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// (C) Copyright 2017, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "include_gunit.h"
#include "cycletimer.h" // for CycleTimer
#include "log.h" // for LOG
#include "ocrblock.h" // for class BLOCK
#include "pageres.h"
#include <tesseract/baseapi.h>
#include <allheaders.h>
#include "gmock/gmock-matchers.h"
#include <memory>
#include <regex>
#include <string>
#include <vector>
namespace tesseract {
using ::testing::ContainsRegex;
using ::testing::HasSubstr;
static const char *langs[] = {"eng", "vie", "hin", "ara", nullptr};
static const char *image_files[] = {"HelloGoogle.tif", "viet.tif", "raaj.tif", "arabic.tif",
nullptr};
static const char *gt_text[] = {"Hello Google", "\x74\x69\xe1\xba\xbf\x6e\x67",
"\xe0\xa4\xb0\xe0\xa4\xbe\xe0\xa4\x9c",
"\xd8\xa7\xd9\x84\xd8\xb9\xd8\xb1\xd8\xa8\xd9\x8a", nullptr};
class FriendlyTessBaseAPI : public tesseract::TessBaseAPI {
FRIEND_TEST(TesseractTest, LSTMGeometryTest);
};
std::string GetCleanedTextResult(tesseract::TessBaseAPI *tess, Image pix) {
tess->SetImage(pix);
char *result = tess->GetUTF8Text();
std::string ocr_result = result;
delete[] result;
trim(ocr_result);
return ocr_result;
}
// The fixture for testing Tesseract.
class TesseractTest : public testing::Test {
protected:
static std::string TestDataNameToPath(const std::string &name) {
return file::JoinPath(TESTING_DIR, name);
}
static std::string TessdataPath() {
return TESSDATA_DIR;
}
};
// Test static TessBaseAPI (like it is used by tesserocr).
TEST_F(TesseractTest, StaticTessBaseAPI) {
static tesseract::TessBaseAPI api;
api.End();
}
// Tests that Tesseract gets exactly the right answer on phototest.
TEST_F(TesseractTest, BasicTesseractTest) {
tesseract::TessBaseAPI api;
std::string truth_text;
std::string ocr_text;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) != -1) {
Image src_pix = pixRead(TestDataNameToPath("phototest.tif").c_str());
CHECK(src_pix);
ocr_text = GetCleanedTextResult(&api, src_pix);
CHECK_OK(
file::GetContents(TestDataNameToPath("phototest.gold.txt"), &truth_text, file::Defaults()));
trim(truth_text);
EXPECT_STREQ(truth_text.c_str(), ocr_text.c_str());
src_pix.destroy();
} else {
// eng.traineddata not found.
GTEST_SKIP();
}
}
// Test that api.GetComponentImages() will return a set of images for
// paragraphs even if text recognition was not run.
TEST_F(TesseractTest, IteratesParagraphsEvenIfNotDetected) {
tesseract::TessBaseAPI api;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) != -1) {
api.SetPageSegMode(tesseract::PSM_SINGLE_BLOCK);
api.SetVariable("paragraph_debug_level", "3");
#if 0 // TODO: b622.png is missing
Pix* src_pix = pixRead(TestDataNameToPath("b622.png").c_str());
CHECK(src_pix);
api.SetImage(src_pix);
Boxa* para_boxes =
api.GetComponentImages(tesseract::RIL_PARA, true, nullptr, nullptr);
EXPECT_TRUE(para_boxes != nullptr);
Boxa* block_boxes =
api.GetComponentImages(tesseract::RIL_BLOCK, true, nullptr, nullptr);
EXPECT_TRUE(block_boxes != nullptr);
// TODO(eger): Get paragraphs out of this page pre-text.
EXPECT_GE(boxaGetCount(para_boxes), boxaGetCount(block_boxes));
boxaDestroy(&block_boxes);
boxaDestroy(¶_boxes);
src_pix.destroy();
#endif
} else {
// eng.traineddata not found.
GTEST_SKIP();
}
}
// We should get hOCR output and not seg fault, even if the api caller doesn't
// call SetInputName().
TEST_F(TesseractTest, HOCRWorksWithoutSetInputName) {
tesseract::TessBaseAPI api;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
// eng.traineddata not found.
