mirror of
https://github.com/tesseract-ocr/tesseract.git
synced 2024-12-05 02:47:00 +08:00
484 lines
20 KiB
C++
484 lines
20 KiB
C++
// (C) Copyright 2017, 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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#include "include_gunit.h"
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#include "log.h" // for LOG
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#include "genericvector.h"
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#include "recodebeam.h"
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#include "matrix.h"
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#include "pageres.h"
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#include "ratngs.h"
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#include "unicharcompress.h"
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#include "normstrngs.h"
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#include "unicharset_training_utils.h"
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#include "helpers.h"
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#include "absl/strings/str_format.h" // for absl::StrFormat
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namespace tesseract {
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// Number of characters to test beam search with.
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const int kNumChars = 100;
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// Amount of extra random data to pad with after.
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const int kPadding = 64;
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// Dictionary test data.
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// The top choice is: "Gef s wordsright.".
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// The desired phrase is "Gets words right.".
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// There is a competing dictionary phrase: "Get swords right.".
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// ... due to the following errors from the network:
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// f stronger than t in "Get".
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// weak space between Gef and s and between s and words.
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// weak space between words and right.
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const char* kGWRTops[] = {"G", "e", "f", " ", "s", " ", "w", "o", "r", "d",
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"s", "", "r", "i", "g", "h", "t", ".", nullptr};
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const float kGWRTopScores[] = {0.99, 0.85, 0.87, 0.55, 0.99, 0.65,
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0.89, 0.99, 0.99, 0.99, 0.99, 0.95,
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0.99, 0.90, 0.90, 0.90, 0.95, 0.75};
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const char* kGWR2nds[] = {"C", "c", "t", "", "S", "", "W", "O", "t", "h",
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"S", " ", "t", "I", "9", "b", "f", ",", nullptr};
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const float kGWR2ndScores[] = {0.01, 0.10, 0.12, 0.42, 0.01, 0.25,
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0.10, 0.01, 0.01, 0.01, 0.01, 0.05,
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0.01, 0.09, 0.09, 0.09, 0.05, 0.25};
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const char* kZHTops[] = {"实", "学", "储", "啬", "投", "学", "生", nullptr};
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const float kZHTopScores[] = {0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98};
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const char* kZH2nds[] = {"学", "储", "投", "生", "学", "生", "实", nullptr};
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const float kZH2ndScores[] = {0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01};
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const char* kViTops[] = {"v", "ậ", "y", " ", "t", "ộ", "i", nullptr};
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const float kViTopScores[] = {0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.97};
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const char* kVi2nds[] = {"V", "a", "v", "", "l", "o", "", nullptr};
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const float kVi2ndScores[] = {0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01};
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class RecodeBeamTest : public ::testing::Test {
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protected:
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void SetUp() {
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std::locale::global(std::locale(""));
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file::MakeTmpdir();
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}
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RecodeBeamTest() : lstm_dict_(&ccutil_) {}
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~RecodeBeamTest() { lstm_dict_.End(); }
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// Loads and compresses the given unicharset.
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void LoadUnicharset(const std::string& unicharset_name) {
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std::string radical_stroke_file = file::JoinPath(LANGDATA_DIR,
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"radical-stroke.txt");
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std::string unicharset_file =
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file::JoinPath(TESTDATA_DIR, unicharset_name);
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std::string radical_data;
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CHECK_OK(file::GetContents(radical_stroke_file, &radical_data,
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file::Defaults()));
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CHECK(ccutil_.unicharset.load_from_file(unicharset_file.c_str()));
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unichar_null_char_ = ccutil_.unicharset.has_special_codes()
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? UNICHAR_BROKEN
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: ccutil_.unicharset.size();
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STRING radical_str(radical_data.c_str());
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EXPECT_TRUE(recoder_.ComputeEncoding(ccutil_.unicharset, unichar_null_char_,
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&radical_str));
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RecodedCharID code;
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recoder_.EncodeUnichar(unichar_null_char_, &code);
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encoded_null_char_ = code(0);
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// Space should encode as itself.
