>
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#include <stdlib.h>
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#else
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#include <glob.h>
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#include <libgen.h>
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#include <string.h>
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#endif
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#if defined(_WIN32) && !defined(VERSION)
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#include "version.h"
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#endif
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namespace tesseract {
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/** Minimum sensible image size to be worth running tesseract. */
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const int kMinRectSize = 10;
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/** Character returned when Tesseract couldn't recognize as anything. */
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const char kTesseractReject = '~';
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/** Character used by UNLV error counter as a reject. */
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const char kUNLVReject = '~';
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/** Character used by UNLV as a suspect marker. */
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const char kUNLVSuspect = '^';
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/**
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* Filename used for input image file, from which to derive a name to search
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* for a possible UNLV zone file, if none is specified by SetInputName.
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*/
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const char* kInputFile = "noname.tif";
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/** Temp file used for storing current parameters before applying retry values. */
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const char* kOldVarsFile = "failed_vars.txt";
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/** Max string length of an int. */
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const int kMaxIntSize = 22;
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/**
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* Minimum believable resolution. Used as a default if there is no other
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* information, as it is safer to under-estimate than over-estimate.
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*/
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const int kMinCredibleResolution = 70;
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/** Maximum believable resolution. */
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const int kMaxCredibleResolution = 2400;
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TessBaseAPI::TessBaseAPI()
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: tesseract_(NULL),
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osd_tesseract_(NULL),
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equ_detect_(NULL),
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// Thresholder is initialized to NULL here, but will be set before use by:
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// A constructor of a derived API, SetThresholder(), or
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// created implicitly when used in InternalSetImage.
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thresholder_(NULL),
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paragraph_models_(NULL),
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block_list_(NULL),
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page_res_(NULL),
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input_file_(NULL),
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output_file_(NULL),
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datapath_(NULL),
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language_(NULL),
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last_oem_requested_(OEM_DEFAULT),
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recognition_done_(false),
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truth_cb_(NULL),
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rect_left_(0), rect_top_(0), rect_width_(0), rect_height_(0),
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image_width_(0), image_height_(0) {
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}
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TessBaseAPI::~TessBaseAPI() {
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End();
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}
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/**
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* Returns the version identifier as a static string. Do not delete.
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*/
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const char* TessBaseAPI::Version() {
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return VERSION;
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}
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/**
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* Set the name of the input file. Needed only for training and
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* loading a UNLV zone file.
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*/
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void TessBaseAPI::SetInputName(const char* name) {
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if (input_file_ == NULL)
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input_file_ = new STRING(name);
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else
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*input_file_ = name;
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}
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/** Set the name of the output files. Needed only for debugging. */
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void TessBaseAPI::SetOutputName(const char* name) {
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if (output_file_ == NULL)
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output_file_ = new STRING(name);
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else
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*output_file_ = name;
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}
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bool TessBaseAPI::SetVariable(const char* name, const char* value) {
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if (tesseract_ == NULL) tesseract_ = new Tesseract;
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return ParamUtils::SetParam(name, value, SET_PARAM_CONSTRAINT_NON_INIT_ONLY,
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tesseract_->params());
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}
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bool TessBaseAPI::SetDebugVariable(const char* name, const char* value) {
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if (tesseract_ == NULL) tesseract_ = new Tesseract;
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return ParamUtils::SetParam(name, value, SET_PARAM_CONSTRAINT_DEBUG_ONLY,
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tesseract_->params());
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}
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bool TessBaseAPI::GetIntVariable(const char *name, int *value) const {
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IntParam *p = ParamUtils::FindParam<IntParam>(
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name, GlobalParams()->int_params, tesseract_->params()->int_params);
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if (p == NULL) return false;
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*value = (inT32)(*p);
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return true;
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}
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bool TessBaseAPI::GetBoolVariable(const char *name, bool *value) const {
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BoolParam *p = ParamUtils::FindParam<BoolParam>(
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name, GlobalParams()->bool_params, tesseract_->params()->bool_params);
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if (p == NULL) return false;
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*value = (BOOL8)(*p);
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return true;
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}
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const char *TessBaseAPI::GetStringVariable(const char *name) const {
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StringParam *p = ParamUtils::FindParam<StringParam>(
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name, GlobalParams()->string_params, tesseract_->params()->string_params);
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return (p != NULL) ? p->string() : NULL;
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}
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bool TessBaseAPI::GetDoubleVariable(const char *name, double *value) const {
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DoubleParam *p = ParamUtils::FindParam<DoubleParam>(
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name, GlobalParams()->double_params, tesseract_->params()->double_params);
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if (p == NULL) return false;
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*value = (double)(*p);
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return true;
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}
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/** Get value of named variable as a string, if it exists. */
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bool TessBaseAPI::GetVariableAsString(const char *name, STRING *val) {
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return ParamUtils::GetParamAsString(name, tesseract_->params(), val);
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}
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/** Print Tesseract parameters to the given file. */
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void TessBaseAPI::PrintVariables(FILE *fp) const {
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ParamUtils::PrintParams(fp, tesseract_->params());
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}
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/**
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* The datapath must be the name of the data directory (no ending /) or
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* some other file in which the data directory resides (for instance argv[0].)
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* The language is (usually) an ISO 639-3 string or NULL will default to eng.
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* If numeric_mode is true, then only digits and Roman numerals will
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* be returned.
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* @return: 0 on success and -1 on initialization failure.
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*/
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int TessBaseAPI::Init(const char* datapath, const char* language,
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OcrEngineMode oem, char **configs, int configs_size,
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const GenericVector<STRING> *vars_vec,
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const GenericVector<STRING> *vars_values,
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bool set_only_non_debug_params) {
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// Default language is "eng".
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if (language == NULL) language = "eng";
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// If the datapath, OcrEngineMode or the language have changed - start again.
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// Note that the language_ field stores the last requested language that was
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// initialized successfully, while tesseract_->lang stores the language
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// actually used. They differ only if the requested language was NULL, in
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// which case tesseract_->lang is set to the Tesseract default ("eng").
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if (tesseract_ != NULL &&
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(datapath_ == NULL || language_ == NULL ||
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*datapath_ != datapath || last_oem_requested_ != oem ||
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(*language_ != language && tesseract_->lang != language))) {
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delete tesseract_;
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tesseract_ = NULL;
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}
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bool reset_classifier = true;
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if (tesseract_ == NULL) {
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reset_classifier = false;
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tesseract_ = new Tesseract;
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if (tesseract_->init_tesseract(
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datapath, output_file_ != NULL ? output_file_->string() : NULL,
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language, oem, configs, configs_size, vars_vec, vars_values,
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set_only_non_debug_params) != 0) {
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return -1;
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}
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}
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// Update datapath and language requested for the last valid initialization.
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if (datapath_ == NULL)
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datapath_ = new STRING(datapath);
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else
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*datapath_ = datapath;
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if (language_ == NULL)
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language_ = new STRING(language);
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else
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*language_ = language;
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last_oem_requested_ = oem;
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// For same language and datapath, just reset the adaptive classifier.
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if (reset_classifier) tesseract_->ResetAdaptiveClassifier();
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return 0;
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}
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/**
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* Returns the languages string used in the last valid initialization.
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* If the last initialization specified "deu+hin" then that will be
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* returned. If hin loaded eng automatically as well, then that will
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* not be included in this list. To find the languages actually
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* loaded use GetLoadedLanguagesAsVector.
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* The returned string should NOT be deleted.
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*/
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const char* TessBaseAPI::GetInitLanguagesAsString() const {
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return (language_ == NULL || language_->string() == NULL) ?
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"" : language_->string();
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}
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/**
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* Returns the loaded languages in the vector of STRINGs.
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* Includes all languages loaded by the last Init, including those loaded
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* as dependencies of other loaded languages.
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*/
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void TessBaseAPI::GetLoadedLanguagesAsVector(
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GenericVector<STRING>* langs) const {
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langs->clear();
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if (tesseract_ != NULL) {
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langs->push_back(tesseract_->lang);
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int num_subs = tesseract_->num_sub_langs();
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for (int i = 0; i < num_subs; ++i)
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langs->push_back(tesseract_->get_sub_lang(i)->lang);
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}
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}
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/**
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* Returns the available languages in the vector of STRINGs.
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*/
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void TessBaseAPI::GetAvailableLanguagesAsVector(
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GenericVector<STRING>* langs) const {
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langs->clear();
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if (tesseract_ != NULL) {
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STRING pattern = tesseract_->datadir + "/*." + kTrainedDataSuffix;
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#ifdef _WIN32
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char fname[_MAX_FNAME];
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WIN32_FIND_DATA data;
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BOOL result = TRUE;
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HANDLE handle = FindFirstFile(pattern.string(), &data);
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if (handle != INVALID_HANDLE_VALUE) {
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for (; result; result = FindNextFile(handle, &data)) {
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_splitpath(data.cFileName, NULL, NULL, fname, NULL);
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langs->push_back(STRING(fname));
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}
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FindClose(handle);
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}
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#else
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glob_t pglob;
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char **paths;
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char *path, *dot;
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if (glob(pattern.string(), 0, NULL, &pglob) == 0) {
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for (paths = pglob.gl_pathv; *paths != NULL; paths++) {
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path = basename(*paths);
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if ((dot = strchr(path, '.'))) {
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*dot = '\0';
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langs->push_back(STRING(path));
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}
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}
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globfree(&pglob);
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}
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#endif
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}
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}
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/**
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* Init only the lang model component of Tesseract. The only functions
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* that work after this init are SetVariable and IsValidWord.
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* WARNING: temporary! This function will be removed from here and placed
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* in a separate API at some future time.
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*/
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int TessBaseAPI::InitLangMod(const char* datapath, const char* language) {
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if (tesseract_ == NULL)
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tesseract_ = new Tesseract;
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return tesseract_->init_tesseract_lm(datapath, NULL, language);
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}
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/**
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* Init only for page layout analysis. Use only for calls to SetImage and
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* AnalysePage. Calls that attempt recognition will generate an error.
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*/
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void TessBaseAPI::InitForAnalysePage() {
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if (tesseract_ == NULL) {
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tesseract_ = new Tesseract;
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tesseract_->InitAdaptiveClassifier(false);
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}
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}
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/**
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* Read a "config" file containing a set of parameter name, value pairs.
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* Searches the standard places: tessdata/configs, tessdata/tessconfigs
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* and also accepts a relative or absolute path name.
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*/
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void TessBaseAPI::ReadConfigFile(const char* filename) {
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tesseract_->read_config_file(filename, SET_PARAM_CONSTRAINT_NON_INIT_ONLY);
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}
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/** Same as above, but only set debug params from the given config file. */
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void TessBaseAPI::ReadDebugConfigFile(const char* filename) {
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tesseract_->read_config_file(filename, SET_PARAM_CONSTRAINT_DEBUG_ONLY);
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}
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/**
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* Set the current page segmentation mode. Defaults to PSM_AUTO.
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* The mode is stored as an IntParam so it can also be modified by
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* ReadConfigFile or SetVariable("tessedit_pageseg_mode", mode as string).
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*/
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void TessBaseAPI::SetPageSegMode(PageSegMode mode) {
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if (tesseract_ == NULL)
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tesseract_ = new Tesseract;
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tesseract_->tessedit_pageseg_mode.set_value(mode);
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}
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/** Return the current page segmentation mode. */
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PageSegMode TessBaseAPI::GetPageSegMode() const {
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if (tesseract_ == NULL)
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return PSM_SINGLE_BLOCK;
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return static_cast<PageSegMode>(
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static_cast<int>(tesseract_->tessedit_pageseg_mode));
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}
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/**
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* Recognize a rectangle from an image and return the result as a string.