GTEST_SKIP();
}
Image src_pix = pixRead(TestDataNameToPath("HelloGoogle.tif").c_str());
CHECK(src_pix);
api.SetImage(src_pix);
char *result = api.GetHOCRText(0);
EXPECT_TRUE(result != nullptr);
EXPECT_THAT(result, HasSubstr("Hello"));
EXPECT_THAT(result, HasSubstr("<div class='ocr_page'"));
delete[] result;
src_pix.destroy();
}
// hOCR output should contain baseline info for upright textlines.
TEST_F(TesseractTest, HOCRContainsBaseline) {
tesseract::TessBaseAPI api;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
// eng.traineddata not found.
GTEST_SKIP();
}
Image src_pix = pixRead(TestDataNameToPath("HelloGoogle.tif").c_str());
CHECK(src_pix);
api.SetInputName("HelloGoogle.tif");
api.SetImage(src_pix);
char *result = api.GetHOCRText(0);
EXPECT_TRUE(result != nullptr);
EXPECT_THAT(result, HasSubstr("Hello"));
EXPECT_TRUE(std::regex_search(
result, std::regex{"<span class='ocr_line'[^>]* baseline [-.0-9]+ [-.0-9]+"}));
delete[] result;
src_pix.destroy();
}
// Tests that Tesseract gets exactly the right answer on some page numbers.
TEST_F(TesseractTest, AdaptToWordStrTest) {
#ifdef DISABLED_LEGACY_ENGINE
// Skip test because TessBaseAPI::AdaptToWordStr is missing.
GTEST_SKIP();
#else
static const char *kTrainingPages[] = {"136.tif", "256.tif", "410.tif", "432.tif", "540.tif",
"692.tif", "779.tif", "793.tif", "808.tif", "815.tif",
"12.tif", "12.tif", nullptr};
static const char *kTrainingText[] = {"1 3 6", "2 5 6", "4 1 0", "4 3 2", "5 4 0",
"6 9 2", "7 7 9", "7 9 3", "8 0 8", "8 1 5",
"1 2", "1 2", nullptr};
static const char *kTestPages[] = {"324.tif", "433.tif", "12.tif", nullptr};
static const char *kTestText[] = {"324", "433", "12", nullptr};
tesseract::TessBaseAPI api;
std::string truth_text;
std::string ocr_text;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_TESSERACT_ONLY) == -1) {
// eng.traineddata not found.
GTEST_SKIP();
}
api.SetVariable("matcher_sufficient_examples_for_prototyping", "1");
api.SetVariable("classify_class_pruner_threshold", "220");
// Train on the training text.
for (int i = 0; kTrainingPages[i] != nullptr; ++i) {
std::string image_file = TestDataNameToPath(kTrainingPages[i]);
Image src_pix = pixRead(image_file.c_str());
CHECK(src_pix);
api.SetImage(src_pix);
EXPECT_TRUE(api.AdaptToWordStr(tesseract::PSM_SINGLE_WORD, kTrainingText[i]))
<< "Failed to adapt to text \"" << kTrainingText[i] << "\" on image " << image_file;
src_pix.destroy();
}
// Test the test text.
api.SetVariable("tess_bn_matching", "1");
api.SetPageSegMode(tesseract::PSM_SINGLE_WORD);
for (int i = 0; kTestPages[i] != nullptr; ++i) {
Image src_pix = pixRead(TestDataNameToPath(kTestPages[i]).c_str());
CHECK(src_pix);
ocr_text = GetCleanedTextResult(&api, src_pix);
trim(truth_text);
EXPECT_STREQ(kTestText[i], ocr_text.c_str());
src_pix.destroy();
}
#endif
}
// Tests that LSTM gets exactly the right answer on phototest.
TEST_F(TesseractTest, BasicLSTMTest) {
tesseract::TessBaseAPI api;
std::string truth_text;
std::string ocr_text;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_LSTM_ONLY) == -1) {
// eng.traineddata not found.
