mirror of
https://github.com/tesseract-ocr/tesseract.git
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2882 lines
96 KiB
C++
2882 lines
96 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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#ifdef __linux__
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#include <signal.h>
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#endif
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#if defined(_WIN32)
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#ifdef _MSC_VER
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#include "vcsversion.h"
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#include "mathfix.h"
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#elif MINGW
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// workaround for stdlib.h with -std=c++11 for _splitpath and _MAX_FNAME
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#undef __STRICT_ANSI__
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#endif // _MSC_VER
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#include <fcntl.h>
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#include <io.h>
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#else
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#include <dirent.h>
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#include <libgen.h>
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#include <string.h>
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#endif // _WIN32
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#include <iostream>
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#include <string>
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#include <iterator>
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#include <fstream>
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#include "allheaders.h"
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#include "baseapi.h"
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#include "blobclass.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 "dict.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 "globaloc.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 "makerow.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 "renderer.h"
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#include "strngs.h"
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#include "openclwrapper.h"
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BOOL_VAR(stream_filelist, FALSE, "Stream a filelist from stdin");
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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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/**
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* Temp file used for storing current parameters before applying retry values.
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*/
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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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unknown_title_ = "";
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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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#if defined(GIT_REV) && (defined(DEBUG) || defined(_DEBUG))
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return GIT_REV;
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#else
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return TESSERACT_VERSION_STR;
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#endif
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}
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/**
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* If compiled with OpenCL AND an available OpenCL
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* device is deemed faster than serial code, then
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* "device" is populated with the cl_device_id
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* and returns sizeof(cl_device_id)
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* otherwise *device=NULL and returns 0.
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*/
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#ifdef USE_OPENCL
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#if USE_DEVICE_SELECTION
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#include "opencl_device_selection.h"
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#endif
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#endif
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size_t TessBaseAPI::getOpenCLDevice(void **data) {
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#ifdef USE_OPENCL
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#if USE_DEVICE_SELECTION
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ds_device device = OpenclDevice::getDeviceSelection();
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if (device.type == DS_DEVICE_OPENCL_DEVICE) {
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*data = reinterpret_cast<void*>(new cl_device_id);
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memcpy(*data, &device.oclDeviceID, sizeof(cl_device_id));
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return sizeof(cl_device_id);
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}
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#endif
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#endif
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*data = NULL;
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return 0;
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}
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/**
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* Writes the thresholded image to stderr as a PBM file on receipt of a
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* SIGSEGV, SIGFPE, or SIGBUS signal. (Linux/Unix only).
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*/
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void TessBaseAPI::CatchSignals() {
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#ifdef __linux__
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struct sigaction action;
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memset(&action, 0, sizeof(action));
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action.sa_handler = &signal_exit;
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action.sa_flags = SA_RESETHAND;
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sigaction(SIGSEGV, &action, NULL);
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sigaction(SIGFPE, &action, NULL);
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sigaction(SIGBUS, &action, NULL);
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#else
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// Warn API users that an implementation is needed.
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tprintf("CatchSignals has no non-linux implementation!\n");
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#endif
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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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PERF_COUNT_START("TessBaseAPI::Init")
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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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// PERF_COUNT_SUB("delete tesseract_")
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#ifdef USE_OPENCL
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OpenclDevice od;
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od.InitEnv();
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#endif
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PERF_COUNT_SUB("OD::InitEnv()")
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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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PERF_COUNT_SUB("update tesseract_")
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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 ((strcmp(datapath_->string(), "") == 0) &&
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(strcmp(tesseract_->datadir.string(), "") != 0))
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*datapath_ = tesseract_->datadir;
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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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// PERF_COUNT_SUB("update last_oem_requested_")
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// For same language and datapath, just reset the adaptive classifier.
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if (reset_classifier) {
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tesseract_->ResetAdaptiveClassifier();
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PERF_COUNT_SUB("tesseract_->ResetAdaptiveClassifier()")
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}
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PERF_COUNT_END
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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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#ifdef _WIN32
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STRING pattern = tesseract_->datadir + "/*." + kTrainedDataSuffix;
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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 // _WIN32
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DIR *dir;
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struct dirent *dirent;
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char *dot;
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STRING extension = STRING(".") + kTrainedDataSuffix;
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dir = opendir(tesseract_->datadir.string());
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if (dir != NULL) {
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while ((dirent = readdir(dir))) {
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// Skip '.', '..', and hidden files
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if (dirent->d_name[0] != '.') {
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if (strstr(dirent->d_name, extension.string()) != NULL) {
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dot = strrchr(dirent->d_name, '.');
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// This ensures that .traineddata is at the end of the file name
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if (strncmp(dot, extension.string(),
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strlen(extension.string())) == 0) {
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*dot = '\0';
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langs->push_back(STRING(dirent->d_name));
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}
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}
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}
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}
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closedir(dir);
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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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else
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ParamUtils::ResetToDefaults(tesseract_->params());
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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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*/
|
|
char* TessBaseAPI::TesseractRect(const unsigned char* imagedata,
|
|
int bytes_per_pixel,
|
|
int bytes_per_line,
|
|
int left, int top,
|
|
int width, int height) {
|
|
if (tesseract_ == NULL || width < kMinRectSize || height < kMinRectSize)
|
|
return NULL; // Nothing worth doing.
|
|
|
|
// Since this original api didn't give the exact size of the image,
|
|
// we have to invent a reasonable value.
|
|
int bits_per_pixel = bytes_per_pixel == 0 ? 1 : bytes_per_pixel * 8;
|
|
SetImage(imagedata, bytes_per_line * 8 / bits_per_pixel, height + top,
|
|
bytes_per_pixel, bytes_per_line);
|
|
SetRectangle(left, top, width, height);
|
|
|
|
return GetUTF8Text();
|
|
}
|
|
|
|
/**
|
|
* Call between pages or documents etc to free up memory and forget
|
|
* adaptive data.
|
|
*/
|
|
void TessBaseAPI::ClearAdaptiveClassifier() {
|
|
if (tesseract_ == NULL)
|
|
return;
|
|
tesseract_->ResetAdaptiveClassifier();
|
|
tesseract_->ResetDocumentDictionary();
|
|
}
|
|
|
|
/**
|
|
* Provide an image for Tesseract to recognize. Format is as
|
|
* TesseractRect above. Copies the image buffer and converts to Pix.
|
|
* SetImage clears all recognition results, and sets the rectangle to the
|
|
* full image, so it may be followed immediately by a GetUTF8Text, and it
|
|
* will automatically perform recognition.