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* May be called many times for a single Init.
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* Currently has no error checking.
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* Greyscale of 8 and color of 24 or 32 bits per pixel may be given.
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* Palette color images will not work properly and must be converted to
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* 24 bit.
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* Binary images of 1 bit per pixel may also be given but they must be
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* byte packed with the MSB of the first byte being the first pixel, and a
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* one pixel is WHITE. For binary images set bytes_per_pixel=0.
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* The recognized text is returned as a char* which is coded
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* as UTF8 and must be freed with the delete [] operator.
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*/
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char* TessBaseAPI::TesseractRect(const unsigned char* imagedata,
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int bytes_per_pixel,
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int bytes_per_line,
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int left, int top,
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int width, int height) {
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if (tesseract_ == NULL || width < kMinRectSize || height < kMinRectSize)
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return NULL; // Nothing worth doing.
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// Since this original api didn't give the exact size of the image,
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// we have to invent a reasonable value.
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int bits_per_pixel = bytes_per_pixel == 0 ? 1 : bytes_per_pixel * 8;
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SetImage(imagedata, bytes_per_line * 8 / bits_per_pixel, height + top,
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bytes_per_pixel, bytes_per_line);
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SetRectangle(left, top, width, height);
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return GetUTF8Text();
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}
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/**
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* Call between pages or documents etc to free up memory and forget
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* adaptive data.
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*/
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void TessBaseAPI::ClearAdaptiveClassifier() {
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if (tesseract_ == NULL)
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return;
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tesseract_->ResetAdaptiveClassifier();
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tesseract_->ResetDocumentDictionary();
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}
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/**
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* Provide an image for Tesseract to recognize. Format is as
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* TesseractRect above. Does not copy the image buffer, or take
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* ownership. The source image may be destroyed after Recognize is called,
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* either explicitly or implicitly via one of the Get*Text functions.
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* SetImage clears all recognition results, and sets the rectangle to the
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* full image, so it may be followed immediately by a GetUTF8Text, and it
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* will automatically perform recognition.
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*/
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void TessBaseAPI::SetImage(const unsigned char* imagedata,
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int width, int height,
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int bytes_per_pixel, int bytes_per_line) {
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if (InternalSetImage())
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thresholder_->SetImage(imagedata, width, height,
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bytes_per_pixel, bytes_per_line);
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}
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void TessBaseAPI::SetSourceResolution(int ppi) {
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if (thresholder_)
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thresholder_->SetSourceYResolution(ppi);
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else
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tprintf("Please call SetImage before SetSourceResolution.\n");
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}
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/**
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* Provide an image for Tesseract to recognize. As with SetImage above,
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* Tesseract doesn't take a copy or ownership or pixDestroy the image, so
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* it must persist until after Recognize.
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* Pix vs raw, which to use?
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* Use Pix where possible. A future version of Tesseract may choose to use Pix
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* as its internal representation and discard IMAGE altogether.
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* Because of that, an implementation that sources and targets Pix may end up
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* with less copies than an implementation that does not.
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*/
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void TessBaseAPI::SetImage(const Pix* pix) {
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if (InternalSetImage())
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thresholder_->SetImage(pix);
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}
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/**
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* Restrict recognition to a sub-rectangle of the image. Call after SetImage.
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* Each SetRectangle clears the recogntion results so multiple rectangles
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* can be recognized with the same image.
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*/
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void TessBaseAPI::SetRectangle(int left, int top, int width, int height) {
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if (thresholder_ == NULL)
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return;
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thresholder_->SetRectangle(left, top, width, height);
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ClearResults();
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}
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/**
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* ONLY available if you have Leptonica installed.
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* Get a copy of the internal thresholded image from Tesseract.
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*/
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Pix* TessBaseAPI::GetThresholdedImage() {
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|
if (tesseract_ == NULL)
|
|
return NULL;
|
|
if (tesseract_->pix_binary() == NULL)
|
|
Threshold(tesseract_->mutable_pix_binary());
|
|
return pixClone(tesseract_->pix_binary());
|
|
}
|
|
|
|
/**
|
|
* Get the result of page layout analysis as a leptonica-style
|
|
* Boxa, Pixa pair, in reading order.
|
|
* Can be called before or after Recognize.
|
|
*/
|
|
Boxa* TessBaseAPI::GetRegions(Pixa** pixa) {
|
|
return GetComponentImages(RIL_BLOCK, false, pixa, NULL);
|
|
}
|
|
|
|
/**
|
|
* Get the textlines as a leptonica-style Boxa, Pixa pair, in reading order.
|
|
* Can be called before or after Recognize.
|
|
* If blockids is not NULL, the block-id of each line is also returned as an
|
|
* array of one element per line. delete [] after use.
|
|
*/
|
|
Boxa* TessBaseAPI::GetTextlines(Pixa** pixa, int** blockids) {
|
|
return GetComponentImages(RIL_TEXTLINE, true, pixa, blockids);
|
|
}
|
|
|
|
/**
|
|
* Get textlines and strips of image regions as a leptonica-style Boxa, Pixa
|
|
* pair, in reading order. Enables downstream handling of non-rectangular
|
|
* regions.
|
|
* Can be called before or after Recognize.
|
|
* If blockids is not NULL, the block-id of each line is also returned as an
|
|
* array of one element per line. delete [] after use.
|
|
*/
|
|
Boxa* TessBaseAPI::GetStrips(Pixa** pixa, int** blockids) {
|
|
return GetComponentImages(RIL_TEXTLINE, false, pixa, blockids);
|
|
}
|
|
|
|
/**
|
|
* Get the words as a leptonica-style
|
|
* Boxa, Pixa pair, in reading order.
|
|
* Can be called before or after Recognize.
|
|
*/
|
|
Boxa* TessBaseAPI::GetWords(Pixa** pixa) {
|
|
return GetComponentImages(RIL_WORD, true, pixa, NULL);
|
|
}
|
|
|
|
/**
|
|
* Gets the individual connected (text) components (created
|
|
* after pages segmentation step, but before recognition)
|
|
* as a leptonica-style Boxa, Pixa pair, in reading order.
|
|
* Can be called before or after Recognize.
|
|
*/
|
|
Boxa* TessBaseAPI::GetConnectedComponents(Pixa** pixa) {
|
|
return GetComponentImages(RIL_SYMBOL, true, pixa, NULL);
|
|
}
|
|
|
|
/**
|
|
* Get the given level kind of components (block, textline, word etc.) as a
|
|
* leptonica-style Boxa, Pixa pair, in reading order.
|
|
* Can be called before or after Recognize.
|
|
* If blockids is not NULL, the block-id of each component is also returned
|
|
* as an array of one element per component. delete [] after use.
|
|
* If text_only is true, then only text components are returned.
|
|
*/
|
|
Boxa* TessBaseAPI::GetComponentImages(PageIteratorLevel level,
|
|
bool text_only,
|
|
Pixa** pixa, int** blockids) {
|
|
PageIterator* page_it = GetIterator();
|
|
if (page_it == NULL)
|
|
page_it = AnalyseLayout();
|
|
if (page_it == NULL)
|
|
return NULL; // Failed.
|
|
|
|
// Count the components to get a size for the arrays.
|
|
int component_count = 0;
|
|
int left, top, right, bottom;
|
|
do {
|
|
if (page_it->BoundingBoxInternal(level, &left, &top, &right, &bottom) &&
|
|
(!text_only || PTIsTextType(page_it->BlockType())))
|
|
++component_count;
|
|
} while (page_it->Next(level));
|
|
|
|
Boxa* boxa = boxaCreate(component_count);
|
|
if (pixa != NULL)
|
|
*pixa = pixaCreate(component_count);
|
|
if (blockids != NULL)
|
|
*blockids = new int[component_count];
|
|
|
|
int blockid = 0;
|
|
int component_index = 0;
|
|
page_it->Begin();
|
|
do {
|
|
if (page_it->BoundingBoxInternal(level, &left, &top, &right, &bottom) &&
|
|
(!text_only || PTIsTextType(page_it->BlockType()))) {
|
|
Box* lbox = boxCreate(left, top, right - left, bottom - top);
|
|
boxaAddBox(boxa, lbox, L_INSERT);
|
|
if (pixa != NULL) {
|
|
Pix* pix = page_it->GetBinaryImage(level);
|
|
pixaAddPix(*pixa, pix, L_INSERT);
|
|
pixaAddBox(*pixa, lbox, L_CLONE);
|
|
}
|
|
if (blockids != NULL) {
|
|
(*blockids)[component_index] = blockid;
|
|
if (page_it->IsAtFinalElement(RIL_BLOCK, level))
|
|
++blockid;
|
|
}
|
|
++component_index;
|
|
}
|
|
} while (page_it->Next(level));
|
|
delete page_it;
|
|
return boxa;
|
|
}
|
|
|
|
int TessBaseAPI::GetThresholdedImageScaleFactor() const {
|
|
if (thresholder_ == NULL) {
|
|
return 0;
|
|
}
|
|
return thresholder_->GetScaleFactor();
|
|
}
|
|
|
|
/** Dump the internal binary image to a PGM file. */
|
|
void TessBaseAPI::DumpPGM(const char* filename) {
|
|
if (tesseract_ == NULL)
|
|
return;
|
|
FILE *fp = fopen(filename, "wb");
|
|
Pix* pix = tesseract_->pix_binary();
|
|
int width = pixGetWidth(pix);
|
|
int height = pixGetHeight(pix);
|
|
l_uint32* data = pixGetData(pix);
|
|
fprintf(fp, "P5 %d %d 255\n", width, height);
|
|
for (int y = 0; y < height; ++y, data += pixGetWpl(pix)) {
|
|
for (int x = 0; x < width; ++x) {
|
|
uinT8 b = GET_DATA_BIT(data, x) ? 0 : 255;
|
|
fwrite(&b, 1, 1, fp);
|
|
}
|
|
}
|
|
fclose(fp);
|
|
}
|
|
|
|
/**
|
|
* Placeholder for call to Cube and test that the input data is correct.
|
|
* reskew is the direction of baselines in the skewed image in
|
|
* normalized (cos theta, sin theta) form, so (0.866, 0.5) would represent
|
|
* a 30 degree anticlockwise skew.
|
|
*/
|
|
int CubeAPITest(Boxa* boxa_blocks, Pixa* pixa_blocks,
|
|
Boxa* boxa_words, Pixa* pixa_words,
|
|
const FCOORD& reskew, Pix* page_pix,
|
|
PAGE_RES* page_res) {
|
|
int block_count = boxaGetCount(boxa_blocks);
|
|
ASSERT_HOST(block_count == pixaGetCount(pixa_blocks));
|
|
// Write each block to the current directory as junk_write_display.nnn.png.
|
|
for (int i = 0; i < block_count; ++i) {
|
|
Pix* pix = pixaGetPix(pixa_blocks, i, L_CLONE);
|
|
pixDisplayWrite(pix, 1);
|
|
}
|
|
int word_count = boxaGetCount(boxa_words);
|
|
ASSERT_HOST(word_count == pixaGetCount(pixa_words));
|
|
int pr_word = 0;
|
|
PAGE_RES_IT page_res_it(page_res);
|
|
for (page_res_it.restart_page(); page_res_it.word () != NULL;
|
|
page_res_it.forward(), ++pr_word) {
|
|
WERD_RES *word = page_res_it.word();
|
|
WERD_CHOICE* choice = word->best_choice;
|
|
// Write the first 100 words to files names wordims/<wordstring>.tif.
