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https://github.com/tesseract-ocr/tesseract.git
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d8d9b390d1
git-svn-id: https://tesseract-ocr.googlecode.com/svn/trunk@961 d0cd1f9f-072b-0410-8dd7-cf729c803f20
72 lines
2.4 KiB
C++
72 lines
2.4 KiB
C++
///////////////////////////////////////////////////////////////////////
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// File: par_control.cpp
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// Description: Control code for parallel implementation.
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// Author: Ray Smith
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// Created: Mon Nov 04 13:23:15 PST 2013
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//
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// (C) Copyright 2013, 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 "tesseractclass.h"
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namespace tesseract {
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struct BlobData {
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BlobData() : blob(NULL), choices(NULL) {}
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BlobData(int index, Tesseract* tess, const WERD_RES& word)
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: blob(word.chopped_word->blobs[index]),
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tesseract(tess),
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choices(&(*word.ratings)(index, index)) {}
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TBLOB* blob;
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Tesseract* tesseract;
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BLOB_CHOICE_LIST** choices;
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};
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void Tesseract::PrerecAllWordsPar(const GenericVector<WordData>& words) {
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// Prepare all the blobs.
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GenericVector<BlobData> blobs;
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for (int w = 0; w < words.size(); ++w) {
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if (words[w].word->ratings != NULL &&
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words[w].word->ratings->get(0, 0) == NULL) {
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for (int b = 0; b < words[w].word->chopped_word->NumBlobs(); ++b) {
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blobs.push_back(BlobData(b, this, *words[w].word));
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}
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for (int s = 0; s < words[w].lang_words.size(); ++s) {
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const WERD_RES& word = words[w].lang_words[s];
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for (int b = 0; b < word.chopped_word->NumBlobs(); ++b) {
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blobs.push_back(BlobData(b, sub_langs_[s], word));
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}
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}
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}
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}
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// Pre-classify all the blobs.
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if (tessedit_parallelize > 1) {
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#pragma omp parallel for num_threads(10)
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for (int b = 0; b < blobs.size(); ++b) {
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*blobs[b].choices =
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blobs[b].tesseract->classify_blob(blobs[b].blob, "par", White, NULL);
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}
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} else {
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// TODO(AMD) parallelize this.
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for (int b = 0; b < blobs.size(); ++b) {
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*blobs[b].choices =
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blobs[b].tesseract->classify_blob(blobs[b].blob, "par", White, NULL);
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}
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}
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}
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} // namespace tesseract.
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