|
|
*/
|
|
void TessBaseAPI::SetImage(const unsigned char* imagedata,
|
|
int width, int height,
|
|
int bytes_per_pixel, int bytes_per_line) {
|
|
if (InternalSetImage()) {
|
|
thresholder_->SetImage(imagedata, width, height,
|
|
bytes_per_pixel, bytes_per_line);
|
|
SetInputImage(thresholder_->GetPixRect());
|
|
}
|
|
}
|
|
|
|
void TessBaseAPI::SetSourceResolution(int ppi) {
|
|
if (thresholder_)
|
|
thresholder_->SetSourceYResolution(ppi);
|
|
else
|
|
tprintf("Please call SetImage before SetSourceResolution.\n");
|
|
}
|
|
|
|
/**
|
|
* Provide an image for Tesseract to recognize. As with SetImage above,
|
|
* Tesseract takes its own copy of the image, so it need not persist until
|
|
* after Recognize.
|
|
* Pix vs raw, which to use?
|
|
* Use Pix where possible. Tesseract uses Pix as its internal representation
|
|
* and it is therefore more efficient to provide a Pix directly.
|
|
*/
|
|
void TessBaseAPI::SetImage(Pix* pix) {
|
|
if (InternalSetImage()) {
|
|
thresholder_->SetImage(pix);
|
|
SetInputImage(thresholder_->GetPixRect());
|
|
}
|
|
}
|
|
|
|
/**
|
|
* Restrict recognition to a sub-rectangle of the image. Call after SetImage.
|
|
* Each SetRectangle clears the recogntion results so multiple rectangles
|
|
* can be recognized with the same image.
|
|
*/
|
|
void TessBaseAPI::SetRectangle(int left, int top, int width, int height) {
|
|
if (thresholder_ == NULL)
|
|
return;
|
|
thresholder_->SetRectangle(left, top, width, height);
|
|
ClearResults();
|
|
}
|
|
|
|
/**
|
|
* ONLY available after SetImage if you have Leptonica installed.
|
|
* Get a copy of the internal thresholded image from Tesseract.
|
|
*/
|
|
Pix* TessBaseAPI::GetThresholdedImage() {
|
|
if (tesseract_ == NULL || thresholder_ == 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.
|
|
* If paraids is not NULL, the paragraph-id of each line within its block is
|
|
* also returned as an array of one element per line. delete [] after use.
|
|
*/
|
|
Boxa* TessBaseAPI::GetTextlines(const bool raw_image, const int raw_padding,
|
|
Pixa** pixa, int** blockids, int** paraids) {
|
|
return GetComponentImages(RIL_TEXTLINE, true, raw_image, raw_padding,
|
|
pixa, blockids, paraids);
|
|
}
|
|
|
|
/**
|
|
* 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, bool raw_image,
|
|
const int raw_padding,
|
|
Pixa** pixa, int** blockids,
|
|
int** paraids) {
|
|
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;
|
|
|
|
TessResultCallback<bool>* get_bbox = NULL;
|
|
if (raw_image) {
|
|
// Get bounding box in original raw image with padding.
|
|
get_bbox = NewPermanentTessCallback(page_it, &PageIterator::BoundingBox,
|
|
level, raw_padding,
|
|
&left, &top, &right, &bottom);
|
|
} else {
|
|
// Get bounding box from binarized imaged. Note that this could be
|
|
// differently scaled from the original image.
|
|
get_bbox = NewPermanentTessCallback(page_it,
|
|
&PageIterator::BoundingBoxInternal,
|
|
level, &left, &top, &right, &bottom);
|
|
}
|
|
do {
|
|
if (get_bbox->Run() &&
|
|
(!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];
|
|
if (paraids != NULL)
|
|
*paraids = new int[component_count];
|
|
|
|
int blockid = 0;
|
|
int paraid = 0;
|
|
int component_index = 0;
|
|
page_it->Begin();
|
|
do {
|
|
if (get_bbox->Run() &&
|
|
(!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 = NULL;
|
|
if (raw_image) {
|
|
pix = page_it->GetImage(level, raw_padding, GetInputImage(), &left,
|
|
&top);
|
|
} else {
|
|
pix = page_it->GetBinaryImage(level);
|
|
}
|
|
pixaAddPix(*pixa, pix, L_INSERT);
|
|
pixaAddBox(*pixa, lbox, L_CLONE);
|
|
}
|
|
if (paraids != NULL) {
|
|
(*paraids)[component_index] = paraid;
|
|
if (page_it->IsAtFinalElement(RIL_PARA, level))
|
|
++paraid;
|
|
}
|
|
if (blockids != NULL) {
|
|
(*blockids)[component_index] = blockid;
|
|
if (page_it->IsAtFinalElement(RIL_BLOCK, level)) {
|
|
++blockid;
|
|
paraid = 0;
|
|
}
|
|
}
|
|
++component_index;
|
|
}
|
|
} while (page_it->Next(level));
|
|
delete page_it;
|
|
delete get_bbox;
|
|
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);
|
|
}
|
|
|
|
#ifndef NO_CUBE_BUILD
|
|
/**
|
|
* 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;
|
|
}
|
|
#endif // NO_CUBE_BUILD
|
|
|
|
/**
|
|
* 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.
|
|
* If merge_similar_words is true, words are combined where suitable for use
|
|
* with a line recognizer. Use if you want to use AnalyseLayout to find the
|
|
* textlines, and then want to process textline fragments with an external
|
|
* line recognizer.
|
|
* 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() { return AnalyseLayout(false); }
|
|
|
|
PageIterator* TessBaseAPI::AnalyseLayout(bool merge_similar_words) {
|
|
if (FindLines() == 0) {
|
|
if (block_list_->empty())
|
|
return NULL; // The page was empty.
|
|
page_res_ = new PAGE_RES(merge_similar_words, 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;
|
|
delete page_res_;
|
|
if (block_list_->empty()) {
|
|
page_res_ = new PAGE_RES(false, 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 {
|
|
// TODO(rays) LSTM here.
|
|
page_res_ = new PAGE_RES(false,
|
|
block_list_, &tesseract_->prev_word_best_choice_);
|
|
}
|
|
if (page_res_ == NULL) {
|
|
return -1;
|
|
}
|
|
if (tesseract_->tessedit_make_boxes_from_boxes) {
|
|
tesseract_->CorrectClassifyWords(page_res_);
|
|
return 0;
|
|
}
|
|
|
|
if (truth_cb_ != NULL) {
|
|
tesseract_->wordrec_run_blamer.set_value(true);
|
|
PageIterator *page_it = new PageIterator(
|
|
page_res_, tesseract_, thresholder_->GetScaleFactor(),
|
|
thresholder_->GetScaledYResolution(),
|
|
rect_left_, rect_top_, rect_width_, rect_height_);
|
|
truth_cb_->Run(tesseract_->getDict().getUnicharset(),
|
|
image_height_, page_it, this->tesseract()->pix_grey());
|
|
delete page_it;
|
|
}
|
|
|
|
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) {
|
|
STRING fontname;
|
|
ExtractFontName(*output_file_, &fontname);
|
|
tesseract_->ApplyBoxTraining(fontname, 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.
