text: add simple test

modules/text/CMakeLists.txt

@@ -18,3 +18,8 @@ configure_file(${CMAKE_CURRENT_SOURCE_DIR}/text_config.hpp.in
                ${CMAKE_BINARY_DIR}/text_config.hpp @ONLY)
 
 ocv_include_directories(${CMAKE_CURRENT_BINARY_DIR})
+
+ocv_add_testdata(samples/ contrib/text
+    FILES_MATCHING PATTERN "*.xml" PATTERN "*.xml.gz" REGEX "scenetext[0-9]+.jpg"
+    COMPONENT "tests"
+)

modules/text/test/test_detection.cpp

@@ -0,0 +1,91 @@
+// This file is part of OpenCV project.
+// It is subject to the license terms in the LICENSE file found in the top-level directory
+// of this distribution and at http://opencv.org/license.html.
+
+#include "test_precomp.hpp"
+#include "opencv2/imgcodecs.hpp"
+
+using namespace cv;
+using namespace cv::text;
+using namespace cvtest;
+
+namespace {
+
+// Just skip test in case of missed testdata
+static cv::String findDataFile(const String& path)
+{
+    return cvtest::findDataFile(path, false);
+}
+
+
+PARAM_TEST_CASE(Detection, std::string, bool)
+{
+    Ptr<ERFilter> er_filter1;
+    Ptr<ERFilter> er_filter2;
+
+    // SetUp doesn't handle SkipTestException
+    void InitERFilter()
+    {
+        String nm1_file = findDataFile("trained_classifierNM1.xml");
+        String nm2_file = findDataFile("trained_classifierNM2.xml");
+
+        // Create ERFilter objects with the 1st and 2nd stage default classifiers
+        er_filter1 = createERFilterNM1(loadClassifierNM1(nm1_file),16,0.00015f,0.13f,0.2f,true,0.1f);
+        er_filter2 = createERFilterNM2(loadClassifierNM2(nm2_file),0.5);
+    }
+};
+
+TEST_P(Detection, sample)
+{
+    InitERFilter();
+
+    std::string imageName = GET_PARAM(0);
+    bool anyDirection = GET_PARAM(1);
+    std::cout << "Image: " << imageName << std::endl;
+    std::cout << "Orientation: " << (anyDirection ? "any" : "horiz") << std::endl;
+    Mat src = cv::imread(findDataFile(imageName));
+    ASSERT_FALSE(src.empty());
+
+    // Extract channels to be processed individually
+    std::vector<Mat> channels;
+    computeNMChannels(src, channels);
+
+    // Append negative channels to detect ER- (bright regions over dark background)
+    for (size_t c = channels.size(); c > 0; c--)
+        channels.push_back(255 - channels[c - 1]);
+
+    std::vector<std::vector<ERStat> > regions(channels.size());
+    // Apply the default cascade classifier to each independent channel (could be done in parallel)
+    for (size_t c = 0; c < channels.size(); c++)
+    {
+        er_filter1->run(channels[c], regions[c]);
+        er_filter2->run(channels[c], regions[c]);
+    }
+
+    // Detect character groups
+    std::vector< std::vector<Vec2i> > region_groups;
+    std::vector<Rect> groups_boxes;
+    if (!anyDirection)
+        erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_HORIZ);
+    else
+        erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_ANY,
+                   findDataFile("trained_classifier_erGrouping.xml"), 0.5);
+
+    std::cout << "Found groups: " << groups_boxes.size() << std::endl;
+
+    EXPECT_GT(groups_boxes.size(), 3u);
+}
+
+INSTANTIATE_TEST_CASE_P(Text, Detection,
+    testing::Combine(
+        testing::Values(
+            "text/scenetext01.jpg",
+            "text/scenetext02.jpg",
+            "text/scenetext03.jpg",
+            "text/scenetext04.jpg",
+            "text/scenetext05.jpg",
+            "text/scenetext06.jpg"
+        ),
+        testing::Bool()
+    ));
+}

modules/text/test/test_main.cpp

@@ -0,0 +1,6 @@
+#include "test_precomp.hpp"
+
+CV_TEST_MAIN("",
+    cvtest::addDataSearchSubDirectory("contrib"),
+    cvtest::addDataSearchSubDirectory("contrib/text")
+)

modules/text/test/test_precomp.hpp

@@ -0,0 +1,8 @@
+#ifndef __OPENCV_TEST_TEXT_PRECOMP_HPP__
+#define __OPENCV_TEST_TEXT_PRECOMP_HPP__
+
+#include "opencv2/core.hpp"
+#include "opencv2/ts.hpp"
+#include "opencv2/text.hpp"
+
+#endif