|
|
if (pr_word < 100) {
|
|
STRING filename("wordims/");
|
|
if (choice != NULL) {
|
|
filename += choice->unichar_string();
|
|
} else {
|
|
char numbuf[32];
|
|
filename += "unclassified";
|
|
snprintf(numbuf, 32, "%03d", pr_word);
|
|
filename += numbuf;
|
|
}
|
|
filename += ".tif";
|
|
Pix* pix = pixaGetPix(pixa_words, pr_word, L_CLONE);
|
|
pixWrite(filename.string(), pix, IFF_TIFF_G4);
|
|
}
|
|
}
|
|
ASSERT_HOST(pr_word == word_count);
|
|
return 0;
|
|
}
|
|
|
|
/**
|
|
* Runs page layout analysis in the mode set by SetPageSegMode.
|
|
* May optionally be called prior to Recognize to get access to just
|
|
* the page layout results. Returns an iterator to the results.
|
|
* Returns NULL on error or an empty page.
|
|
* The returned iterator must be deleted after use.
|
|
* WARNING! This class points to data held within the TessBaseAPI class, and
|
|
* therefore can only be used while the TessBaseAPI class still exists and
|
|
* has not been subjected to a call of Init, SetImage, Recognize, Clear, End
|
|
* DetectOS, or anything else that changes the internal PAGE_RES.
|
|
*/
|
|
PageIterator* TessBaseAPI::AnalyseLayout() {
|
|
if (FindLines() == 0) {
|
|
if (block_list_->empty())
|
|
return NULL; // The page was empty.
|
|
page_res_ = new PAGE_RES(block_list_, NULL);
|
|
DetectParagraphs(false);
|
|
return new PageIterator(
|
|
page_res_, tesseract_, thresholder_->GetScaleFactor(),
|
|
thresholder_->GetScaledYResolution(),
|
|
rect_left_, rect_top_, rect_width_, rect_height_);
|
|
}
|
|
return NULL;
|
|
}
|
|
|
|
/**
|
|
* Recognize the tesseract global image and return the result as Tesseract
|
|
* internal structures.
|
|
*/
|
|
int TessBaseAPI::Recognize(ETEXT_DESC* monitor) {
|
|
if (tesseract_ == NULL)
|
|
return -1;
|
|
if (FindLines() != 0)
|
|
return -1;
|
|
if (page_res_ != NULL)
|
|
delete page_res_;
|
|
if (block_list_->empty()) {
|
|
page_res_ = new PAGE_RES(block_list_, &tesseract_->prev_word_best_choice_);
|
|
return 0; // Empty page.
|
|
}
|
|
|
|
tesseract_->SetBlackAndWhitelist();
|
|
recognition_done_ = true;
|
|
if (tesseract_->tessedit_resegment_from_line_boxes)
|
|
page_res_ = tesseract_->ApplyBoxes(*input_file_, true, block_list_);
|
|
else if (tesseract_->tessedit_resegment_from_boxes)
|
|
page_res_ = tesseract_->ApplyBoxes(*input_file_, false, block_list_);
|
|
else
|
|
page_res_ = new PAGE_RES(block_list_, &tesseract_->prev_word_best_choice_);
|
|
if (tesseract_->tessedit_make_boxes_from_boxes) {
|
|
tesseract_->CorrectClassifyWords(page_res_);
|
|
return 0;
|
|
}
|
|
|
|
if (truth_cb_ != NULL) {
|
|
tesseract_->wordrec_run_blamer.set_value(true);
|
|
truth_cb_->Run(tesseract_->getDict().getUnicharset(),
|
|
image_height_, page_res_);
|
|
}
|
|
|
|
int result = 0;
|
|
if (tesseract_->interactive_display_mode) {
|
|
#ifndef GRAPHICS_DISABLED
|
|
tesseract_->pgeditor_main(rect_width_, rect_height_, page_res_);
|
|
#endif // GRAPHICS_DISABLED
|
|
// The page_res is invalid after an interactive session, so cleanup
|
|
// in a way that lets us continue to the next page without crashing.
|
|
delete page_res_;
|
|
page_res_ = NULL;
|
|
return -1;
|
|
} else if (tesseract_->tessedit_train_from_boxes) {
|
|
tesseract_->ApplyBoxTraining(*output_file_, page_res_);
|
|
} else if (tesseract_->tessedit_ambigs_training) {
|
|
FILE *training_output_file = tesseract_->init_recog_training(*input_file_);
|
|
// OCR the page segmented into words by tesseract.
|
|
tesseract_->recog_training_segmented(
|
|
*input_file_, page_res_, monitor, training_output_file);
|
|
fclose(training_output_file);
|
|
} else {
|
|
// Now run the main recognition.
|
|
if (tesseract_->recog_all_words(page_res_, monitor, NULL, NULL, 0)) {
|
|
DetectParagraphs(true);
|
|
} else {
|
|
result = -1;
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
/** Tests the chopper by exhaustively running chop_one_blob. */
|
|
int TessBaseAPI::RecognizeForChopTest(ETEXT_DESC* monitor) {
|
|
if (tesseract_ == NULL)
|
|
return -1;
|
|
if (thresholder_ == NULL || thresholder_->IsEmpty()) {
|
|
tprintf("Please call SetImage before attempting recognition.");
|
|
return -1;
|
|
}
|
|
if (page_res_ != NULL)
|
|
ClearResults();
|
|
if (FindLines() != 0)
|
|
return -1;
|
|
// Additional conditions under which chopper test cannot be run
|
|
if (tesseract_->interactive_display_mode) return -1;
|
|
|
|
recognition_done_ = true;
|
|
|
|
page_res_ = new PAGE_RES(block_list_, &(tesseract_->prev_word_best_choice_));
|
|
|
|
PAGE_RES_IT page_res_it(page_res_);
|
|
|
|
while (page_res_it.word() != NULL) {
|
|
WERD_RES *word_res = page_res_it.word();
|
|
GenericVector<TBOX> boxes;
|
|
tesseract_->MaximallyChopWord(boxes, page_res_it.block()->block,
|
|
page_res_it.row()->row, word_res);
|
|
page_res_it.forward();
|
|
}
|
|
return 0;
|
|
}
|
|
|
|
/**
|
|
* Recognizes all the pages in the named file, as a multi-page tiff or
|
|
* list of filenames, or single image, and gets the appropriate kind of text
|
|
* according to parameters: tessedit_create_boxfile,
|
|
* tessedit_make_boxes_from_boxes, tessedit_write_unlv, tessedit_create_hocr.
|
|
* Calls ProcessPage on each page in the input file, which may be a
|
|
* multi-page tiff, single-page other file format, or a plain text list of
|
|
* images to read. If tessedit_page_number is non-negative, processing begins
|
|
* at that page of a multi-page tiff file, or filelist.
|
|
* The text is returned in text_out. Returns false on error.
|
|
* If non-zero timeout_millisec terminates processing after the timeout on
|
|
* a single page.
|
|
* If non-NULL and non-empty, and some page fails for some reason,
|
|
* the page is reprocessed with the retry_config config file. Useful
|
|
* for interactively debugging a bad page.
|
|
*/
|
|
bool TessBaseAPI::ProcessPages(const char* filename,
|
|
const char* retry_config, int timeout_millisec,
|
|
STRING* text_out) {
|
|
int page = tesseract_->tessedit_page_number;
|
|
if (page < 0)
|
|
page = 0;
|
|
FILE* fp = fopen(filename, "rb");
|
|
if (fp == NULL) {
|
|
tprintf(_("Image file %s cannot be opened!\n"), filename);
|
|
return false;
|
|
}
|
|
// Find the number of pages if a tiff file, or zero otherwise.
|
|
int npages = CountTiffPages(fp);
|
|
fclose(fp);
|
|
|
|
if (tesseract_->tessedit_create_hocr) {
|
|
*text_out =
|
|
"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n"
|
|
"<!DOCTYPE html PUBLIC \"-//W3C//DTD XHTML 1.0 Transitional//EN\"\n"
|
|
" \"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd\">\n"
|
|
"<html xmlns=\"http://www.w3.org/1999/xhtml\" xml:lang=\"en\" "
|
|
"lang=\"en\">\n <head>\n <title></title>\n"
|
|
" <meta http-equiv=\"Content-Type\" content=\"text/html; "
|
|
"charset=utf-8\" />\n"
|
|
" <meta name='ocr-system' content='tesseract " VERSION "' />\n"
|
|
" <meta name='ocr-capabilities' content='ocr_page ocr_carea ocr_par"
|
|
" ocr_line ocrx_word'/>\n"
|
|
" </head>\n <body>\n";
|
|
} else {
|
|
*text_out = "";
|
|
}
|
|
|
|
bool success = true;
|
|
Pix *pix;
|
|
if (npages > 0) {
|
|
for (; page < npages && (pix = pixReadTiff(filename, page)) != NULL;
|
|
++page) {
|
|
if ((page >= 0) && (npages > 1))
|
|
tprintf(_("Page %d of %d\n"), page + 1, npages);
|
|
char page_str[kMaxIntSize];
|
|
snprintf(page_str, kMaxIntSize - 1, "%d", page);
|
|
SetVariable("applybox_page", page_str);
|
|
success &= ProcessPage(pix, page, filename, retry_config,
|
|
timeout_millisec, text_out);
|
|
pixDestroy(&pix);
|
|
if (tesseract_->tessedit_page_number >= 0 || npages == 1) {
|
|
break;
|
|
}
|
|
}
|
|
} else {
|
|
// The file is not a tiff file, so use the general pixRead function.
|
|
pix = pixRead(filename);
|
|
if (pix != NULL) {
|
|
success &= ProcessPage(pix, 0, filename, retry_config,
|
|
timeout_millisec, text_out);
|
|
pixDestroy(&pix);
|
|
} else {
|
|
// The file is not an image file, so try it as a list of filenames.
|
|
FILE* fimg = fopen(filename, "rb");
|
|
if (fimg == NULL) {
|
|
tprintf(_("File %s cannot be opened!\n"), filename);
|
|
return false;
|
|
}
|
|
tprintf(_("Reading %s as a list of filenames...\n"), filename);
|
|
char pagename[MAX_PATH];
|
|
// Skip to the requested page number.
|
|
for (int i = 0; i < page &&
|
|
fgets(pagename, sizeof(pagename), fimg) != NULL;
|
|
++i);
|
|
while (fgets(pagename, sizeof(pagename), fimg) != NULL) {
|
|
chomp_string(pagename);
|
|
pix = pixRead(pagename);
|
|
if (pix == NULL) {
|
|
tprintf(_("Image file %s cannot be read!\n"), pagename);
|
|
fclose(fimg);
|
|
return false;
|
|
}
|
|
tprintf(_("Page %d : %s\n"), page, pagename);
|
|
success &= ProcessPage(pix, page, pagename, retry_config,
|
|
timeout_millisec, text_out);
|
|
pixDestroy(&pix);
|
|
++page;
|
|
}
|
|
fclose(fimg);
|
|
}
|
|
}
|
|
if (tesseract_->tessedit_create_hocr)
|
|
*text_out += " </body>\n</html>\n";
|
|
return success;
|
|
}
|
|
|
|
/**
|
|
* Recognizes a single page for ProcessPages, appending the text to text_out.