|
|
bool wait_for_text = true;
|
|
GetBoolVariable("paragraph_text_based", &wait_for_text);
|
|
if (!wait_for_text) DetectParagraphs(false);
|
|
if (tesseract_->recog_all_words(page_res_, monitor, NULL, NULL, 0)) {
|
|
if (wait_for_text) 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(false, 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;
|
|
}
|
|
|
|
// Takes ownership of the input pix.
|
|
void TessBaseAPI::SetInputImage(Pix* pix) { tesseract_->set_pix_original(pix); }
|
|
|
|
Pix* TessBaseAPI::GetInputImage() { return tesseract_->pix_original(); }
|
|
|
|
const char * TessBaseAPI::GetInputName() {
|
|
if (input_file_)
|
|
return input_file_->c_str();
|
|
return NULL;
|
|
}
|
|
|
|
const char * TessBaseAPI::GetDatapath() {
|
|
return tesseract_->datadir.c_str();
|
|
}
|
|
|
|
int TessBaseAPI::GetSourceYResolution() {
|
|
return thresholder_->GetSourceYResolution();
|
|
}
|
|
|
|
// If flist exists, get data from there. Otherwise get data from buf.
|
|
// Seems convoluted, but is the easiest way I know of to meet multiple
|
|
// goals. Support streaming from stdin, and also work on platforms
|
|
// lacking fmemopen.
|
|
bool TessBaseAPI::ProcessPagesFileList(FILE *flist,
|
|
STRING *buf,
|
|
const char* retry_config,
|
|
int timeout_millisec,
|
|
TessResultRenderer* renderer,
|
|
int tessedit_page_number) {
|
|
if (!flist && !buf) return false;
|
|
int page = (tessedit_page_number >= 0) ? tessedit_page_number : 0;
|
|
char pagename[MAX_PATH];
|
|
|
|
GenericVector<STRING> lines;
|
|
if (!flist) {
|
|
buf->split('\n', &lines);
|
|
if (lines.empty()) return false;
|
|
}
|
|
|
|
// Skip to the requested page number.
|
|
for (int i = 0; i < page; i++) {
|
|
if (flist) {
|
|
if (fgets(pagename, sizeof(pagename), flist) == NULL) break;
|
|
}
|
|
}
|
|
|
|
// Begin producing output
|
|
if (renderer && !renderer->BeginDocument(unknown_title_)) {
|
|
return false;
|
|
}
|
|
|
|
// Loop over all pages - or just the requested one
|
|
while (true) {
|
|
if (flist) {
|
|
if (fgets(pagename, sizeof(pagename), flist) == NULL) break;
|
|
} else {
|
|
if (page >= lines.size()) break;
|
|
snprintf(pagename, sizeof(pagename), "%s", lines[page].c_str());
|
|
}
|
|
chomp_string(pagename);
|
|
Pix *pix = pixRead(pagename);
|
|
if (pix == NULL) {
|
|
tprintf("Image file %s cannot be read!\n", pagename);
|
|
return false;
|
|
}
|
|
tprintf("Page %d : %s\n", page, pagename);
|
|
bool r = ProcessPage(pix, page, pagename, retry_config,
|
|
timeout_millisec, renderer);
|
|
pixDestroy(&pix);
|
|
if (!r) return false;
|
|
if (tessedit_page_number >= 0) break;
|
|
++page;
|
|
}
|
|
|
|
// Finish producing output
|
|
if (renderer && !renderer->EndDocument()) {
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool TessBaseAPI::ProcessPagesMultipageTiff(const l_uint8 *data,
|
|
size_t size,
|
|
const char* filename,
|
|
const char* retry_config,
|
|
int timeout_millisec,
|
|
TessResultRenderer* renderer,
|
|
int tessedit_page_number) {
|
|
#ifndef ANDROID_BUILD
|
|
Pix *pix = NULL;
|
|
#ifdef USE_OPENCL
|
|
OpenclDevice od;
|
|
#endif // USE_OPENCL
|
|
int page = (tessedit_page_number >= 0) ? tessedit_page_number : 0;
|
|
for (; ; ++page) {
|
|
if (tessedit_page_number >= 0)
|
|
page = tessedit_page_number;
|
|
#ifdef USE_OPENCL
|
|
if ( od.selectedDeviceIsOpenCL() ) {
|
|
pix = (data) ?
|
|
od.pixReadMemTiffCl(data, size, page) :
|
|
od.pixReadTiffCl(filename, page);
|
|
} else {
|
|
#endif // USE_OPENCL
|
|
pix = (data) ?
|
|
pixReadMemTiff(data, size, page) :
|
|
pixReadTiff(filename, page);
|
|
#ifdef USE_OPENCL
|
|
}
|
|
#endif // USE_OPENCL
|
|
if (pix == NULL) break;
|
|
tprintf("Page %d\n", page + 1);
|
|
char page_str[kMaxIntSize];
|
|
snprintf(page_str, kMaxIntSize - 1, "%d", page);
|
|
SetVariable("applybox_page", page_str);
|
|
bool r = ProcessPage(pix, page, filename, retry_config,
|
|
timeout_millisec, renderer);
|
|
pixDestroy(&pix);
|
|
if (!r) return false;
|
|
if (tessedit_page_number >= 0) break;
|
|
}
|
|
return true;
|
|
#else
|
|
return false;
|
|
#endif
|
|
}
|
|
|
|
// Master ProcessPages calls ProcessPagesInternal and then does any post-
|
|
// processing required due to being in a training mode.
|
|
bool TessBaseAPI::ProcessPages(const char* filename, const char* retry_config,
|
|
int timeout_millisec,
|
|
TessResultRenderer* renderer) {
|
|
bool result =
|
|
ProcessPagesInternal(filename, retry_config, timeout_millisec, renderer);
|
|
if (result) {
|
|
if (tesseract_->tessedit_train_from_boxes &&
|
|
!tesseract_->WriteTRFile(*output_file_)) {
|
|
tprintf("Write of TR file failed: %s\n", output_file_->string());
|
|
return false;
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
// In the ideal scenario, Tesseract will start working on data as soon
|
|
// as it can. For example, if you steam a filelist through stdin, we
|
|
// should start the OCR process as soon as the first filename is
|
|
// available. This is particularly useful when hooking Tesseract up to
|
|
// slow hardware such as a book scanning machine.