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recoder_.EncodeUnichar(UNICHAR_SPACE, &code);
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EXPECT_EQ(UNICHAR_SPACE, code(0));
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std::string output_name = file::JoinPath(FLAGS_test_tmpdir, "testenc.txt");
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STRING encoding = recoder_.GetEncodingAsString(ccutil_.unicharset);
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std::string encoding_str(&encoding[0], encoding.size());
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CHECK_OK(file::SetContents(output_name, encoding_str, file::Defaults()));
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LOG(INFO) << "Wrote encoding to:" << output_name << "\n";
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}
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// Loads the dictionary.
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void LoadDict(const std::string& lang) {
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std::string traineddata_name = lang + ".traineddata";
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std::string traineddata_file =
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file::JoinPath(TESTDATA_DIR, traineddata_name);
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lstm_dict_.SetupForLoad(nullptr);
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tesseract::TessdataManager mgr;
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mgr.Init(traineddata_file.c_str());
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lstm_dict_.LoadLSTM(lang.c_str(), &mgr);
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lstm_dict_.FinishLoad();
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}
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// Expects the appropriate results from the compressed_ ccutil_.unicharset.
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void ExpectCorrect(const GENERIC_2D_ARRAY<float>& output,
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const GenericVector<int>& transcription) {
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// Get the utf8 string of the transcription.
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std::string truth_utf8;
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for (int i = 0; i < transcription.size(); ++i) {
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truth_utf8 += ccutil_.unicharset.id_to_unichar(transcription[i]);
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}
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PointerVector<WERD_RES> words;
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ExpectCorrect(output, truth_utf8, nullptr, &words);
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}
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void ExpectCorrect(const GENERIC_2D_ARRAY<float>& output,
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const std::string& truth_utf8, Dict* dict,
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PointerVector<WERD_RES>* words) {
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RecodeBeamSearch beam_search(recoder_, encoded_null_char_, false, dict);
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beam_search.Decode(output, 3.5, -0.125, -25.0, nullptr);
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// Uncomment and/or change nullptr above to &ccutil_.unicharset to debug:
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// beam_search.DebugBeams(ccutil_.unicharset);
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std::vector<int> labels, xcoords;
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beam_search.ExtractBestPathAsLabels(&labels, &xcoords);
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LOG(INFO) << "Labels size = " << labels.size() << " coords "
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<< xcoords.size() << "\n";
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// Now decode using recoder_.
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std::string decoded;
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int end = 1;
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for (int start = 0; start < labels.size(); start = end) {
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RecodedCharID code;
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int index = start;
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int uni_id = INVALID_UNICHAR_ID;
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do {
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code.Set(code.length(), labels[index++]);
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uni_id = recoder_.DecodeUnichar(code);
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} while (index < labels.size() &&
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code.length() < RecodedCharID::kMaxCodeLen &&
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(uni_id == INVALID_UNICHAR_ID ||
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!recoder_.IsValidFirstCode(labels[index])));
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EXPECT_NE(INVALID_UNICHAR_ID, uni_id)
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<< "index=" << index << "/" << labels.size();
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// To the extent of truth_utf8, we expect decoded to match, but if
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// transcription is shorter, that is OK too, as we may just be testing
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// that we get a valid sequence when padded with random data.
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if (uni_id != unichar_null_char_ && decoded.size() < truth_utf8.size())
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decoded += ccutil_.unicharset.id_to_unichar(uni_id);
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end = index;
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}
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EXPECT_EQ(truth_utf8, decoded);
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// Check that ExtractBestPathAsUnicharIds does the same thing.