|
|
* The pix is the image processed - filename and page_index are metadata
|
|
* used by side-effect processes, such as reading a box file or formatting
|
|
* as hOCR.
|
|
* If non-zero timeout_millisec terminates processing after the timeout.
|
|
* If non-NULL and non-empty, and some page fails for some reason,
|
|
* the page is reprocessed with the retry_config config file. Useful
|
|
* for interactively debugging a bad page.
|
|
* The text is returned in text_out. Returns false on error.
|
|
*/
|
|
bool TessBaseAPI::ProcessPage(Pix* pix, int page_index, const char* filename,
|
|
const char* retry_config, int timeout_millisec,
|
|
STRING* text_out) {
|
|
SetInputName(filename);
|
|
SetImage(pix);
|
|
bool failed = false;
|
|
if (timeout_millisec > 0) {
|
|
// Running with a timeout.
|
|
ETEXT_DESC monitor;
|
|
monitor.cancel = NULL;
|
|
monitor.cancel_this = NULL;
|
|
monitor.set_deadline_msecs(timeout_millisec);
|
|
// Now run the main recognition.
|
|
failed = Recognize(&monitor) < 0;
|
|
} else if (tesseract_->tessedit_pageseg_mode == PSM_OSD_ONLY ||
|
|
tesseract_->tessedit_pageseg_mode == PSM_AUTO_ONLY) {
|
|
// Disabled character recognition.
|
|
PageIterator* it = AnalyseLayout();
|
|
if (it == NULL) {
|
|
failed = true;
|
|
} else {
|
|
delete it;
|
|
return true;
|
|
}
|
|
} else {
|
|
// Normal layout and character recognition with no timeout.
|
|
failed = Recognize(NULL) < 0;
|
|
}
|
|
if (tesseract_->tessedit_write_images) {
|
|
Pix* page_pix = GetThresholdedImage();
|
|
pixWrite("tessinput.tif", page_pix, IFF_TIFF_G4);
|
|
}
|
|
if (failed && retry_config != NULL && retry_config[0] != '\0') {
|
|
// Save current config variables before switching modes.
|
|
FILE* fp = fopen(kOldVarsFile, "wb");
|
|
PrintVariables(fp);
|
|
fclose(fp);
|
|
// Switch to alternate mode for retry.
|
|
ReadConfigFile(retry_config);
|
|
SetImage(pix);
|
|
Recognize(NULL);
|
|
// Restore saved config variables.
|
|
ReadConfigFile(kOldVarsFile);
|
|
}
|
|
// Get text only if successful.
|
|
if (!failed) {
|
|
char* text;
|
|
if (tesseract_->tessedit_create_boxfile ||
|
|
tesseract_->tessedit_make_boxes_from_boxes) {
|
|
text = GetBoxText(page_index);
|
|
} else if (tesseract_->tessedit_write_unlv) {
|
|
text = GetUNLVText();
|
|
} else if (tesseract_->tessedit_create_hocr) {
|
|
text = GetHOCRText(page_index);
|
|
} else {
|
|
text = GetUTF8Text();
|
|
}
|
|
*text_out += text;
|
|
delete [] text;
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
/**
|
|
* Get a left-to-right iterator to the results of LayoutAnalysis and/or
|
|
* Recognize. The returned iterator must be deleted after use.
|
|
*/
|
|
LTRResultIterator* TessBaseAPI::GetLTRIterator() {
|
|
if (tesseract_ == NULL || page_res_ == NULL)
|
|
return NULL;
|
|
return new LTRResultIterator(
|
|
page_res_, tesseract_,
|
|
thresholder_->GetScaleFactor(), thresholder_->GetScaledYResolution(),
|
|
rect_left_, rect_top_, rect_width_, rect_height_);
|
|
}
|
|
|
|
/**
|
|
* Get a reading-order iterator to the results of LayoutAnalysis and/or
|
|
* Recognize. The returned iterator must be deleted after use.
|
|
* WARNING! This class points to data held within the TessBaseAPI class, and
|
|
* therefore can only be used while the TessBaseAPI class still exists and
|
|
* has not been subjected to a call of Init, SetImage, Recognize, Clear, End
|
|
* DetectOS, or anything else that changes the internal PAGE_RES.
|
|
*/
|
|
ResultIterator* TessBaseAPI::GetIterator() {
|
|
if (tesseract_ == NULL || page_res_ == NULL)
|
|
return NULL;
|
|
return ResultIterator::StartOfParagraph(LTRResultIterator(
|
|
page_res_, tesseract_,
|
|
thresholder_->GetScaleFactor(), thresholder_->GetScaledYResolution(),
|
|
rect_left_, rect_top_, rect_width_, rect_height_));
|
|
}
|
|
|
|
/**
|
|
* Get a mutable iterator to the results of LayoutAnalysis and/or Recognize.
|
|
* The returned iterator must be deleted after use.
|
|
* WARNING! This class points to data held within the TessBaseAPI class, and
|
|
* therefore can only be used while the TessBaseAPI class still exists and
|
|
* has not been subjected to a call of Init, SetImage, Recognize, Clear, End
|
|
* DetectOS, or anything else that changes the internal PAGE_RES.
|
|
*/
|
|
MutableIterator* TessBaseAPI::GetMutableIterator() {
|
|
if (tesseract_ == NULL || page_res_ == NULL)
|
|
return NULL;
|
|
return new MutableIterator(page_res_, tesseract_,
|
|
thresholder_->GetScaleFactor(),
|
|
thresholder_->GetScaledYResolution(),
|
|
rect_left_, rect_top_, rect_width_, rect_height_);
|
|
}
|
|
|
|
/** Make a text string from the internal data structures. */
|
|
char* TessBaseAPI::GetUTF8Text() {
|
|
if (tesseract_ == NULL ||
|
|
(!recognition_done_ && Recognize(NULL) < 0))
|
|
return NULL;
|
|
STRING text("");
|
|
ResultIterator *it = GetIterator();
|
|
do {
|
|
if (it->Empty(RIL_PARA)) continue;
|
|
char *para_text = it->GetUTF8Text(RIL_PARA);
|
|
text += para_text;
|
|
delete []para_text;
|
|
} while (it->Next(RIL_PARA));
|
|
char* result = new char[text.length() + 1];
|
|
strncpy(result, text.string(), text.length() + 1);
|
|
delete it;
|
|
return result;
|
|
}
|
|
|
|
static void AddBoxTohOCR(const PageIterator *it,
|
|
PageIteratorLevel level,
|
|
STRING* hocr_str) {
|
|
int left, top, right, bottom;
|
|
it->BoundingBox(level, &left, &top, &right, &bottom);
|
|
hocr_str->add_str_int("' title=\"bbox ", left);
|
|
hocr_str->add_str_int(" ", top);
|
|
hocr_str->add_str_int(" ", right);
|
|
hocr_str->add_str_int(" ", bottom);
|
|
*hocr_str += "\">";
|
|
}
|
|
|
|
/**
|
|
* Make a HTML-formatted string with hOCR markup from the internal
|
|
* data structures.
|
|
* page_number is 0-based but will appear in the output as 1-based.
|
|
* Image name/input_file_ can be set by SetInputName before calling
|
|
* GetHOCRText
|
|
* STL removed from original patch submission and refactored by rays.
|
|
*/
|
|
char* TessBaseAPI::GetHOCRText(int page_number) {
|
|
if (tesseract_ == NULL ||
|
|
(page_res_ == NULL && Recognize(NULL) < 0))
|
|
return NULL;
|
|
|
|
int lcnt = 1, bcnt = 1, pcnt = 1, wcnt = 1;
|
|
int page_id = page_number + 1; // hOCR uses 1-based page numbers.
|
|
|
|
STRING hocr_str("");
|
|
|
|
if (input_file_ == NULL)
|
|
SetInputName(NULL);
|
|
|
|
hocr_str.add_str_int(" <div class='ocr_page' id='page_", page_id);
|
|
hocr_str += "' title='image \"";
|
|
hocr_str += input_file_ ? *input_file_ : "unknown";
|
|
hocr_str.add_str_int("\"; bbox ", rect_left_);
|
|
hocr_str.add_str_int(" ", rect_top_);
|
|
hocr_str.add_str_int(" ", rect_width_);
|
|
hocr_str.add_str_int(" ", rect_height_);
|
|
hocr_str.add_str_int("; ppageno ", page_number);
|
|
hocr_str += "'>\n";
|
|
|
|
ResultIterator *res_it = GetIterator();
|
|
while (!res_it->Empty(RIL_BLOCK)) {
|
|
if (res_it->Empty(RIL_WORD)) {
|
|
res_it->Next(RIL_WORD);
|
|
continue;
|
|
}
|
|
|
|
// Open any new block/paragraph/textline.
|
|
if (res_it->IsAtBeginningOf(RIL_BLOCK)) {
|
|
hocr_str.add_str_int(" <div class='ocr_carea' id='block_", bcnt);
|
|
hocr_str.add_str_int("_", bcnt);
|
|
AddBoxTohOCR(res_it, RIL_BLOCK, &hocr_str);
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_PARA)) {
|
|
if (res_it->ParagraphIsLtr()) {
|
|
hocr_str.add_str_int("\n <p class='ocr_par' dir='ltr' id='par_", pcnt);
|
|
} else {
|
|
hocr_str.add_str_int("\n <p class='ocr_par' dir='rtl' id='par_", pcnt);
|
|
}
|
|
AddBoxTohOCR(res_it, RIL_PARA, &hocr_str);
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_TEXTLINE)) {
|
|
hocr_str.add_str_int("\n <span class='ocr_line' id='line_", lcnt);
|
|
AddBoxTohOCR(res_it, RIL_TEXTLINE, &hocr_str);
|
|
}
|
|
|
|
// Now, process the word...
|
|
hocr_str.add_str_int("<span class='ocrx_word' id='word_", wcnt);
|
|
AddBoxTohOCR(res_it, RIL_WORD, &hocr_str);
|
|
const char *font_name;
|
|
bool bold, italic, underlined, monospace, serif, smallcaps;
|
|
int pointsize, font_id;
|
|
font_name = res_it->WordFontAttributes(&bold, &italic, &underlined,
|
|
&monospace, &serif, &smallcaps,
|
|
&pointsize, &font_id);
|
|
bool last_word_in_line = res_it->IsAtFinalElement(RIL_TEXTLINE, RIL_WORD);
|
|
bool last_word_in_para = res_it->IsAtFinalElement(RIL_PARA, RIL_WORD);
|
|
bool last_word_in_block = res_it->IsAtFinalElement(RIL_BLOCK, RIL_WORD);
|
|
if (bold) hocr_str += "<strong>";
|
|
if (italic) hocr_str += "<em>";
|
|
do {
|
|
const char *grapheme = res_it->GetUTF8Text(RIL_SYMBOL);
|
|
if (grapheme && grapheme[0] != 0) {
|
|
if (grapheme[1] == 0) {
|
|
switch (grapheme[0]) {
|
|
case '<': hocr_str += "<"; break;
|
|
case '>': hocr_str += ">"; break;
|
|
case '&': hocr_str += "&"; break;
|
|
case '"': hocr_str += """; break;
|
|
case '\'': hocr_str += "'"; break;
|
|
default: hocr_str += grapheme;
|
|
}
|
|
} else {
|
|
hocr_str += grapheme;
|
|
}
|
|
}
|
|
delete []grapheme;
|
|
res_it->Next(RIL_SYMBOL);
|
|
} while (!res_it->Empty(RIL_BLOCK) && !res_it->IsAtBeginningOf(RIL_WORD));
|
|
if (italic) hocr_str += "</em>";
|
|
if (bold) hocr_str += "</strong>";
|
|
hocr_str += "</span> ";
|
|
wcnt++;
|
|
// Close any ending block/paragraph/textline.