|
|
//
|
|
// Unfortunately there are tradeoffs. You can't seek on stdin. That
|
|
// makes automatic detection of datatype (TIFF? filelist? PNG?)
|
|
// impractical. So we support a command line flag to explicitly
|
|
// identify the scenario that really matters: filelists on
|
|
// stdin. We'll still do our best if the user likes pipes.
|
|
bool TessBaseAPI::ProcessPagesInternal(const char* filename,
|
|
const char* retry_config,
|
|
int timeout_millisec,
|
|
TessResultRenderer* renderer) {
|
|
PERF_COUNT_START("ProcessPages")
|
|
bool stdInput = !strcmp(filename, "stdin") || !strcmp(filename, "-");
|
|
if (stdInput) {
|
|
#ifdef WIN32
|
|
if (_setmode(_fileno(stdin), _O_BINARY) == -1)
|
|
tprintf("ERROR: cin to binary: %s", strerror(errno));
|
|
#endif // WIN32
|
|
}
|
|
|
|
if (stream_filelist) {
|
|
return ProcessPagesFileList(stdin, NULL, retry_config,
|
|
timeout_millisec, renderer,
|
|
tesseract_->tessedit_page_number);
|
|
}
|
|
|
|
// At this point we are officially in autodection territory.
|
|
// That means any data in stdin must be buffered, to make it
|
|
// seekable.
|
|
std::string buf;
|
|
const l_uint8 *data = NULL;
|
|
if (stdInput) {
|
|
buf.assign((std::istreambuf_iterator<char>(std::cin)),
|
|
(std::istreambuf_iterator<char>()));
|
|
data = reinterpret_cast<const l_uint8 *>(buf.data());
|
|
}
|
|
|
|
// Here is our autodetection
|
|
int format;
|
|
int r = (stdInput) ?
|
|
findFileFormatBuffer(data, &format) :
|
|
findFileFormat(filename, &format);
|
|
|
|
// Maybe we have a filelist
|
|
if (r != 0 || format == IFF_UNKNOWN) {
|
|
STRING s(buf.c_str());
|
|
return ProcessPagesFileList(NULL, &s, retry_config,
|
|
timeout_millisec, renderer,
|
|
tesseract_->tessedit_page_number);
|
|
}
|
|
|
|
// Maybe we have a TIFF which is potentially multipage
|
|
bool tiff = (format == IFF_TIFF || format == IFF_TIFF_PACKBITS ||
|
|
format == IFF_TIFF_RLE || format == IFF_TIFF_G3 ||
|
|
format == IFF_TIFF_G4 || format == IFF_TIFF_LZW ||
|
|
format == IFF_TIFF_ZIP);
|
|
|
|
// Fail early if we can, before producing any output
|
|
Pix *pix = NULL;
|
|
if (!tiff) {
|
|
pix = (stdInput) ? pixReadMem(data, buf.size()) : pixRead(filename);
|
|
if (pix == NULL) {
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// Begin the output
|
|
if (renderer && !renderer->BeginDocument(unknown_title_)) {
|
|
pixDestroy(&pix);
|
|
return false;
|
|
}
|
|
|
|
// Produce output
|
|
r = (tiff) ?
|
|
ProcessPagesMultipageTiff(data, buf.size(), filename, retry_config,
|
|
timeout_millisec, renderer,
|
|
tesseract_->tessedit_page_number) :
|
|
ProcessPage(pix, 0, filename, retry_config,
|
|
timeout_millisec, renderer);
|
|
|
|
// Clean up memory as needed
|
|
pixDestroy(&pix);
|
|
|
|
// End the output
|
|
if (!r || (renderer && !renderer->EndDocument())) {
|
|
return false;
|
|
}
|
|
PERF_COUNT_END
|
|
return true;
|
|
}
|
|
|
|
bool TessBaseAPI::ProcessPage(Pix* pix, int page_index, const char* filename,
|
|
const char* retry_config, int timeout_millisec,
|
|
TessResultRenderer* renderer) {
|
|
PERF_COUNT_START("ProcessPage")
|
|
SetInputName(filename);
|
|
SetImage(pix);
|
|
bool failed = false;
|
|
|
|
if (tesseract_->tessedit_pageseg_mode == PSM_AUTO_ONLY) {
|
|
// Disabled character recognition
|
|
PageIterator* it = AnalyseLayout();
|
|
|
|
if (it == NULL) {
|
|
failed = true;
|
|
} else {
|
|
delete it;
|
|
}
|
|
} else if (tesseract_->tessedit_pageseg_mode == PSM_OSD_ONLY) {
|
|
failed = FindLines() != 0;
|
|
} else 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 {
|
|
// Normal layout and character recognition with no timeout.
|
|
failed = Recognize(NULL) < 0;
|
|
}
|
|
|
|
if (tesseract_->tessedit_write_images) {
|
|
#ifndef ANDROID_BUILD
|
|
Pix* page_pix = GetThresholdedImage();
|
|
pixWrite("tessinput.tif", page_pix, IFF_TIFF_G4);
|
|
#endif // ANDROID_BUILD
|
|
}
|
|
|
|
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);
|
|
}
|
|
|
|
if (renderer && !failed) {
|
|
failed = !renderer->AddImage(this);
|
|
}
|
|
|
|
PERF_COUNT_END
|
|
return !failed;
|
|
}
|
|
|
|
/**
|
|
* 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;
|
|
}
|
|
|
|
/**
|
|
* Gets the block orientation at the current iterator position.
|
|
*/
|
|
static tesseract::Orientation GetBlockTextOrientation(const PageIterator *it) {
|
|
tesseract::Orientation orientation;
|
|
tesseract::WritingDirection writing_direction;
|
|
tesseract::TextlineOrder textline_order;
|
|
float deskew_angle;
|
|
it->Orientation(&orientation, &writing_direction, &textline_order,
|
|
&deskew_angle);
|
|
return orientation;
|
|
}
|
|
|
|
/**
|
|
* Fits a line to the baseline at the given level, and appends its coefficients
|
|
* to the hOCR string.
|
|
* NOTE: The hOCR spec is unclear on how to specify baseline coefficients for
|
|
* rotated textlines. For this reason, on textlines that are not upright, this
|
|
* method currently only inserts a 'textangle' property to indicate the rotation
|
|
* direction and does not add any baseline information to the hocr string.