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std::vector<int> unichar_ids;
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std::vector<float> certainties, ratings;
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beam_search.ExtractBestPathAsUnicharIds(false, &ccutil_.unicharset,
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&unichar_ids, &certainties,
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&ratings, &xcoords);
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std::string u_decoded;
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float total_rating = 0.0f;
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for (int u = 0; u < unichar_ids.size(); ++u) {
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// To the extent of truth_utf8, we expect decoded to match, but if
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// transcription is shorter, that is OK too, as we may just be testing
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// that we get a valid sequence when padded with random data.
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if (u_decoded.size() < truth_utf8.size()) {
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const char* str = ccutil_.unicharset.id_to_unichar(unichar_ids[u]);
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total_rating += ratings[u];
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LOG(INFO) << absl::StrFormat("%d:u_id=%d=%s, c=%g, r=%g, r_sum=%g @%d", u,
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unichar_ids[u], str, certainties[u],
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ratings[u], total_rating, xcoords[u]) << "\n";
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if (str[0] == ' ') total_rating = 0.0f;
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u_decoded += str;
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}
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}
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EXPECT_EQ(truth_utf8, u_decoded);
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// Check that ExtractBestPathAsWords does the same thing.
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TBOX line_box(0, 0, 100, 10);
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for (int i = 0; i < 2; ++i) {
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beam_search.ExtractBestPathAsWords(line_box, 1.0f, false,
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&ccutil_.unicharset, words);
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std::string w_decoded;
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for (int w = 0; w < words->size(); ++w) {
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const WERD_RES* word = (*words)[w];
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if (w_decoded.size() < truth_utf8.size()) {
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if (!w_decoded.empty() && word->word->space()) w_decoded += " ";
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w_decoded += word->best_choice->unichar_string().c_str();
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}
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LOG(INFO) << absl::StrFormat("Word:%d = %s, c=%g, r=%g, perm=%d", w,
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word->best_choice->unichar_string().c_str(),
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word->best_choice->certainty(),
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word->best_choice->rating(),
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word->best_choice->permuter()) << "\n";
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}
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std::string w_trunc(w_decoded.data(), truth_utf8.size());
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if (truth_utf8 != w_trunc) {
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tesseract::NormalizeUTF8String(
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tesseract::UnicodeNormMode::kNFKD, tesseract::OCRNorm::kNormalize,
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tesseract::GraphemeNorm::kNone, w_decoded.c_str(), &w_decoded);
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w_trunc.assign(w_decoded.data(), truth_utf8.size());
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}
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EXPECT_EQ(truth_utf8, w_trunc);
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}
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}
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// Generates easy encoding of the given unichar_ids, and pads with at least
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// padding of random data.
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GENERIC_2D_ARRAY<float> GenerateRandomPaddedOutputs(
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const GenericVector<int>& unichar_ids, int padding) {
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int width = unichar_ids.size() * 2 * RecodedCharID::kMaxCodeLen;
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int num_codes = recoder_.code_range();
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GENERIC_2D_ARRAY<float> outputs(width + padding, num_codes, 0.0f);
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// Fill with random data.
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TRand random;
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for (int t = 0; t < width; ++t) {
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for (int i = 0; i < num_codes; ++i)
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outputs(t, i) = random.UnsignedRand(0.25);
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}
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int t = 0;
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for (int i = 0; i < unichar_ids.size(); ++i) {
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RecodedCharID code;
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int len = recoder_.EncodeUnichar(unichar_ids[i], &code);
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EXPECT_NE(0, len);
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for (int j = 0; j < len; ++j) {
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// Make the desired answer a clear winner.
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if (j > 0 && code(j) == code(j - 1)) {
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// We will collapse adjacent equal codes so put a null in between.
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outputs(t++, encoded_null_char_) = 1.0f;
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}
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outputs(t++, code(j)) = 1.0f;
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}
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// Put a 0 as a null char in between.
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outputs(t++, encoded_null_char_) = 1.0f;
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}
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// Normalize the probs.