|
|
if (last_word_in_line) {
|
|
hocr_str += "\n </span>";
|
|
lcnt++;
|
|
}
|
|
if (last_word_in_para) {
|
|
hocr_str += "\n </p>\n";
|
|
pcnt++;
|
|
}
|
|
if (last_word_in_block) {
|
|
hocr_str += " </div>\n";
|
|
bcnt++;
|
|
}
|
|
}
|
|
hocr_str += " </div>\n";
|
|
|
|
char *ret = new char[hocr_str.length() + 1];
|
|
strcpy(ret, hocr_str.string());
|
|
delete res_it;
|
|
return ret;
|
|
}
|
|
|
|
/** The 5 numbers output for each box (the usual 4 and a page number.) */
|
|
const int kNumbersPerBlob = 5;
|
|
/**
|
|
* The number of bytes taken by each number. Since we use inT16 for ICOORD,
|
|
* assume only 5 digits max.
|
|
*/
|
|
const int kBytesPerNumber = 5;
|
|
/**
|
|
* Multiplier for max expected textlength assumes (kBytesPerNumber + space)
|
|
* * kNumbersPerBlob plus the newline. Add to this the
|
|
* original UTF8 characters, and one kMaxBytesPerLine for safety.
|
|
*/
|
|
const int kBytesPerBlob = kNumbersPerBlob * (kBytesPerNumber + 1) + 1;
|
|
const int kBytesPerBoxFileLine = (kBytesPerNumber + 1) * kNumbersPerBlob + 1;
|
|
/** Max bytes in the decimal representation of inT64. */
|
|
const int kBytesPer64BitNumber = 20;
|
|
/**
|
|
* A maximal single box could occupy kNumbersPerBlob numbers at
|
|
* kBytesPer64BitNumber digits (if someone sneaks in a 64 bit value) and a
|
|
* space plus the newline and the maximum length of a UNICHAR.
|
|
* Test against this on each iteration for safety.
|
|
*/
|
|
const int kMaxBytesPerLine = kNumbersPerBlob * (kBytesPer64BitNumber + 1) + 1 +
|
|
UNICHAR_LEN;
|
|
|
|
/**
|
|
* The recognized text is returned as a char* which is coded
|
|
* as a UTF8 box file and must be freed with the delete [] operator.
|
|
* page_number is a 0-base page index that will appear in the box file.
|
|
*/
|
|
char* TessBaseAPI::GetBoxText(int page_number) {
|
|
if (tesseract_ == NULL ||
|
|
(!recognition_done_ && Recognize(NULL) < 0))
|
|
return NULL;
|
|
int blob_count;
|
|
int utf8_length = TextLength(&blob_count);
|
|
int total_length = blob_count * kBytesPerBoxFileLine + utf8_length +
|
|
kMaxBytesPerLine;
|
|
char* result = new char[total_length];
|
|
strcpy(result, "\0");
|
|
int output_length = 0;
|
|
LTRResultIterator* it = GetLTRIterator();
|
|
do {
|
|
int left, top, right, bottom;
|
|
if (it->BoundingBox(RIL_SYMBOL, &left, &top, &right, &bottom)) {
|
|
char* text = it->GetUTF8Text(RIL_SYMBOL);
|
|
// Tesseract uses space for recognition failure. Fix to a reject
|
|
// character, kTesseractReject so we don't create illegal box files.
|
|
for (int i = 0; text[i] != '\0'; ++i) {
|
|
if (text[i] == ' ')
|
|
text[i] = kTesseractReject;
|
|
}
|
|
snprintf(result + output_length, total_length - output_length,
|
|
"%s %d %d %d %d %d\n",
|
|
text, left, image_height_ - bottom,
|
|
right, image_height_ - top, page_number);
|
|
output_length += strlen(result + output_length);
|
|
delete [] text;
|
|
// Just in case...
|
|
if (output_length + kMaxBytesPerLine > total_length)
|
|
break;
|
|
}
|
|
} while (it->Next(RIL_SYMBOL));
|
|
delete it;
|
|
return result;
|
|
}
|
|
|
|
/**
|
|
* Conversion table for non-latin characters.
|
|
* Maps characters out of the latin set into the latin set.
|
|
* TODO(rays) incorporate this translation into unicharset.
|
|
*/
|
|
const int kUniChs[] = {
|
|
0x20ac, 0x201c, 0x201d, 0x2018, 0x2019, 0x2022, 0x2014, 0
|
|
};
|
|
/** Latin chars corresponding to the unicode chars above. */
|
|
const int kLatinChs[] = {
|
|
0x00a2, 0x0022, 0x0022, 0x0027, 0x0027, 0x00b7, 0x002d, 0
|
|
};
|
|
|
|
/**
|
|
* The recognized text is returned as a char* which is coded
|
|
* as UNLV format Latin-1 with specific reject and suspect codes
|
|
* and must be freed with the delete [] operator.
|
|
*/
|
|
char* TessBaseAPI::GetUNLVText() {
|
|
if (tesseract_ == NULL ||
|
|
(!recognition_done_ && Recognize(NULL) < 0))
|
|
return NULL;
|
|
bool tilde_crunch_written = false;
|
|
bool last_char_was_newline = true;
|
|
bool last_char_was_tilde = false;
|
|
|
|
int total_length = TextLength(NULL);
|
|
PAGE_RES_IT page_res_it(page_res_);
|
|
char* result = new char[total_length];
|
|
char* ptr = result;
|
|
for (page_res_it.restart_page(); page_res_it.word () != NULL;
|
|
page_res_it.forward()) {
|
|
WERD_RES *word = page_res_it.word();
|
|
// Process the current word.
|
|
if (word->unlv_crunch_mode != CR_NONE) {
|
|
if (word->unlv_crunch_mode != CR_DELETE &&
|
|
(!tilde_crunch_written ||
|
|
(word->unlv_crunch_mode == CR_KEEP_SPACE &&
|
|
word->word->space() > 0 &&
|
|
!word->word->flag(W_FUZZY_NON) &&
|
|
!word->word->flag(W_FUZZY_SP)))) {
|
|
if (!word->word->flag(W_BOL) &&
|
|
word->word->space() > 0 &&
|
|
!word->word->flag(W_FUZZY_NON) &&
|
|
!word->word->flag(W_FUZZY_SP)) {
|
|
/* Write a space to separate from preceeding good text */
|
|
*ptr++ = ' ';
|
|
last_char_was_tilde = false;
|
|
}
|
|
if (!last_char_was_tilde) {
|
|
// Write a reject char.
|
|
last_char_was_tilde = true;
|
|
*ptr++ = kUNLVReject;
|
|
tilde_crunch_written = true;
|
|
last_char_was_newline = false;
|
|
}
|
|
}
|
|
} else {
|
|
// NORMAL PROCESSING of non tilde crunched words.
|
|
tilde_crunch_written = false;
|
|
tesseract_->set_unlv_suspects(word);
|
|
const char* wordstr = word->best_choice->unichar_string().string();
|
|
const STRING& lengths = word->best_choice->unichar_lengths();
|
|
int length = lengths.length();
|
|
int i = 0;
|
|
int offset = 0;
|
|
|
|
if (last_char_was_tilde &&
|
|
word->word->space() == 0 && wordstr[offset] == ' ') {
|
|
// Prevent adjacent tilde across words - we know that adjacent tildes
|
|
// within words have been removed.
|
|
// Skip the first character.
|
|
offset = lengths[i++];
|
|
}
|
|
if (i < length && wordstr[offset] != 0) {
|
|
if (!last_char_was_newline)
|
|
*ptr++ = ' ';
|
|
else
|
|
last_char_was_newline = false;
|
|
for (; i < length; offset += lengths[i++]) {
|
|
if (wordstr[offset] == ' ' ||
|
|
wordstr[offset] == kTesseractReject) {
|
|
*ptr++ = kUNLVReject;
|
|
last_char_was_tilde = true;
|
|
} else {
|
|
if (word->reject_map[i].rejected())
|
|
*ptr++ = kUNLVSuspect;
|
|
UNICHAR ch(wordstr + offset, lengths[i]);
|
|
int uni_ch = ch.first_uni();
|
|
for (int j = 0; kUniChs[j] != 0; ++j) {
|
|
if (kUniChs[j] == uni_ch) {
|
|
uni_ch = kLatinChs[j];
|
|
break;
|
|
}
|
|
}
|
|
if (uni_ch <= 0xff) {
|
|
*ptr++ = static_cast<char>(uni_ch);
|
|
last_char_was_tilde = false;
|
|
} else {
|
|
*ptr++ = kUNLVReject;
|
|
last_char_was_tilde = true;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
if (word->word->flag(W_EOL) && !last_char_was_newline) {
|
|
/* Add a new line output */
|
|
*ptr++ = '\n';
|
|
tilde_crunch_written = false;
|
|
last_char_was_newline = true;
|
|
last_char_was_tilde = false;
|
|
}
|
|
}
|
|
*ptr++ = '\n';
|
|
*ptr = '\0';
|
|
return result;
|
|
}
|
|
|
|
/** Returns the average word confidence for Tesseract page result. */
|
|
int TessBaseAPI::MeanTextConf() {
|
|
int* conf = AllWordConfidences();
|
|
if (!conf) return 0;
|
|
int sum = 0;
|
|
int *pt = conf;
|
|
while (*pt >= 0) sum += *pt++;
|
|
if (pt != conf) sum /= pt - conf;
|
|
delete [] conf;
|
|
return sum;
|
|
}
|
|
|
|
/** Returns an array of all word confidences, terminated by -1. */
|
|
int* TessBaseAPI::AllWordConfidences() {
|
|
if (tesseract_ == NULL ||
|
|
(!recognition_done_ && Recognize(NULL) < 0))
|
|
return NULL;
|
|
int n_word = 0;
|
|
PAGE_RES_IT res_it(page_res_);
|
|
for (res_it.restart_page(); res_it.word() != NULL; res_it.forward())
|
|
n_word++;
|
|
|
|
int* conf = new int[n_word+1];
|
|
n_word = 0;
|
|
for (res_it.restart_page(); res_it.word() != NULL; res_it.forward()) {
|
|
WERD_RES *word = res_it.word();
|
|
WERD_CHOICE* choice = word->best_choice;
|
|
int w_conf = static_cast<int>(100 + 5 * choice->certainty());
|
|
// This is the eq for converting Tesseract confidence to 1..100
|
|
if (w_conf < 0) w_conf = 0;
|
|
if (w_conf > 100) w_conf = 100;
|
|
conf[n_word++] = w_conf;
|
|
}
|
|
conf[n_word] = -1;
|
|
return conf;
|
|
}
|
|
|
|
/**
|
|
* Applies the given word to the adaptive classifier if possible.
|
|
* The word must be SPACE-DELIMITED UTF-8 - l i k e t h i s , so it can
|
|
* tell the boundaries of the graphemes.
|
|
* Assumes that SetImage/SetRectangle have been used to set the image
|
|
* to the given word. The mode arg should be PSM_SINGLE_WORD or
|
|
* PSM_CIRCLE_WORD, as that will be used to control layout analysis.
