From 9195d2e6140acecb0312d0ccf04f8cbb98a22a87 Mon Sep 17 00:00:00 2001
From: Vladislav Sovrasov <sovrasov.vlad@gmail.com>
Date: Wed, 11 Oct 2017 14:47:52 +0300
Subject: [PATCH] text: small adjustments in samples and image preprocessing

---
 modules/text/samples/dictnet_demo.cpp | 9 ---------
 modules/text/samples/textbox_demo.cpp | 4 ++--
 modules/text/src/ocr_holistic.cpp     | 4 ++++
 modules/text/src/text_detectorCNN.cpp | 9 +++++----
 4 files changed, 11 insertions(+), 15 deletions(-)

diff --git a/modules/text/samples/dictnet_demo.cpp b/modules/text/samples/dictnet_demo.cpp
index 277a1c9be..f70f2c175 100644
--- a/modules/text/samples/dictnet_demo.cpp
+++ b/modules/text/samples/dictnet_demo.cpp
@@ -1,12 +1,3 @@
-/*
- * 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"
diff --git a/modules/text/samples/textbox_demo.cpp b/modules/text/samples/textbox_demo.cpp
index f3c292836..e6412f9f5 100644
--- a/modules/text/samples/textbox_demo.cpp
+++ b/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();
diff --git a/modules/text/src/ocr_holistic.cpp b/modules/text/src/ocr_holistic.cpp
index 77016edf2..07c4aa98f 100644
--- a/modules/text/src/ocr_holistic.cpp
+++ b/modules/text/src/ocr_holistic.cpp
@@ -1,3 +1,7 @@
+// 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"
diff --git a/modules/text/src/text_detectorCNN.cpp b/modules/text/src/text_detectorCNN.cpp
index cd624985f..23a84f015 100644
--- a/modules/text/src/text_detectorCNN.cpp
+++ b/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);
         }
      }
 };