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for (int t = 0; t < width; ++t) {
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double sum = 0.0;
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for (int i = 0; i < num_codes; ++i) sum += outputs(t, i);
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for (int i = 0; i < num_codes; ++i) outputs(t, i) /= sum;
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}
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return outputs;
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}
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// Encodes a utf8 string (character) as unichar_id, then recodes, and sets
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// the score for the appropriate sequence of codes, returning the ending t.
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int EncodeUTF8(const char* utf8_str, float score, int start_t, TRand* random,
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GENERIC_2D_ARRAY<float>* outputs) {
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int t = start_t;
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std::vector<int> unichar_ids;
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EXPECT_TRUE(ccutil_.unicharset.encode_string(utf8_str, true, &unichar_ids,
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nullptr, nullptr));
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if (unichar_ids.empty() || utf8_str[0] == '\0') {
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unichar_ids.clear();
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unichar_ids.push_back(unichar_null_char_);
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}
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int num_ids = unichar_ids.size();
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for (int u = 0; u < num_ids; ++u) {
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RecodedCharID code;
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int len = recoder_.EncodeUnichar(unichar_ids[u], &code);
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EXPECT_NE(0, len);
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for (int i = 0; i < len; ++i) {
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// Apply the desired score.
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(*outputs)(t++, code(i)) = score;
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if (random != nullptr &&
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t + (num_ids - u) * RecodedCharID::kMaxCodeLen < outputs->dim1()) {
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int dups = static_cast<int>(random->UnsignedRand(3.0));
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for (int d = 0; d < dups; ++d) {
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// Duplicate the desired score.
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(*outputs)(t++, code(i)) = score;
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}
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}
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}
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if (random != nullptr &&
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t + (num_ids - u) * RecodedCharID::kMaxCodeLen < outputs->dim1()) {
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int dups = static_cast<int>(random->UnsignedRand(3.0));
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for (int d = 0; d < dups; ++d) {
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// Add a random number of nulls as well.
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(*outputs)(t++, encoded_null_char_) = score;
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}
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}
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}
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return t;
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}
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// Generates an encoding of the given 4 arrays as synthetic network scores.
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// uses scores1 for chars1 and scores2 for chars2, and everything else gets
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// the leftovers shared out equally. Note that empty string encodes as the
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// null_char_.
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GENERIC_2D_ARRAY<float> GenerateSyntheticOutputs(const char* chars1[],
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const float scores1[],
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const char* chars2[],
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const float scores2[],
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TRand* random) {
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int width = 0;
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while (chars1[width] != nullptr) ++width;
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int padding = width * RecodedCharID::kMaxCodeLen;
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int num_codes = recoder_.code_range();
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GENERIC_2D_ARRAY<float> outputs(width + padding, num_codes, 0.0f);
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int t = 0;
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for (int i = 0; i < width; ++i) {
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// In case there is overlap in the codes between 1st and 2nd choice, it
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// is better to encode the 2nd choice first.
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int end_t2 = EncodeUTF8(chars2[i], scores2[i], t, random, &outputs);
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int end_t1 = EncodeUTF8(chars1[i], scores1[i], t, random, &outputs);
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// Advance t to the max end, setting everything else to the leftovers.
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int max_t = std::max(end_t1, end_t2);
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while (t < max_t) {
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double total_score = 0.0;
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for (int j = 0; j < num_codes; ++j) total_score += outputs(t, j);
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double null_remainder = (1.0 - total_score) / 2.0;
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double remainder = null_remainder / (num_codes - 2);
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if (outputs(t, encoded_null_char_) < null_remainder) {
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outputs(t, encoded_null_char_) += null_remainder;
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} else {
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remainder += remainder;
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}
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for (int j = 0; j < num_codes; ++j) {
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if (outputs(t, j) == 0.0f) outputs(t, j) = remainder;
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}
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++t;
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}
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}
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// Fill the rest with null chars.