|
|
* The currently set PageSegMode is preserved.
|
|
* Returns false if adaption was not possible for some reason.
|
|
*/
|
|
bool TessBaseAPI::AdaptToWordStr(PageSegMode mode, const char* wordstr) {
|
|
int debug = 0;
|
|
GetIntVariable("applybox_debug", &debug);
|
|
bool success = true;
|
|
PageSegMode current_psm = GetPageSegMode();
|
|
SetPageSegMode(mode);
|
|
SetVariable("classify_enable_learning", "0");
|
|
char* text = GetUTF8Text();
|
|
if (debug) {
|
|
tprintf("Trying to adapt \"%s\" to \"%s\"\n", text, wordstr);
|
|
}
|
|
if (text != NULL) {
|
|
PAGE_RES_IT it(page_res_);
|
|
WERD_RES* word_res = it.word();
|
|
if (word_res != NULL) {
|
|
word_res->word->set_text(wordstr);
|
|
} else {
|
|
success = false;
|
|
}
|
|
// Check to see if text matches wordstr.
|
|
int w = 0;
|
|
int t = 0;
|
|
for (t = 0; text[t] != '\0'; ++t) {
|
|
if (text[t] == '\n' || text[t] == ' ')
|
|
continue;
|
|
while (wordstr[w] != '\0' && wordstr[w] == ' ')
|
|
++w;
|
|
if (text[t] != wordstr[w])
|
|
break;
|
|
++w;
|
|
}
|
|
if (text[t] != '\0' || wordstr[w] != '\0') {
|
|
// No match.
|
|
delete page_res_;
|
|
GenericVector<TBOX> boxes;
|
|
page_res_ = tesseract_->SetupApplyBoxes(boxes, block_list_);
|
|
tesseract_->ReSegmentByClassification(page_res_);
|
|
tesseract_->TidyUp(page_res_);
|
|
PAGE_RES_IT pr_it(page_res_);
|
|
if (pr_it.word() == NULL)
|
|
success = false;
|
|
else
|
|
word_res = pr_it.word();
|
|
} else {
|
|
word_res->BestChoiceToCorrectText();
|
|
}
|
|
if (success) {
|
|
tesseract_->EnableLearning = true;
|
|
tesseract_->LearnWord(NULL, NULL, word_res);
|
|
}
|
|
delete [] text;
|
|
} else {
|
|
success = false;
|
|
}
|
|
SetPageSegMode(current_psm);
|
|
return success;
|
|
}
|
|
|
|
/**
|
|
* Free up recognition results and any stored image data, without actually
|
|
* freeing any recognition data that would be time-consuming to reload.
|
|
* Afterwards, you must call SetImage or TesseractRect before doing
|
|
* any Recognize or Get* operation.
|
|
*/
|
|
void TessBaseAPI::Clear() {
|
|
if (thresholder_ != NULL)
|
|
thresholder_->Clear();
|
|
ClearResults();
|
|
}
|
|
|
|
/**
|
|
* Close down tesseract and free up all memory. End() is equivalent to
|
|
* destructing and reconstructing your TessBaseAPI.
|
|
* Once End() has been used, none of the other API functions may be used
|
|
* other than Init and anything declared above it in the class definition.
|
|
*/
|
|
void TessBaseAPI::End() {
|
|
if (thresholder_ != NULL) {
|
|
delete thresholder_;
|
|
thresholder_ = NULL;
|
|
}
|
|
if (page_res_ != NULL) {
|
|
delete page_res_;
|
|
page_res_ = NULL;
|
|
}
|
|
if (block_list_ != NULL) {
|
|
delete block_list_;
|
|
block_list_ = NULL;
|
|
}
|
|
if (paragraph_models_ != NULL) {
|
|
paragraph_models_->delete_data_pointers();
|
|
delete paragraph_models_;
|
|
paragraph_models_ = NULL;
|
|
}
|
|
if (tesseract_ != NULL) {
|
|
delete tesseract_;
|
|
if (osd_tesseract_ == tesseract_)
|
|
osd_tesseract_ = NULL;
|
|
tesseract_ = NULL;
|
|
}
|
|
if (osd_tesseract_ != NULL) {
|
|
delete osd_tesseract_;
|
|
osd_tesseract_ = NULL;
|
|
}
|
|
if (equ_detect_ != NULL) {
|
|
delete equ_detect_;
|
|
equ_detect_ = NULL;
|
|
}
|
|
if (input_file_ != NULL) {
|
|
delete input_file_;
|
|
input_file_ = NULL;
|
|
}
|
|
if (output_file_ != NULL) {
|
|
delete output_file_;
|
|
output_file_ = NULL;
|
|
}
|
|
if (datapath_ != NULL) {
|
|
delete datapath_;
|
|
datapath_ = NULL;
|
|
}
|
|
if (language_ != NULL) {
|
|
delete language_;
|
|
language_ = NULL;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Check whether a word is valid according to Tesseract's language model
|
|
* returns 0 if the word is invalid, non-zero if valid
|
|
*/
|
|
int TessBaseAPI::IsValidWord(const char *word) {
|
|
return tesseract_->getDict().valid_word(word);
|
|
}
|
|
|
|
|
|
bool TessBaseAPI::GetTextDirection(int* out_offset, float* out_slope) {
|
|
if (page_res_ == NULL)
|
|
FindLines();
|
|
if (block_list_->length() < 1) {
|
|
return false;
|
|
}
|
|
|
|
// Get first block
|
|
BLOCK_IT block_it(block_list_);
|
|
block_it.move_to_first();
|
|
ROW_LIST* rows = block_it.data()->row_list();
|
|
if (rows->length() < 1) {
|
|
return false;
|
|
}
|
|
|
|
// Get first line of block
|
|
ROW_IT row_it(rows);
|
|
row_it.move_to_first();
|
|
ROW* row = row_it.data();
|
|
|
|
// Calculate offset and slope (NOTE: Kind of ugly)
|
|
*out_offset = static_cast<int>(row->base_line(0.0));
|
|
*out_slope = row->base_line(1.0) - row->base_line(0.0);
|
|
|
|
return true;
|
|
}
|
|
|
|
/** Sets Dict::letter_is_okay_ function to point to the given function. */
|
|
void TessBaseAPI::SetDictFunc(DictFunc f) {
|
|
if (tesseract_ != NULL) {
|
|
tesseract_->getDict().letter_is_okay_ = f;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Sets Dict::probability_in_context_ function to point to the given
|
|
* function.
|
|
*/
|
|
void TessBaseAPI::SetProbabilityInContextFunc(ProbabilityInContextFunc f) {
|
|
if (tesseract_ != NULL) {
|
|
tesseract_->getDict().probability_in_context_ = f;
|
|
// Set it for the sublangs too.
|
|
int num_subs = tesseract_->num_sub_langs();
|
|
for (int i = 0; i < num_subs; ++i) {
|
|
tesseract_->get_sub_lang(i)->getDict().probability_in_context_ = f;
|
|
}
|
|
}
|
|
}
|
|
|
|
/** Sets Wordrec::fill_lattice_ function to point to the given function. */
|
|
void TessBaseAPI::SetFillLatticeFunc(FillLatticeFunc f) {
|
|
if (tesseract_ != NULL) tesseract_->fill_lattice_ = f;
|
|
}
|
|
|
|
/** Common code for setting the image. */
|
|
bool TessBaseAPI::InternalSetImage() {
|
|
if (tesseract_ == NULL) {
|
|
tprintf("Please call Init before attempting to send an image.");
|
|
return false;
|
|
}
|
|
if (thresholder_ == NULL)
|
|
thresholder_ = new ImageThresholder;
|
|
ClearResults();
|
|
return true;
|
|
}
|
|
|
|
/**
|
|
* Run the thresholder to make the thresholded image, returned in pix,
|
|
* which must not be NULL. *pix must be initialized to NULL, or point
|
|
* to an existing pixDestroyable Pix.
|
|
* The usual argument to Threshold is Tesseract::mutable_pix_binary().
|
|
*/
|
|
void TessBaseAPI::Threshold(Pix** pix) {
|
|
ASSERT_HOST(pix != NULL);
|
|
if (!thresholder_->IsBinary()) {
|
|
tesseract_->set_pix_grey(thresholder_->GetPixRectGrey());
|
|
}
|
|
if (*pix != NULL)
|
|
pixDestroy(pix);
|
|
// Zero resolution messes up the algorithms, so make sure it is credible.
|
|
int y_res = thresholder_->GetScaledYResolution();
|
|
if (y_res < kMinCredibleResolution || y_res > kMaxCredibleResolution) {
|
|
// Use the minimum default resolution, as it is safer to under-estimate
|
|
// than over-estimate resolution.
|
|
thresholder_->SetSourceYResolution(kMinCredibleResolution);
|
|
}
|
|
thresholder_->ThresholdToPix(pix);
|
|
thresholder_->GetImageSizes(&rect_left_, &rect_top_,
|
|
&rect_width_, &rect_height_,
|
|
&image_width_, &image_height_);
|
|
// Set the internal resolution that is used for layout parameters from the
|
|
// estimated resolution, rather than the image resolution, which may be
|
|
// fabricated, but we will use the image resolution, if there is one, to
|
|
// report output point sizes.
|
|
int estimated_res = ClipToRange(thresholder_->GetScaledEstimatedResolution(),
|
|
kMinCredibleResolution,
|
|
kMaxCredibleResolution);
|
|
if (estimated_res != thresholder_->GetScaledEstimatedResolution()) {
|
|
tprintf("Estimated resolution %d out of range! Corrected to %d\n",
|
|
thresholder_->GetScaledEstimatedResolution(), estimated_res);
|
|
}
|
|
tesseract_->set_source_resolution(estimated_res);
|
|
}
|
|
|
|
/** Find lines from the image making the BLOCK_LIST. */
|
|
int TessBaseAPI::FindLines() {
|
|
if (thresholder_ == NULL || thresholder_->IsEmpty()) {
|
|
tprintf("Please call SetImage before attempting recognition.");
|
|
return -1;
|
|
}
|
|
if (recognition_done_)
|
|
ClearResults();
|
|
if (!block_list_->empty()) {
|
|
return 0;
|
|
}
|
|
if (tesseract_ == NULL) {
|
|
tesseract_ = new Tesseract;
|
|
tesseract_->InitAdaptiveClassifier(false);
|
|
}
|
|
if (tesseract_->pix_binary() == NULL)
|
|
Threshold(tesseract_->mutable_pix_binary());
|
|
if (tesseract_->ImageWidth() > MAX_INT16 ||
|
|
tesseract_->ImageHeight() > MAX_INT16) {
|
|
tprintf("Image too large: (%d, %d)\n",
|
|
tesseract_->ImageWidth(), tesseract_->ImageHeight());
|
|
return -1;
|
|
}
|
|
|
|
tesseract_->PrepareForPageseg();
|
|
|
|
if (tesseract_->textord_equation_detect) {
|
|
if (equ_detect_ == NULL && datapath_ != NULL) {
|
|
equ_detect_ = new EquationDetect(datapath_->string(), NULL);
|
|
}
|
|
tesseract_->SetEquationDetect(equ_detect_);
|
|
}
|
|
|
|
Tesseract* osd_tess = osd_tesseract_;
|
|
OSResults osr;
|
|
if (PSM_OSD_ENABLED(tesseract_->tessedit_pageseg_mode) && osd_tess == NULL) {
|
|
if (strcmp(language_->string(), "osd") == 0) {
|
|
osd_tess = tesseract_;
|
|
} else {
|
|
osd_tesseract_ = new Tesseract;
|
|
if (osd_tesseract_->init_tesseract(
|
|
datapath_->string(), NULL, "osd", OEM_TESSERACT_ONLY,
|
|
NULL, 0, NULL, NULL, false) == 0) {
|
|
osd_tess = osd_tesseract_;
|
|
osd_tesseract_->set_source_resolution(
|
|
thresholder_->GetSourceYResolution());
|
|
} else {
|
|
tprintf("Warning: Auto orientation and script detection requested,"
|
|
" but osd language failed to load\n");
|
|
delete osd_tesseract_;
|
|
osd_tesseract_ = NULL;
|
|
}
|
|
}
|
|
}
|
|
|
|
if (tesseract_->SegmentPage(input_file_, block_list_, osd_tess, &osr) < 0)
|
|
return -1;
|
|
// If Devanagari is being recognized, we use different images for page seg
|
|
// and for OCR.