|
|
*/
|
|
static void AddBaselineCoordsTohOCR(const PageIterator *it,
|
|
PageIteratorLevel level,
|
|
STRING* hocr_str) {
|
|
tesseract::Orientation orientation = GetBlockTextOrientation(it);
|
|
if (orientation != ORIENTATION_PAGE_UP) {
|
|
hocr_str->add_str_int("; textangle ", 360 - orientation * 90);
|
|
return;
|
|
}
|
|
|
|
int left, top, right, bottom;
|
|
it->BoundingBox(level, &left, &top, &right, &bottom);
|
|
|
|
// Try to get the baseline coordinates at this level.
|
|
int x1, y1, x2, y2;
|
|
if (!it->Baseline(level, &x1, &y1, &x2, &y2))
|
|
return;
|
|
// Following the description of this field of the hOCR spec, we convert the
|
|
// baseline coordinates so that "the bottom left of the bounding box is the
|
|
// origin".
|
|
x1 -= left;
|
|
x2 -= left;
|
|
y1 -= bottom;
|
|
y2 -= bottom;
|
|
|
|
// Now fit a line through the points so we can extract coefficients for the
|
|
// equation: y = p1 x + p0
|
|
double p1 = 0;
|
|
double p0 = 0;
|
|
if (x1 == x2) {
|
|
// Problem computing the polynomial coefficients.
|
|
return;
|
|
}
|
|
p1 = (y2 - y1) / static_cast<double>(x2 - x1);
|
|
p0 = y1 - static_cast<double>(p1 * x1);
|
|
|
|
hocr_str->add_str_double("; baseline ", round(p1 * 1000.0) / 1000.0);
|
|
hocr_str->add_str_double(" ", round(p0 * 1000.0) / 1000.0);
|
|
}
|
|
|
|
static void AddIdTohOCR(STRING* hocr_str, const std::string base, int num1,
|
|
int num2) {
|
|
const size_t BUFSIZE = 64;
|
|
char id_buffer[BUFSIZE];
|
|
if (num2 >= 0) {
|
|
snprintf(id_buffer, BUFSIZE - 1, "%s_%d_%d", base.c_str(), num1, num2);
|
|
} else {
|
|
snprintf(id_buffer, BUFSIZE - 1, "%s_%d", base.c_str(), num1);
|
|
}
|
|
id_buffer[BUFSIZE - 1] = '\0';
|
|
*hocr_str += " id='";
|
|
*hocr_str += id_buffer;
|
|
*hocr_str += "'";
|
|
}
|
|
|
|
static void AddBoxTohOCR(const ResultIterator* it, PageIteratorLevel level,
|
|
STRING* hocr_str) {
|
|
int left, top, right, bottom;
|
|
it->BoundingBox(level, &left, &top, &right, &bottom);
|
|
// This is the only place we use double quotes instead of single quotes,
|
|
// but it may too late to change for consistency
|
|
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);
|
|
// Add baseline coordinates & heights for textlines only.
|
|
if (level == RIL_TEXTLINE) {
|
|
AddBaselineCoordsTohOCR(it, level, hocr_str);
|
|
// add custom height measures
|
|
float row_height, descenders, ascenders; // row attributes
|
|
it->RowAttributes(&row_height, &descenders, &ascenders);
|
|
// TODO(rays): Do we want to limit these to a single decimal place?
|
|
hocr_str->add_str_double("; x_size ", row_height);
|
|
hocr_str->add_str_double("; x_descenders ", descenders * -1);
|
|
hocr_str->add_str_double("; x_ascenders ", ascenders);
|
|
}
|
|
*hocr_str += "\">";
|
|
}
|
|
|
|
static void AddBoxToTSV(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("\t", left);
|
|
hocr_str->add_str_int("\t", top);
|
|
hocr_str->add_str_int("\t", right - left);
|
|
hocr_str->add_str_int("\t", bottom - top);
|
|
}
|
|
|
|
/**
|
|
* 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) {
|
|
return GetHOCRText(NULL, page_number);
|
|
}
|
|
|
|
/**
|
|
* 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(ETEXT_DESC* monitor, int page_number) {
|
|
if (tesseract_ == NULL || (page_res_ == NULL && Recognize(monitor) < 0))
|
|
return NULL;
|
|
|
|
int lcnt = 1, bcnt = 1, pcnt = 1, wcnt = 1;
|
|
int page_id = page_number + 1; // hOCR uses 1-based page numbers.
|
|
bool para_is_ltr = true; // Default direction is LTR
|
|
const char* paragraph_lang = NULL;
|
|
bool font_info = false;
|
|
GetBoolVariable("hocr_font_info", &font_info);
|
|
|
|
STRING hocr_str("");
|
|
|
|
if (input_file_ == NULL)
|
|
SetInputName(NULL);
|
|
|
|
#ifdef _WIN32
|
|
// convert input name from ANSI encoding to utf-8
|
|
int str16_len =
|
|
MultiByteToWideChar(CP_ACP, 0, input_file_->string(), -1, NULL, 0);
|
|
wchar_t *uni16_str = new WCHAR[str16_len];
|
|
str16_len = MultiByteToWideChar(CP_ACP, 0, input_file_->string(), -1,
|
|
uni16_str, str16_len);
|
|
int utf8_len = WideCharToMultiByte(CP_UTF8, 0, uni16_str, str16_len, NULL, 0,
|
|
NULL, NULL);
|
|
char *utf8_str = new char[utf8_len];
|
|
WideCharToMultiByte(CP_UTF8, 0, uni16_str, str16_len, utf8_str,
|
|
utf8_len, NULL, NULL);
|
|
*input_file_ = utf8_str;
|
|
delete[] uni16_str;
|
|
delete[] utf8_str;
|
|
#endif
|
|
|
|
hocr_str += " <div class='ocr_page'";
|
|
AddIdTohOCR(&hocr_str, "page", page_id, -1);
|
|
hocr_str += " title='image \"";
|
|
if (input_file_) {
|
|
hocr_str += HOcrEscape(input_file_->string());
|
|
} else {
|
|
hocr_str += "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)) {
|
|
para_is_ltr = true; // reset to default direction
|
|
hocr_str += " <div class='ocr_carea'";
|
|
AddIdTohOCR(&hocr_str, "block", page_id, bcnt);
|
|
AddBoxTohOCR(res_it, RIL_BLOCK, &hocr_str);
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_PARA)) {
|
|
hocr_str += "\n <p class='ocr_par'";
|
|
para_is_ltr = res_it->ParagraphIsLtr();
|
|
if (!para_is_ltr) {
|
|
hocr_str += " dir='rtl'";
|
|
}
|
|
AddIdTohOCR(&hocr_str, "par", page_id, pcnt);
|
|
paragraph_lang = res_it->WordRecognitionLanguage();
|
|
if (paragraph_lang) {
|
|
hocr_str += " lang='";
|
|
hocr_str += paragraph_lang;
|
|
hocr_str += "'";
|
|
}
|
|
AddBoxTohOCR(res_it, RIL_PARA, &hocr_str);
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_TEXTLINE)) {
|
|
hocr_str += "\n <span class='ocr_line'";
|
|
AddIdTohOCR(&hocr_str, "line", page_id, lcnt);
|
|
AddBoxTohOCR(res_it, RIL_TEXTLINE, &hocr_str);
|
|
}
|
|
|
|
// Now, process the word...