GTEST_SKIP();
}
Image src_pix = pixRead(TestDataNameToPath("phototest_2.tif").c_str());
CHECK(src_pix);
ocr_text = GetCleanedTextResult(&api, src_pix);
CHECK_OK(
file::GetContents(TestDataNameToPath("phototest.gold.txt"), &truth_text, file::Defaults()));
trim(truth_text);
EXPECT_STREQ(truth_text.c_str(), ocr_text.c_str());
src_pix.destroy();
}
// Test that LSTM's character bounding boxes are properly converted to
// Tesseract structures. Note that we can't guarantee that LSTM's
// character boxes fall completely within Tesseract's word box because
// the baseline denormalization/normalization transforms may introduce
// errors due to float/int conversions (e.g., see OUTLINE::move() in
// ccstruct/poutline.h) Instead, we do a loose check.
TEST_F(TesseractTest, LSTMGeometryTest) {
Image src_pix = pixRead(TestDataNameToPath("deslant.tif").c_str());
FriendlyTessBaseAPI api;
if (api.Init(TessdataPath().c_str(), "eng", tesseract::OEM_LSTM_ONLY) == -1) {
// eng.traineddata not found.
GTEST_SKIP();
}
api.SetImage(src_pix);
ASSERT_EQ(api.Recognize(nullptr), 0);
const PAGE_RES *page_res = api.GetPageRes();
PAGE_RES_IT page_res_it(const_cast<PAGE_RES *>(page_res));
page_res_it.restart_page();
BLOCK *block = page_res_it.block()->block;
CHECK(block);
// extract word and character boxes for each word
for (page_res_it.restart_page(); page_res_it.word() != nullptr; page_res_it.forward()) {
WERD_RES *word = page_res_it.word();
CHECK(word);
CHECK(word->best_choice);
CHECK_GT(word->best_choice->length(), 0);
CHECK(word->word);
CHECK(word->box_word);
// tesseract's word box
TBOX tess_blob_box;
tess_blob_box = word->word->bounding_box();
tess_blob_box.rotate(block->re_rotation());
// verify that each of LSTM's character boxes lies close to within
// tesseract's word box
for (int i = 0; i < word->box_word->length(); ++i) {
TBOX lstm_blob_box = word->box_word->BlobBox(i);
// LSTM character box should not spill out of tesseract word box
// by more than a few pixels in any direction
EXPECT_LT(tess_blob_box.left() - lstm_blob_box.left(), 5);
EXPECT_LT(lstm_blob_box.right() - tess_blob_box.right(), 5);
EXPECT_LT(tess_blob_box.bottom() - lstm_blob_box.bottom(), 5);
EXPECT_LT(lstm_blob_box.top() - tess_blob_box.top(), 5);
}
}
src_pix.destroy();
}
TEST_F(TesseractTest, InitConfigOnlyTest) {
// Languages for testing initialization.
const char *langs[] = {"eng", "chi_tra", "jpn", "vie"};
std::unique_ptr<tesseract::TessBaseAPI> api;
CycleTimer timer;
for (auto &lang : langs) {
api = std::make_unique<tesseract::TessBaseAPI>();
timer.Restart();
EXPECT_EQ(0, api->Init(TessdataPath().c_str(), lang, tesseract::OEM_TESSERACT_ONLY));
timer.Stop();
LOG(INFO) << "Lang " << lang << " took " << timer.GetInMs() << "ms in regular init";
}
// Init variables to set for config-only initialization.
std::vector<std::string> vars_vec, vars_values;
vars_vec.emplace_back("tessedit_init_config_only");
vars_values.emplace_back("1");
LOG(INFO) << "Switching to config only initialization:";
for (auto &lang : langs) {
api = std::make_unique<tesseract::TessBaseAPI>();
timer.Restart();
EXPECT_EQ(0, api->Init(TessdataPath().c_str(), lang, tesseract::OEM_TESSERACT_ONLY, nullptr, 0,
&vars_vec, &vars_values, false));
timer.Stop();
LOG(INFO) << "Lang " << lang << " took " << timer.GetInMs() << "ms in config-only init";
}
}
// Tests if two instances of Tesseract/LSTM can co-exist in the same thread.
// NOTE: This is not an exhaustive test and current support for multiple
// instances in Tesseract is fragile. This test is intended largely as a means
// of detecting and guarding against the existing support being possibly broken
// by future CLs. TessBaseAPI instances are initialized using the default
// OEM_DEFAULT mode.