|
|
tesseract_->PrepareForTessOCR(block_list_, osd_tess, &osr);
|
|
return 0;
|
|
}
|
|
|
|
/** Delete the pageres and clear the block list ready for a new page. */
|
|
void TessBaseAPI::ClearResults() {
|
|
if (tesseract_ != NULL) {
|
|
tesseract_->Clear();
|
|
}
|
|
if (page_res_ != NULL) {
|
|
delete page_res_;
|
|
page_res_ = NULL;
|
|
}
|
|
recognition_done_ = false;
|
|
if (block_list_ == NULL)
|
|
block_list_ = new BLOCK_LIST;
|
|
else
|
|
block_list_->clear();
|
|
if (paragraph_models_ != NULL) {
|
|
paragraph_models_->delete_data_pointers();
|
|
delete paragraph_models_;
|
|
paragraph_models_ = NULL;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Return the length of the output text string, as UTF8, assuming
|
|
* liberally two spacing marks after each word (as paragraphs end with two
|
|
* newlines), and assuming a single character reject marker for each rejected
|
|
* character.
|
|
* Also return the number of recognized blobs in blob_count.
|
|
*/
|
|
int TessBaseAPI::TextLength(int* blob_count) {
|
|
if (tesseract_ == NULL || page_res_ == NULL)
|
|
return 0;
|
|
|
|
PAGE_RES_IT page_res_it(page_res_);
|
|
int total_length = 2;
|
|
int total_blobs = 0;
|
|
// Iterate over the data structures to extract the recognition result.
|
|
for (page_res_it.restart_page(); page_res_it.word () != NULL;
|
|
page_res_it.forward()) {
|
|
WERD_RES *word = page_res_it.word();
|
|
WERD_CHOICE* choice = word->best_choice;
|
|
if (choice != NULL) {
|
|
total_blobs += choice->length() + 2;
|
|
total_length += choice->unichar_string().length() + 2;
|
|
for (int i = 0; i < word->reject_map.length(); ++i) {
|
|
if (word->reject_map[i].rejected())
|
|
++total_length;
|
|
}
|
|
}
|
|
}
|
|
if (blob_count != NULL)
|
|
*blob_count = total_blobs;
|
|
return total_length;
|
|
}
|
|
|
|
/**
|
|
* Estimates the Orientation And Script of the image.
|
|
* Returns true if the image was processed successfully.
|
|
*/
|
|
bool TessBaseAPI::DetectOS(OSResults* osr) {
|
|
if (tesseract_ == NULL)
|
|
return false;
|
|
ClearResults();
|
|
if (tesseract_->pix_binary() == NULL)
|
|
Threshold(tesseract_->mutable_pix_binary());
|
|
if (input_file_ == NULL)
|
|
input_file_ = new STRING(kInputFile);
|
|
return orientation_and_script_detection(*input_file_, osr, tesseract_);
|
|
}
|
|
|
|
void TessBaseAPI::set_min_orientation_margin(double margin) {
|
|
tesseract_->min_orientation_margin.set_value(margin);
|
|
}
|
|
|
|
/**
|
|
* Return text orientation of each block as determined in an earlier page layout
|
|
* analysis operation. Orientation is returned as the number of ccw 90-degree
|
|
* rotations (in [0..3]) required to make the text in the block upright
|
|
* (readable). Note that this may not necessary be the block orientation
|
|
* preferred for recognition (such as the case of vertical CJK text).
|
|
*
|
|
* Also returns whether the text in the block is believed to have vertical
|
|
* writing direction (when in an upright page orientation).
|
|
*
|
|
* The returned array is of length equal to the number of text blocks, which may
|
|
* be less than the total number of blocks. The ordering is intended to be
|
|
* consistent with GetTextLines().
|
|
*/
|
|
void TessBaseAPI::GetBlockTextOrientations(int** block_orientation,
|
|
bool** vertical_writing) {
|
|
delete[] *block_orientation;
|
|
*block_orientation = NULL;
|
|
delete[] *vertical_writing;
|
|
*vertical_writing = NULL;
|
|
BLOCK_IT block_it(block_list_);
|
|
|
|
block_it.move_to_first();
|
|
int num_blocks = 0;
|
|
for (block_it.mark_cycle_pt(); !block_it.cycled_list(); block_it.forward()) {
|
|
if (!block_it.data()->poly_block()->IsText()) {
|
|
continue;
|
|
}
|
|
++num_blocks;
|
|
}
|
|
if (!num_blocks) {
|
|
tprintf("WARNING: Found no blocks\n");
|
|
return;
|
|
}
|
|
*block_orientation = new int[num_blocks];
|
|
*vertical_writing = new bool[num_blocks];
|
|
block_it.move_to_first();
|
|
int i = 0;
|
|
for (block_it.mark_cycle_pt(); !block_it.cycled_list();
|
|
block_it.forward()) {
|
|
if (!block_it.data()->poly_block()->IsText()) {
|
|
continue;
|
|
}
|
|
FCOORD re_rotation = block_it.data()->re_rotation();
|
|
float re_theta = re_rotation.angle();
|
|
FCOORD classify_rotation = block_it.data()->classify_rotation();
|
|
float classify_theta = classify_rotation.angle();
|
|
double rot_theta = - (re_theta - classify_theta) * 2.0 / PI;
|
|
if (rot_theta < 0) rot_theta += 4;
|
|
int num_rotations = static_cast<int>(rot_theta + 0.5);
|
|
(*block_orientation)[i] = num_rotations;
|
|
// The classify_rotation is non-zero only if the text has vertical
|
|
// writing direction.
|
|
(*vertical_writing)[i] = classify_rotation.y() != 0.0f;
|
|
++i;
|
|
}
|
|
}
|
|
|
|
// ____________________________________________________________________________
|
|
// Ocropus add-ons.
|
|
|
|
/** Find lines from the image making the BLOCK_LIST. */
|
|
BLOCK_LIST* TessBaseAPI::FindLinesCreateBlockList() {
|
|
FindLines();
|
|
BLOCK_LIST* result = block_list_;
|
|
block_list_ = NULL;
|
|
return result;
|
|
}
|
|
|
|
/**
|
|
* Delete a block list.
|
|
* This is to keep BLOCK_LIST pointer opaque
|
|
* and let go of including the other headers.
|
|
*/
|
|
void TessBaseAPI::DeleteBlockList(BLOCK_LIST *block_list) {
|
|
delete block_list;
|
|
}
|
|
|
|
|
|
ROW *TessBaseAPI::MakeTessOCRRow(float baseline,
|
|
float xheight,
|
|
float descender,
|
|
float ascender) {
|
|
inT32 xstarts[] = {-32000};
|
|
double quad_coeffs[] = {0, 0, baseline};
|
|
return new ROW(1,
|
|
xstarts,
|
|
quad_coeffs,
|
|
xheight,
|
|
ascender - (baseline + xheight),
|
|
descender - baseline,
|
|
0,
|
|
0);
|
|
}
|
|
|
|
/** Creates a TBLOB* from the whole pix. */
|
|
TBLOB *TessBaseAPI::MakeTBLOB(Pix *pix) {
|
|
int width = pixGetWidth(pix);
|
|
int height = pixGetHeight(pix);
|
|
BLOCK block("a character", TRUE, 0, 0, 0, 0, width, height);
|
|
|
|
// Create C_BLOBs from the page
|
|
extract_edges(pix, &block);
|
|
|
|
// Merge all C_BLOBs
|
|
C_BLOB_LIST *list = block.blob_list();
|
|
C_BLOB_IT c_blob_it(list);
|
|
if (c_blob_it.empty())
|
|
return NULL;
|
|
// Move all the outlines to the first blob.
|
|
C_OUTLINE_IT ol_it(c_blob_it.data()->out_list());
|
|
for (c_blob_it.forward();
|
|
!c_blob_it.at_first();
|
|
c_blob_it.forward()) {
|
|
C_BLOB *c_blob = c_blob_it.data();
|
|
ol_it.add_list_after(c_blob->out_list());
|
|
}
|
|
// Convert the first blob to the output TBLOB.
|
|
return TBLOB::PolygonalCopy(c_blob_it.data());
|
|
}
|
|
|
|
/**
|
|
* This method baseline normalizes a TBLOB in-place. The input row is used
|
|
* for normalization. The denorm is an optional parameter in which the
|
|
* normalization-antidote is returned.
|
|
*/
|
|
void TessBaseAPI::NormalizeTBLOB(TBLOB *tblob, ROW *row,
|
|
bool numeric_mode, DENORM *denorm) {
|
|
TWERD word;
|
|
word.blobs = tblob;
|
|
if (denorm != NULL) {
|
|
word.SetupBLNormalize(NULL, row, row->x_height(), numeric_mode, denorm);
|
|
word.Normalize(*denorm);
|
|
} else {
|
|
DENORM normer;
|
|
word.SetupBLNormalize(NULL, row, row->x_height(), numeric_mode, &normer);
|
|
word.Normalize(normer);
|
|
}
|
|
word.blobs = NULL;
|
|
}
|
|
|
|
/**
|
|
* Return a TBLOB * from the whole pix.
|
|
* To be freed later with delete.
|
|
*/
|
|
TBLOB *make_tesseract_blob(float baseline, float xheight,
|
|
float descender, float ascender,
|
|
bool numeric_mode, Pix* pix) {
|
|
TBLOB *tblob = TessBaseAPI::MakeTBLOB(pix);
|
|
|
|
// Normalize TBLOB
|
|
ROW *row =
|
|
TessBaseAPI::MakeTessOCRRow(baseline, xheight, descender, ascender);
|
|
TessBaseAPI::NormalizeTBLOB(tblob, row, numeric_mode, NULL);
|
|
delete row;
|
|
return tblob;
|
|
}
|
|
|
|
/**
|
|
* Adapt to recognize the current image as the given character.
|
|
* The image must be preloaded into pix_binary_ and be just an image
|
|
* of a single character.
|
|
*/
|
|
void TessBaseAPI::AdaptToCharacter(const char *unichar_repr,
|
|
int length,
|
|
float baseline,
|
|
float xheight,
|
|
float descender,
|
|
float ascender) {
|
|
UNICHAR_ID id = tesseract_->unicharset.unichar_to_id(unichar_repr, length);
|
|
TBLOB *blob = make_tesseract_blob(baseline, xheight, descender, ascender,
|
|
tesseract_->classify_bln_numeric_mode,
|
|
tesseract_->pix_binary());
|
|
float threshold;
|
|
UNICHAR_ID best_class = 0;
|
|
float best_rating = -100;
|
|
|
|
|
|
// Classify to get a raw choice.