|
|
hocr_str += "<span class='ocrx_word'";
|
|
AddIdTohOCR(&hocr_str, "word", page_id, wcnt);
|
|
int left, top, right, bottom;
|
|
bool bold, italic, underlined, monospace, serif, smallcaps;
|
|
int pointsize, font_id;
|
|
const char *font_name;
|
|
res_it->BoundingBox(RIL_WORD, &left, &top, &right, &bottom);
|
|
font_name = res_it->WordFontAttributes(&bold, &italic, &underlined,
|
|
&monospace, &serif, &smallcaps,
|
|
&pointsize, &font_id);
|
|
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.add_str_int("; x_wconf ", res_it->Confidence(RIL_WORD));
|
|
if (font_info) {
|
|
if (font_name) {
|
|
hocr_str += "; x_font ";
|
|
hocr_str += HOcrEscape(font_name);
|
|
}
|
|
hocr_str.add_str_int("; x_fsize ", pointsize);
|
|
}
|
|
hocr_str += "'";
|
|
const char* lang = res_it->WordRecognitionLanguage();
|
|
if (lang && (!paragraph_lang || strcmp(lang, paragraph_lang))) {
|
|
hocr_str += " lang='";
|
|
hocr_str += lang;
|
|
hocr_str += "'";
|
|
}
|
|
switch (res_it->WordDirection()) {
|
|
// Only emit direction if different from current paragraph direction
|
|
case DIR_LEFT_TO_RIGHT:
|
|
if (!para_is_ltr) hocr_str += " dir='ltr'";
|
|
break;
|
|
case DIR_RIGHT_TO_LEFT:
|
|
if (para_is_ltr) hocr_str += " dir='rtl'";
|
|
break;
|
|
case DIR_MIX:
|
|
case DIR_NEUTRAL:
|
|
default: // Do nothing.
|
|
break;
|
|
}
|
|
hocr_str += ">";
|
|
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) {
|
|
hocr_str += HOcrEscape(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++;
|
|
para_is_ltr = true; // back to default direction
|
|
}
|
|
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;
|
|
}
|
|
|
|
/**
|
|
* Make a TSV-formatted string from the internal data structures.
|
|
* page_number is 0-based but will appear in the output as 1-based.
|
|
*/
|
|
char* TessBaseAPI::GetTSVText(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; // we use 1-based page numbers.
|
|
|
|
STRING tsv_str("");
|
|
|
|
int page_num = page_id, block_num = 0, par_num = 0, line_num = 0,
|
|
word_num = 0;
|
|
|
|
tsv_str.add_str_int("1\t", page_num); // level 1 - page
|
|
tsv_str.add_str_int("\t", block_num);
|
|
tsv_str.add_str_int("\t", par_num);
|
|
tsv_str.add_str_int("\t", line_num);
|
|
tsv_str.add_str_int("\t", word_num);
|
|
tsv_str.add_str_int("\t", rect_left_);
|
|
tsv_str.add_str_int("\t", rect_top_);
|
|
tsv_str.add_str_int("\t", rect_width_);
|
|
tsv_str.add_str_int("\t", rect_height_);
|
|
tsv_str += "\t-1\t\n";
|
|
|
|
ResultIterator* res_it = GetIterator();
|
|
while (!res_it->Empty(RIL_BLOCK)) {
|
|
if (res_it->Empty(RIL_WORD)) {
|
|
res_it->Next(RIL_WORD);
|
|
continue;
|
|
}
|
|
|
|
// Add rows for any new block/paragraph/textline.
|
|
if (res_it->IsAtBeginningOf(RIL_BLOCK)) {
|
|
block_num++, par_num = 0, line_num = 0, word_num = 0;
|
|
tsv_str.add_str_int("2\t", page_num); // level 2 - block
|
|
tsv_str.add_str_int("\t", block_num);
|
|
tsv_str.add_str_int("\t", par_num);
|
|
tsv_str.add_str_int("\t", line_num);
|
|
tsv_str.add_str_int("\t", word_num);
|
|
AddBoxToTSV(res_it, RIL_BLOCK, &tsv_str);
|
|
tsv_str += "\t-1\t\n"; // end of row for block
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_PARA)) {
|
|
par_num++, line_num = 0, word_num = 0;
|
|
tsv_str.add_str_int("3\t", page_num); // level 3 - paragraph
|
|
tsv_str.add_str_int("\t", block_num);
|
|
tsv_str.add_str_int("\t", par_num);
|
|
tsv_str.add_str_int("\t", line_num);
|
|
tsv_str.add_str_int("\t", word_num);
|
|
AddBoxToTSV(res_it, RIL_PARA, &tsv_str);
|
|
tsv_str += "\t-1\t\n"; // end of row for para
|
|
}
|
|
if (res_it->IsAtBeginningOf(RIL_TEXTLINE)) {
|
|
line_num++, word_num = 0;
|
|
tsv_str.add_str_int("4\t", page_num); // level 4 - line
|
|
tsv_str.add_str_int("\t", block_num);
|
|
tsv_str.add_str_int("\t", par_num);
|
|
tsv_str.add_str_int("\t", line_num);
|
|
tsv_str.add_str_int("\t", word_num);
|
|
AddBoxToTSV(res_it, RIL_TEXTLINE, &tsv_str);
|
|
tsv_str += "\t-1\t\n"; // end of row for line
|
|
}
|
|
|
|
// Now, process the word...