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while (t < width + padding) {
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outputs(t++, encoded_null_char_) = 1.0f;
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}
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return outputs;
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}
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UnicharCompress recoder_;
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int unichar_null_char_ = 0;
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int encoded_null_char_ = 0;
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CCUtil ccutil_;
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Dict lstm_dict_;
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};
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TEST_F(RecodeBeamTest, DoesChinese) {
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LOG(INFO) << "Testing chi_tra" << "\n";
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LoadUnicharset("chi_tra.unicharset");
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// Correctly reproduce the first kNumchars characters from easy output.
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GenericVector<int> transcription;
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for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
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transcription.push_back(i);
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GENERIC_2D_ARRAY<float> outputs =
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GenerateRandomPaddedOutputs(transcription, kPadding);
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ExpectCorrect(outputs, transcription);
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LOG(INFO) << "Testing chi_sim" << "\n";
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LoadUnicharset("chi_sim.unicharset");
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// Correctly reproduce the first kNumchars characters from easy output.
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transcription.clear();
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for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
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transcription.push_back(i);
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outputs = GenerateRandomPaddedOutputs(transcription, kPadding);
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ExpectCorrect(outputs, transcription);
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}
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TEST_F(RecodeBeamTest, DoesJapanese) {
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LOG(INFO) << "Testing jpn" << "\n";
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LoadUnicharset("jpn.unicharset");
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// Correctly reproduce the first kNumchars characters from easy output.
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GenericVector<int> transcription;
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for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
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transcription.push_back(i);
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GENERIC_2D_ARRAY<float> outputs =
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GenerateRandomPaddedOutputs(transcription, kPadding);
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ExpectCorrect(outputs, transcription);
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}
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TEST_F(RecodeBeamTest, DoesKorean) {
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LOG(INFO) << "Testing kor" << "\n";
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LoadUnicharset("kor.unicharset");
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// Correctly reproduce the first kNumchars characters from easy output.
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GenericVector<int> transcription;
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for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
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transcription.push_back(i);
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GENERIC_2D_ARRAY<float> outputs =
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GenerateRandomPaddedOutputs(transcription, kPadding);
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ExpectCorrect(outputs, transcription);
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}
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TEST_F(RecodeBeamTest, DoesKannada) {
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LOG(INFO) << "Testing kan" << "\n";
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LoadUnicharset("kan.unicharset");
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// Correctly reproduce the first kNumchars characters from easy output.
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GenericVector<int> transcription;
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for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
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transcription.push_back(i);
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GENERIC_2D_ARRAY<float> outputs =
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GenerateRandomPaddedOutputs(transcription, kPadding);
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|
ExpectCorrect(outputs, transcription);
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|
}
|
|
|
|
TEST_F(RecodeBeamTest, DoesMarathi) {
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|
LOG(INFO) << "Testing mar" << "\n";
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|
LoadUnicharset("mar.unicharset");
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|
// Correctly reproduce the first kNumchars characters from easy output.
|
|
GenericVector<int> transcription;
|
|
for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
|
|
transcription.push_back(i);
|
|
GENERIC_2D_ARRAY<float> outputs =
|
|
GenerateRandomPaddedOutputs(transcription, kPadding);
|
|
ExpectCorrect(outputs, transcription);
|
|
}
|
|
|
|
TEST_F(RecodeBeamTest, DoesEnglish) {
|
|
LOG(INFO) << "Testing eng" << "\n";
|
|
LoadUnicharset("eng.unicharset");
|
|
// Correctly reproduce the first kNumchars characters from easy output.