TEST(TesseractInstanceTest, TestMultipleTessInstances) {
int num_langs = 0;
while (langs[num_langs] != nullptr) {
++num_langs;
}
const std::string kTessdataPath = TESSDATA_DIR;
// Preload images and verify that OCR is correct on them individually.
std::vector<Image > pix(num_langs);
for (int i = 0; i < num_langs; ++i) {
std::string tracestring = "Single instance test with lang = ";
tracestring += langs[i];
SCOPED_TRACE(tracestring);
std::string path = file::JoinPath(TESTING_DIR, image_files[i]);
pix[i] = pixRead(path.c_str());
QCHECK(pix[i] != nullptr) << "Could not read " << path;
tesseract::TessBaseAPI tess;
EXPECT_EQ(0, tess.Init(kTessdataPath.c_str(), langs[i]));
std::string ocr_result = GetCleanedTextResult(&tess, pix[i]);
EXPECT_STREQ(gt_text[i], ocr_result.c_str());
}
// Process the images in all pairwise combinations of associated languages.
std::string ocr_result[2];
for (int i = 0; i < num_langs; ++i) {
for (int j = i + 1; j < num_langs; ++j) {
tesseract::TessBaseAPI tess1, tess2;
tess1.Init(kTessdataPath.c_str(), langs[i]);
tess2.Init(kTessdataPath.c_str(), langs[j]);
ocr_result[0] = GetCleanedTextResult(&tess1, pix[i]);
ocr_result[1] = GetCleanedTextResult(&tess2, pix[j]);
EXPECT_FALSE(strcmp(gt_text[i], ocr_result[0].c_str()) ||
strcmp(gt_text[j], ocr_result[1].c_str()))
<< "OCR failed on language pair " << langs[i] << "-" << langs[j];
}
}
for (int i = 0; i < num_langs; ++i) {
pix[i].destroy();
}
}
// Tests whether Tesseract parameters are correctly set for the two instances.
TEST(TesseractInstanceTest, TestMultipleTessInstanceVariables) {
std::string illegal_name = "an_illegal_name";
std::string langs[2] = {"eng", "hin"};
std::string int_param_name = "tessedit_pageseg_mode";
int int_param[2] = {1, 2};
std::string int_param_str[2] = {"1", "2"};
std::string bool_param_name = "tessedit_ambigs_training";
bool bool_param[2] = {false, true};
std::string bool_param_str[2] = {"F", "T"};
std::string str_param_name = "tessedit_char_blacklist";
std::string str_param[2] = {"abc", "def"};
std::string double_param_name = "segment_penalty_dict_frequent_word";
std::string double_param_str[2] = {"0.01", "2"};
double double_param[2] = {0.01, 2};
const std::string kTessdataPath = TESSDATA_DIR;
tesseract::TessBaseAPI tess1, tess2;
for (int i = 0; i < 2; ++i) {
tesseract::TessBaseAPI *api = (i == 0) ? &tess1 : &tess2;
api->Init(kTessdataPath.c_str(), langs[i].c_str());
api->SetVariable(illegal_name.c_str(), "none");
api->SetVariable(int_param_name.c_str(), int_param_str[i].c_str());
api->SetVariable(bool_param_name.c_str(), bool_param_str[i].c_str());
api->SetVariable(str_param_name.c_str(), str_param[i].c_str());
api->SetVariable(double_param_name.c_str(), double_param_str[i].c_str());
}
for (int i = 0; i < 2; ++i) {
tesseract::TessBaseAPI *api = (i == 0) ? &tess1 : &tess2;
EXPECT_FALSE(api->GetStringVariable(illegal_name.c_str()));
int intvar;
EXPECT_TRUE(api->GetIntVariable(int_param_name.c_str(), &intvar));
EXPECT_EQ(int_param[i], intvar);
bool boolvar;
EXPECT_TRUE(api->GetBoolVariable(bool_param_name.c_str(), &boolvar));
EXPECT_EQ(bool_param[i], boolvar);
EXPECT_STREQ(str_param[i].c_str(), api->GetStringVariable(str_param_name.c_str()));
double doublevar;
EXPECT_TRUE(api->GetDoubleVariable(double_param_name.c_str(), &doublevar));
EXPECT_EQ(double_param[i], doublevar);
}
}
} // namespace tesseract
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