|
|
int left, top, right, bottom;
|
|
bool bold, italic, underlined, monospace, serif, smallcaps;
|
|
int pointsize, font_id;
|
|
const char* font_name;
|
|
res_it->BoundingBox(RIL_WORD, &left, &top, &right, &bottom);
|
|
font_name =
|
|
res_it->WordFontAttributes(&bold, &italic, &underlined, &monospace,
|
|
&serif, &smallcaps, &pointsize, &font_id);
|
|
word_num++;
|
|
tsv_str.add_str_int("5\t", page_num); // level 5 - word
|
|
tsv_str.add_str_int("\t", block_num);
|
|
tsv_str.add_str_int("\t", par_num);
|
|
tsv_str.add_str_int("\t", line_num);
|
|
tsv_str.add_str_int("\t", word_num);
|
|
tsv_str.add_str_int("\t", left);
|
|
tsv_str.add_str_int("\t", top);
|
|
tsv_str.add_str_int("\t", right - left);
|
|
tsv_str.add_str_int("\t", bottom - top);
|
|
tsv_str.add_str_int("\t", res_it->Confidence(RIL_WORD));
|
|
tsv_str += "\t";
|
|
|
|
// Increment counts if at end of block/paragraph/textline.
|
|
if (res_it->IsAtFinalElement(RIL_TEXTLINE, RIL_WORD)) lcnt++;
|
|
if (res_it->IsAtFinalElement(RIL_PARA, RIL_WORD)) pcnt++;
|
|
if (res_it->IsAtFinalElement(RIL_BLOCK, RIL_WORD)) bcnt++;
|
|
|
|
do {
|
|
tsv_str += res_it->GetUTF8Text(RIL_SYMBOL);
|
|
res_it->Next(RIL_SYMBOL);
|
|
} while (!res_it->Empty(RIL_BLOCK) && !res_it->IsAtBeginningOf(RIL_WORD));
|
|
tsv_str += "\n"; // end of row
|
|
wcnt++;
|
|
}
|
|
|
|
char* ret = new char[tsv_str.length() + 1];
|
|
strcpy(ret, tsv_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 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];
|
|
result[0] = '\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 preceding 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;
|
|
}
|
|
|
|
/**
|
|
* Detect the orientation of the input image and apparent script (alphabet).
|
|
* orient_deg is the detected clockwise rotation of the input image in degrees (0, 90, 180, 270)
|
|
* orient_conf is the confidence (15.0 is reasonably confident)
|
|
* script_name is an ASCII string, the name of the script, e.g. "Latin"
|
|
* script_conf is confidence level in the script
|
|
* Returns true on success and writes values to each parameter as an output
|
|
*/
|
|
bool TessBaseAPI::DetectOrientationScript(int* orient_deg, float* orient_conf, const char** script_name, float* script_conf) {
|
|
OSResults osr;
|
|
|
|
bool osd = DetectOS(&osr);
|
|
if (!osd) {
|
|
return false;
|
|
}
|
|
|
|
int orient_id = osr.best_result.orientation_id;
|
|
int script_id = osr.get_best_script(orient_id);
|
|
if (orient_conf)
|
|
*orient_conf = osr.best_result.oconfidence;
|
|
if (orient_deg)
|
|
*orient_deg = orient_id * 90; // convert quadrant to degrees
|
|
|
|
if (script_name) {
|
|
const char* script =
|
|
osr.unicharset->get_script_from_script_id(script_id);
|
|
|
|
*script_name = script;
|
|
}
|
|
|
|
if (script_conf)
|
|
*script_conf = osr.best_result.sconfidence;
|
|
|
|
return true;
|
|
}
|
|
|
|
/**
|
|
* The recognized text is returned as a char* which is coded
|
|
* as UTF8 and must be freed with the delete [] operator.
|
|
* page_number is a 0-based page index that will appear in the osd file.
|
|
*/
|
|
char* TessBaseAPI::GetOsdText(int page_number) {
|
|
int orient_deg;
|
|
float orient_conf;
|
|
const char* script_name;
|
|
float script_conf;
|
|
|
|
if (!DetectOrientationScript(&orient_deg, &orient_conf, &script_name, &script_conf))
|
|
return NULL;
|
|
|
|
// clockwise rotation needed to make the page upright
|
|
int rotate = OrientationIdToValue(orient_deg / 90);
|
|
|
|
const int kOsdBufsize = 255;
|
|
char* osd_buf = new char[kOsdBufsize];
|
|
snprintf(osd_buf, kOsdBufsize,
|
|
"Page number: %d\n"
|
|
"Orientation in degrees: %d\n"
|
|
"Rotate: %d\n"
|
|
"Orientation confidence: %.2f\n"
|
|
"Script: %s\n"
|
|
"Script confidence: %.2f\n",
|
|
page_number, orient_deg, rotate, orient_conf, script_name,
|
|
script_conf);
|
|
|
|
return osd_buf;
|
|
}
|
|
|
|
/** 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, 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();
|
|
if (tesseract_ != NULL) SetInputImage(NULL);
|
|
}
|
|
|
|
/**
|
|
* 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() {
|
|
Clear();
|
|
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;
|
|
}
|
|
}
|
|
|
|
// Clear any library-level memory caches.
|
|
// There are a variety of expensive-to-load constant data structures (mostly
|
|
// language dictionaries) that are cached globally -- surviving the Init()
|
|
// and End() of individual TessBaseAPI's. This function allows the clearing
|
|
// of these caches.
|
|
void TessBaseAPI::ClearPersistentCache() {
|
|
Dict::GlobalDawgCache()->DeleteUnusedDawgs();
|
|
}
|
|
|
|
/**
|
|
* 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);
|
|
}
|
|
// Returns true if utf8_character is defined in the UniCharset.
|
|
bool TessBaseAPI::IsValidCharacter(const char *utf8_character) {
|
|
return tesseract_->unicharset.contains_unichar(utf8_character);
|
|
}
|
|
|
|
|
|
// TODO(rays) Obsolete this function and replace with a more aptly named
|
|
// function that returns image coordinates rather than tesseract coordinates.
|
|
bool TessBaseAPI::GetTextDirection(int* out_offset, float* out_slope) {
|
|
PageIterator* it = AnalyseLayout();
|
|
if (it == NULL) {
|
|
return false;
|
|
}
|
|
int x1, x2, y1, y2;
|
|
it->Baseline(RIL_TEXTLINE, &x1, &y1, &x2, &y2);
|
|
// Calculate offset and slope (NOTE: Kind of ugly)
|
|
if (x2 <= x1) x2 = x1 + 1;
|
|
// Convert the point pair to slope/offset of the baseline (in image coords.)
|
|
*out_slope = static_cast<float>(y2 - y1) / (x2 - x1);
|
|
*out_offset = static_cast<int>(y1 - *out_slope * x1);
|
|
// Get the y-coord of the baseline at the left and right edges of the
|
|
// textline's bounding box.