|
|
GenericVector<int> transcription;
|
|
for (int i = SPECIAL_UNICHAR_CODES_COUNT; i < kNumChars; ++i)
|
|
transcription.push_back(i);
|
|
GENERIC_2D_ARRAY<float> outputs =
|
|
GenerateRandomPaddedOutputs(transcription, kPadding);
|
|
ExpectCorrect(outputs, transcription);
|
|
}
|
|
|
|
TEST_F(RecodeBeamTest, DISABLED_EngDictionary) {
|
|
LOG(INFO) << "Testing eng dictionary" << "\n";
|
|
LoadUnicharset("eng_beam.unicharset");
|
|
GENERIC_2D_ARRAY<float> outputs = GenerateSyntheticOutputs(
|
|
kGWRTops, kGWRTopScores, kGWR2nds, kGWR2ndScores, nullptr);
|
|
std::string default_str;
|
|
for (int i = 0; kGWRTops[i] != nullptr; ++i) default_str += kGWRTops[i];
|
|
PointerVector<WERD_RES> words;
|
|
ExpectCorrect(outputs, default_str, nullptr, &words);
|
|
// Now try again with the dictionary.
|
|
LoadDict("eng_beam");
|
|
ExpectCorrect(outputs, "Gets words right.", &lstm_dict_, &words);
|
|
}
|
|
|
|
TEST_F(RecodeBeamTest, DISABLED_ChiDictionary) {
|
|
LOG(INFO) << "Testing zh_hans dictionary" << "\n";
|
|
LoadUnicharset("zh_hans.unicharset");
|
|
GENERIC_2D_ARRAY<float> outputs = GenerateSyntheticOutputs(
|
|
kZHTops, kZHTopScores, kZH2nds, kZH2ndScores, nullptr);
|
|
PointerVector<WERD_RES> words;
|
|
ExpectCorrect(outputs, "实学储啬投学生", nullptr, &words);
|
|
// Each is an individual word, with permuter = top choice.
|
|
EXPECT_EQ(7, words.size());
|
|
for (int w = 0; w < words.size(); ++w) {
|
|
EXPECT_EQ(TOP_CHOICE_PERM, words[w]->best_choice->permuter());
|
|
}
|
|
// Now try again with the dictionary.
|
|
LoadDict("zh_hans");
|
|
ExpectCorrect(outputs, "实学储啬投学生", &lstm_dict_, &words);
|
|
// Number of words expected.
|
|
const int kNumWords = 5;
|
|
// Content of the words.
|
|
const char* kWords[kNumWords] = {"实学", "储", "啬", "投", "学生"};
|
|
// Permuters of the words.
|
|
const int kWordPerms[kNumWords] = {SYSTEM_DAWG_PERM, TOP_CHOICE_PERM,
|
|
TOP_CHOICE_PERM, TOP_CHOICE_PERM,
|
|
SYSTEM_DAWG_PERM};
|
|
EXPECT_EQ(kNumWords, words.size());
|
|
for (int w = 0; w < kNumWords && w < words.size(); ++w) {
|
|
EXPECT_STREQ(kWords[w], words[w]->best_choice->unichar_string().c_str());
|
|
EXPECT_EQ(kWordPerms[w], words[w]->best_choice->permuter());
|
|
}
|
|
}
|
|
|
|
// Tests that a recoder built with decomposed unicode allows true ctc
|
|
// arbitrary duplicates and inserted nulls inside the multicode sequence.
|
|
TEST_F(RecodeBeamTest, DISABLED_MultiCodeSequences) {
|
|
LOG(INFO) << "Testing duplicates in multi-code sequences" << "\n";
|
|
LoadUnicharset("vie.d.unicharset");
|
|
tesseract::SetupBasicProperties(false, true, &ccutil_.unicharset);
|
|
TRand random;
|
|
GENERIC_2D_ARRAY<float> outputs = GenerateSyntheticOutputs(
|
|
kViTops, kViTopScores, kVi2nds, kVi2ndScores, &random);
|
|
PointerVector<WERD_RES> words;
|
|
std::string truth_str;
|
|
tesseract::NormalizeUTF8String(
|
|
tesseract::UnicodeNormMode::kNFKC, tesseract::OCRNorm::kNormalize,
|
|
tesseract::GraphemeNorm::kNone, "vậy tội", &truth_str);
|
|
ExpectCorrect(outputs, truth_str, nullptr, &words);
|
|
}
|
|
|
|
} // namespace
|