|
|
BLOB_CHOICE_LIST choices;
|
|
DENORM denorm;
|
|
tesseract_->AdaptiveClassifier(blob, denorm, &choices, NULL);
|
|
BLOB_CHOICE_IT choice_it;
|
|
choice_it.set_to_list(&choices);
|
|
for (choice_it.mark_cycle_pt(); !choice_it.cycled_list();
|
|
choice_it.forward()) {
|
|
if (choice_it.data()->rating() > best_rating) {
|
|
best_rating = choice_it.data()->rating();
|
|
best_class = choice_it.data()->unichar_id();
|
|
}
|
|
}
|
|
|
|
threshold = tesseract_->matcher_good_threshold;
|
|
|
|
if (blob->outlines)
|
|
tesseract_->AdaptToChar(blob, denorm, id, kUnknownFontinfoId, threshold);
|
|
delete blob;
|
|
}
|
|
|
|
|
|
PAGE_RES* TessBaseAPI::RecognitionPass1(BLOCK_LIST* block_list) {
|
|
PAGE_RES *page_res = new PAGE_RES(block_list,
|
|
&(tesseract_->prev_word_best_choice_));
|
|
tesseract_->recog_all_words(page_res, NULL, NULL, NULL, 1);
|
|
return page_res;
|
|
}
|
|
|
|
PAGE_RES* TessBaseAPI::RecognitionPass2(BLOCK_LIST* block_list,
|
|
PAGE_RES* pass1_result) {
|
|
if (!pass1_result)
|
|
pass1_result = new PAGE_RES(block_list,
|
|
&(tesseract_->prev_word_best_choice_));
|
|
tesseract_->recog_all_words(pass1_result, NULL, NULL, NULL, 2);
|
|
return pass1_result;
|
|
}
|
|
|
|
void TessBaseAPI::DetectParagraphs(bool after_text_recognition) {
|
|
int debug_level = 0;
|
|
GetIntVariable("paragraph_debug_level", &debug_level);
|
|
if (paragraph_models_ == NULL)
|
|
paragraph_models_ = new GenericVector<ParagraphModel*>;
|
|
MutableIterator *result_it = GetMutableIterator();
|
|
do { // Detect paragraphs for this block
|
|
GenericVector<ParagraphModel *> models;
|
|
::tesseract::DetectParagraphs(debug_level, after_text_recognition,
|
|
result_it, &models);
|
|
*paragraph_models_ += models;
|
|
} while (result_it->Next(RIL_BLOCK));
|
|
delete result_it;
|
|
}
|
|
|
|
struct TESS_CHAR : ELIST_LINK {
|
|
char *unicode_repr;
|
|
int length; // of unicode_repr
|
|
float cost;
|
|
TBOX box;
|
|
|
|
TESS_CHAR(float _cost, const char *repr, int len = -1) : cost(_cost) {
|
|
length = (len == -1 ? strlen(repr) : len);
|
|
unicode_repr = new char[length + 1];
|
|
strncpy(unicode_repr, repr, length);
|
|
}
|
|
|
|
TESS_CHAR() { // Satisfies ELISTIZE.
|
|
}
|
|
~TESS_CHAR() {
|
|
delete [] unicode_repr;
|
|
}
|
|
};
|
|
|
|
ELISTIZEH(TESS_CHAR)
|
|
ELISTIZE(TESS_CHAR)
|
|
|
|
static void add_space(TESS_CHAR_IT* it) {
|
|
TESS_CHAR *t = new TESS_CHAR(0, " ");
|
|
it->add_after_then_move(t);
|
|
}
|
|
|
|
|
|
static float rating_to_cost(float rating) {
|
|
rating = 100 + rating;
|
|
// cuddled that to save from coverage profiler
|
|
// (I have never seen ratings worse than -100,
|
|
// but the check won't hurt)
|
|
if (rating < 0) rating = 0;
|
|
return rating;
|
|
}
|
|
|
|
/**
|
|
* Extract the OCR results, costs (penalty points for uncertainty),
|
|
* and the bounding boxes of the characters.
|
|
*/
|
|
static void extract_result(TESS_CHAR_IT* out,
|
|
PAGE_RES* page_res) {
|
|
PAGE_RES_IT page_res_it(page_res);
|
|
int word_count = 0;
|
|
while (page_res_it.word() != NULL) {
|
|
WERD_RES *word = page_res_it.word();
|
|
const char *str = word->best_choice->unichar_string().string();
|
|
const char *len = word->best_choice->unichar_lengths().string();
|
|
TBOX real_rect = word->word->bounding_box();
|
|
|
|
if (word_count)
|
|
add_space(out);
|
|
int n = strlen(len);
|
|
for (int i = 0; i < n; i++) {
|
|
TESS_CHAR *tc = new TESS_CHAR(rating_to_cost(word->best_choice->rating()),
|
|
str, *len);
|
|
tc->box = real_rect.intersection(word->box_word->BlobBox(i));
|
|
out->add_after_then_move(tc);
|
|
str += *len;
|
|
len++;
|
|
}
|
|
page_res_it.forward();
|
|
word_count++;
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Extract the OCR results, costs (penalty points for uncertainty),
|
|
* and the bounding boxes of the characters.
|
|
*/
|
|
int TessBaseAPI::TesseractExtractResult(char** text,
|
|
int** lengths,
|
|
float** costs,
|
|
int** x0,
|
|
int** y0,
|
|
int** x1,
|
|
int** y1,
|
|
PAGE_RES* page_res) {
|
|
TESS_CHAR_LIST tess_chars;
|
|
TESS_CHAR_IT tess_chars_it(&tess_chars);
|
|
extract_result(&tess_chars_it, page_res);
|
|
tess_chars_it.move_to_first();
|
|
int n = tess_chars.length();
|
|
int text_len = 0;
|
|
*lengths = new int[n];
|
|
*costs = new float[n];
|
|
*x0 = new int[n];
|
|
*y0 = new int[n];
|
|
*x1 = new int[n];
|
|
*y1 = new int[n];
|
|
int i = 0;
|
|
for (tess_chars_it.mark_cycle_pt();
|
|
!tess_chars_it.cycled_list();
|
|
tess_chars_it.forward(), i++) {
|
|
TESS_CHAR *tc = tess_chars_it.data();
|
|
text_len += (*lengths)[i] = tc->length;
|
|
(*costs)[i] = tc->cost;
|
|
(*x0)[i] = tc->box.left();
|
|
(*y0)[i] = tc->box.bottom();
|
|
(*x1)[i] = tc->box.right();
|
|
(*y1)[i] = tc->box.top();
|
|
}
|
|
char *p = *text = new char[text_len];
|
|
|
|
tess_chars_it.move_to_first();
|
|
for (tess_chars_it.mark_cycle_pt();
|
|
!tess_chars_it.cycled_list();
|
|
tess_chars_it.forward()) {
|
|
TESS_CHAR *tc = tess_chars_it.data();
|
|
strncpy(p, tc->unicode_repr, tc->length);
|
|
p += tc->length;
|
|
}
|
|
return n;
|
|
}
|
|
|
|
/** This method returns the features associated with the input blob. */
|
|
void TessBaseAPI::GetFeaturesForBlob(TBLOB* blob, const DENORM& denorm,
|
|
INT_FEATURE_ARRAY int_features,
|
|
int* num_features,
|
|
int* FeatureOutlineIndex) {
|
|
if (tesseract_) {
|
|
tesseract_->ResetFeaturesHaveBeenExtracted();
|
|
}
|
|
uinT8* norm_array = new uinT8[MAX_NUM_CLASSES];
|
|
inT32 len;
|
|
*num_features = tesseract_->GetCharNormFeatures(
|
|
blob, denorm, tesseract_->PreTrainedTemplates,
|
|
int_features, norm_array, norm_array, &len, FeatureOutlineIndex);
|
|
delete [] norm_array;
|
|
}
|
|
|
|
/**
|
|
* This method returns the row to which a box of specified dimensions would
|
|
* belong. If no good match is found, it returns NULL.
|
|
*/
|
|
ROW* TessBaseAPI::FindRowForBox(BLOCK_LIST* blocks,
|
|
int left, int top, int right, int bottom) {
|
|
TBOX box(left, bottom, right, top);
|
|
BLOCK_IT b_it(blocks);
|
|
for (b_it.mark_cycle_pt(); !b_it.cycled_list(); b_it.forward()) {
|
|
BLOCK* block = b_it.data();
|
|
if (!box.major_overlap(block->bounding_box()))
|
|
continue;
|
|
ROW_IT r_it(block->row_list());
|
|
for (r_it.mark_cycle_pt(); !r_it.cycled_list(); r_it.forward()) {
|
|
ROW* row = r_it.data();
|
|
if (!box.major_overlap(row->bounding_box()))
|
|
continue;
|
|
WERD_IT w_it(row->word_list());
|
|
for (w_it.mark_cycle_pt(); !w_it.cycled_list(); w_it.forward()) {
|
|
WERD* word = w_it.data();
|
|
if (box.major_overlap(word->bounding_box()))
|
|
return row;
|
|
}
|
|
}
|
|
}
|
|
return NULL;
|
|
}
|
|
|
|
/** Method to run adaptive classifier on a blob. */
|
|
void TessBaseAPI::RunAdaptiveClassifier(TBLOB* blob, const DENORM& denorm,
|
|
int num_max_matches,
|
|
int* unichar_ids,
|
|
float* ratings,
|
|
int* num_matches_returned) {
|
|
BLOB_CHOICE_LIST* choices = new BLOB_CHOICE_LIST;
|
|
tesseract_->AdaptiveClassifier(blob, denorm, choices, NULL);
|
|
BLOB_CHOICE_IT choices_it(choices);
|
|
int& index = *num_matches_returned;
|
|
index = 0;
|
|
for (choices_it.mark_cycle_pt();
|
|
!choices_it.cycled_list() && index < num_max_matches;
|
|
choices_it.forward()) {
|
|
BLOB_CHOICE* choice = choices_it.data();
|
|
unichar_ids[index] = choice->unichar_id();
|
|
ratings[index] = choice->rating();
|
|
++index;
|
|
}
|
|
*num_matches_returned = index;
|
|
delete choices;
|
|
}
|
|
|
|
/** This method returns the string form of the specified unichar. */
|
|
const char* TessBaseAPI::GetUnichar(int unichar_id) {
|
|
return tesseract_->unicharset.id_to_unichar(unichar_id);
|
|
}
|
|
|
|
/** Return the pointer to the i-th dawg loaded into tesseract_ object. */
|
|
const Dawg *TessBaseAPI::GetDawg(int i) const {
|
|
if (tesseract_ == NULL || i >= NumDawgs()) return NULL;
|
|
return tesseract_->getDict().GetDawg(i);
|
|
}
|
|
|
|
/** Return the number of dawgs loaded into tesseract_ object. */
|
|
int TessBaseAPI::NumDawgs() const {
|
|
return tesseract_ == NULL ? 0 : tesseract_->getDict().NumDawgs();
|
|
}
|
|
|
|
/** Return a pointer to underlying CubeRecoContext object if present. */
|
|
CubeRecoContext *TessBaseAPI::GetCubeRecoContext() const {
|
|
return (tesseract_ == NULL) ? NULL : tesseract_->GetCubeRecoContext();
|
|
}
|
|
} // namespace tesseract.
|