|
|
int left, top, right, bottom;
|
|
if (!it->BoundingBox(RIL_TEXTLINE, &left, &top, &right, &bottom)) {
|
|
delete it;
|
|
return false;
|
|
}
|
|
int left_y = IntCastRounded(*out_slope * left + *out_offset);
|
|
int right_y = IntCastRounded(*out_slope * right + *out_offset);
|
|
// Shift the baseline down so it passes through the nearest bottom-corner
|
|
// of the textline's bounding box. This is the difference between the y
|
|
// at the lowest (max) edge of the box and the actual box bottom.
|
|
*out_offset += bottom - MAX(left_y, right_y);
|
|
// Switch back to bottom-up tesseract coordinates. Requires negation of
|
|
// the slope and height - offset for the offset.
|
|
*out_slope = -*out_slope;
|
|
*out_offset = rect_height_ - *out_offset;
|
|
delete it;
|
|
|
|
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.
|
|
*
|
|
* @param f A single function that returns the probability of the current
|
|
* "character" (in general a utf-8 string), given the context of a previous
|
|
* utf-8 string.
|
|
*/
|
|
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 set 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 (*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.
|
|
tprintf("Warning. Invalid resolution %d dpi. Using %d instead.\n",
|
|
y_res, kMinCredibleResolution);
|
|
thresholder_->SetSourceYResolution(kMinCredibleResolution);
|
|
}
|
|
PageSegMode pageseg_mode =
|
|
static_cast<PageSegMode>(
|
|
static_cast<int>(tesseract_->tessedit_pageseg_mode));
|
|
thresholder_->ThresholdToPix(pageseg_mode, pix);
|
|
thresholder_->GetImageSizes(&rect_left_, &rect_top_,
|
|
&rect_width_, &rect_height_,
|
|
&image_width_, &image_height_);
|
|
if (!thresholder_->IsBinary()) {
|
|
tesseract_->set_pix_thresholds(thresholder_->GetPixRectThresholds());
|
|
tesseract_->set_pix_grey(thresholder_->GetPixRectGrey());
|
|
} else {
|
|
tesseract_->set_pix_thresholds(NULL);
|
|
tesseract_->set_pix_grey(NULL);
|
|
}
|
|
// 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);
|
|
SavePixForCrash(estimated_res, *pix);
|
|
}
|
|
|
|
/** 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;
|
|
}
|
|
SavePixForCrash(0, 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(false, 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) {
|
|
TBOX box = tblob->bounding_box();
|
|
float x_center = (box.left() + box.right()) / 2.0f;
|
|
float baseline = row->base_line(x_center);
|
|
float scale = kBlnXHeight / row->x_height();
|
|
tblob->Normalize(NULL, NULL, NULL, x_center, baseline, scale, scale,
|
|
0.0f, static_cast<float>(kBlnBaselineOffset), false, 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);
|
|
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;
|
|
float best_rating = -100;
|
|
|
|
|
|
// Classify to get a raw choice.
|
|
BLOB_CHOICE_LIST choices;
|
|
tesseract_->AdaptiveClassifier(blob, &choices);
|
|
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();
|
|
}
|
|
}
|
|
|
|
threshold = tesseract_->matcher_good_threshold;
|
|
|
|
if (blob->outlines)
|
|
tesseract_->AdaptToChar(blob, id, kUnknownFontinfoId, threshold,
|
|
tesseract_->AdaptedTemplates);
|
|
delete blob;
|
|
}
|
|
|
|
|
|
PAGE_RES* TessBaseAPI::RecognitionPass1(BLOCK_LIST* block_list) {
|
|
PAGE_RES *page_res = new PAGE_RES(false, 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(false, 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. */
|
|
// The resulting features are returned in int_features, which must be
|
|
// of size MAX_NUM_INT_FEATURES. The number of features is returned in
|
|
// num_features (or 0 if there was a failure).
|
|
// On return feature_outline_index is filled with an index of the outline
|
|
// corresponding to each feature in int_features.
|
|
// TODO(rays) Fix the caller to out outline_counts instead.
|
|
void TessBaseAPI::GetFeaturesForBlob(TBLOB* blob,
|
|
INT_FEATURE_STRUCT* int_features,
|
|
int* num_features,
|
|
int* feature_outline_index) {
|
|
GenericVector<int> outline_counts;
|
|
GenericVector<INT_FEATURE_STRUCT> bl_features;
|
|
GenericVector<INT_FEATURE_STRUCT> cn_features;
|
|
INT_FX_RESULT_STRUCT fx_info;
|
|
tesseract_->ExtractFeatures(*blob, false, &bl_features,
|
|
&cn_features, &fx_info, &outline_counts);
|
|
if (cn_features.empty() || cn_features.size() > MAX_NUM_INT_FEATURES) {
|
|
*num_features = 0;
|
|
return; // Feature extraction failed.
|
|
}
|
|
*num_features = cn_features.size();
|
|
memcpy(int_features, &cn_features[0], *num_features * sizeof(cn_features[0]));
|
|
// TODO(rays) Pass outline_counts back and simplify the calling code.
|
|
if (feature_outline_index != NULL) {
|
|
int f = 0;
|
|
for (int i = 0; i < outline_counts.size(); ++i) {
|
|
while (f < outline_counts[i])
|
|
feature_outline_index[f++] = i;
|
|
}
|
|
}
|
|
}
|
|
|
|
// 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,
|
|
int num_max_matches,
|
|
int* unichar_ids,
|
|
float* ratings,
|
|
int* num_matches_returned) {
|
|
BLOB_CHOICE_LIST* choices = new BLOB_CHOICE_LIST;
|
|
tesseract_->AdaptiveClassifier(blob, choices);
|
|
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();
|
|
}
|
|
|
|
#ifndef NO_CUBE_BUILD
|
|
/** Return a pointer to underlying CubeRecoContext object if present. */
|
|
CubeRecoContext *TessBaseAPI::GetCubeRecoContext() const {
|
|
return (tesseract_ == NULL) ? NULL : tesseract_->GetCubeRecoContext();
|
|
}
|
|
#endif // NO_CUBE_BUILD
|
|
|
|
/** Escape a char string - remove <>&"' with HTML codes. */
|
|
STRING HOcrEscape(const char* text) {
|
|
STRING ret;
|
|
const char *ptr;
|
|
for (ptr = text; *ptr; ptr++) {
|
|
switch (*ptr) {
|
|
case '<': ret += "<"; break;
|
|
case '>': ret += ">"; break;
|
|
case '&': ret += "&"; break;
|
|
case '"': ret += """; break;
|
|
case '\'': ret += "'"; break;
|
|
default: ret += *ptr;
|
|
}
|
|
}
|
|
return ret;
|
|
}
|
|
|
|
} // namespace tesseract.
|