text: small adjustments in samples and image preprocessing

modules/text/samples/dictnet_demo.cpp

-/*
- * dictnet_demo.cpp
- *
- * Demonstrates simple use of the holistic word classifier in C++
- *
- * Created on: June 26, 2016
- *     Author: Anguelos Nicolaou <anguelos.nicolaou AT gmail.com>
- */
-
 #include  "opencv2/text.hpp"
 #include  "opencv2/highgui.hpp"
 #include  "opencv2/imgproc.hpp"

modules/text/samples/textbox_demo.cpp

@@ -14,14 +14,14 @@ std::string getHelpStr(const std::string& progFname)
 {
     std::stringstream out;
     out << "    Demo of text detection CNN for text detection." << std::endl
-        << "    Max Jaderberg et al.: Reading Text in the Wild with Convolutional Neural Networks, IJCV 2015"<<std::endl<<std::endl
+        << "    Minghui Liao, Baoguang Shi, Xiang Bai, Xinggang Wang, Wenyu Liu: TextBoxes: A Fast Text Detector with a Single Deep Neural Network, AAAI2017\n\n"
         << "    Usage: " << progFname << " <output_file> <input_image>" << std::endl
         << "    Caffe Model files  (textbox.prototxt, TextBoxes_icdar13.caffemodel)"<<std::endl
         << "      must be in the current directory. See the documentation of text::TextDetectorCNN class to get download links." << std::endl;
     return out.str();
 }
 
-bool fileExists (std::string filename)
+bool fileExists (const std::string& filename)
 {
     std::ifstream f(filename.c_str());
     return f.good();

modules/text/src/ocr_holistic.cpp

+// 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 "precomp.hpp"
 #include "opencv2/imgproc.hpp"
 #include "opencv2/core.hpp"

modules/text/src/text_detectorCNN.cpp

@@ -5,12 +5,11 @@
 #include "precomp.hpp"
 #include "opencv2/imgproc.hpp"
 #include "opencv2/core.hpp"
+#include "opencv2/dnn.hpp"
 
 #include <fstream>
 #include <algorithm>
 
-#include "opencv2/dnn.hpp"
-
 using namespace cv::dnn;
 
 namespace cv
@@ -75,20 +74,22 @@ public:
     void detect(InputArray inputImage_, std::vector<Rect>& Bbox, std::vector<float>& confidence)
     {
         CV_Assert(inputImage_.channels() == inputChannelCount_);
-        Mat inputImage = inputImage_.getMat().clone();
+        Size inputSize = inputImage_.getMat().size();
         Bbox.resize(0);
         confidence.resize(0);
 
         for(size_t i = 0; i < sizes_.size(); i++)
         {
             Size inputGeometry = sizes_[i];
+            Mat inputImage = inputImage_.getMat().clone();
+            resize(inputImage, inputImage, inputGeometry);
             net_.setInput(blobFromImage(inputImage, 1, inputGeometry, Scalar(123, 117, 104)), "data");
             Mat outputNet = net_.forward();
             int nbrTextBoxes = outputNet.size[2];
             int nCol = outputNet.size[3];
             int outputChannelCount = outputNet.size[1];
             CV_Assert(outputChannelCount == 1);
-            getOutputs((float*)(outputNet.data), nbrTextBoxes, nCol, Bbox, confidence, inputImage.size());
+            getOutputs((float*)(outputNet.data), nbrTextBoxes, nCol, Bbox, confidence, inputSize);
         }
      }
 };