Add sample script

modules/text/samples/textbox_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"
+
+#include  <sstream>
+#include  <vector>
+#include  <iostream>
+#include  <iomanip>
+#include  <fstream>
+
+inline std::string getHelpStr(std::string progFname){
+    std::stringstream out;
+    out << "    Demo of text detection CNN for text detection." << std::endl;
+    out << "    Max Jaderberg et al.: Reading Text in the Wild with Convolutional Neural Networks, IJCV 2015"<<std::endl<<std::endl;
+
+    out << "    Usage: " << progFname << " <output_file> <input_image>" << std::endl;
+    out << "    Caffe Model files  (textbox.caffemodel, textbox_deploy.prototxt)"<<std::endl;
+    out << "      must be in the current directory." << std::endl << std::endl;
+
+    out << "    Obtaining Caffe Model files in linux shell:"<<std::endl;
+    out << "    wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg.caffemodel"<<std::endl;
+    out << "    wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg_deploy.prototxt"<<std::endl;
+    out << "    wget http://nicolaou.homouniversalis.org/assets/vgg_text/dictnet_vgg_labels.txt"<<std::endl<<std::endl;
+    return out.str();
+}
+
+inline bool fileExists (std::string filename) {
+    std::ifstream f(filename.c_str());
+    return f.good();
+}
+void textbox_draw(cv::Mat &src, std::vector<cv::Rect>  &groups,std::vector<float> &probs,std::vector<cv::String> wordList,float thres=0.6)
+{
+    for (int i=0;i<(int)groups.size(); i++)
+    {
+        if(probs[i]>thres)
+        {
+            if (src.type() == CV_8UC3)
+            {
+                cv::rectangle(src,groups.at(i).tl(),groups.at(i).br(),cv::Scalar( 0, 255, 255 ), 3, 8 );
+                cv::putText(src, wordList[i],groups.at(i).tl() , cv::FONT_HERSHEY_PLAIN, 1, cv::Scalar( 0,0,255 ));
+            }
+            else
+                rectangle(src,groups.at(i).tl(),groups.at(i).br(),cv::Scalar( 255 ), 3, 8 );
+        }
+    }
+}
+
+
+int main(int argc, const char * argv[]){
+    if(!cv::text::cnn_config::caffe_backend::getCaffeAvailable()){
+        std::cout<<"The text module was compiled without Caffe which is the only available DeepCNN backend.\nAborting!\n";
+        exit(1);
+    }
+    //set to true if you have a GPU with more than 3GB
+    cv::text::cnn_config::caffe_backend::setCaffeGpuMode(false);
+
+    if (argc < 3){
+        std::cout<<getHelpStr(argv[0]);
+        std::cout<<"Insufiecient parameters. Aborting!"<<std::endl;
+        exit(1);
+    }
+
+    if (!fileExists("textbox.caffemodel") ||
+            !fileExists("textbox_deploy.prototxt")){
+           // !fileExists("dictnet_vgg_labels.txt"))
+
+        std::cout<<getHelpStr(argv[0]);
+        std::cout<<"Model files not found in the current directory. Aborting!"<<std::endl;
+        exit(1);
+    }
+
+    if (fileExists(argv[1])){
+        std::cout<<getHelpStr(argv[0]);
+        std::cout<<"Output file must not exist. Aborting!"<<std::endl;
+        exit(1);
+    }
+
+    cv::Mat image;
+    image = cv::imread(cv::String(argv[2]));
+
+
+    std::cout<<"Starting Text Box Demo"<<std::endl;
+    cv::Ptr<cv::text::textDetector> textSpotter=cv::text::textDetector::create(
+                "textbox_deploy.prototxt","textbox.caffemodel");
+
+    //cv::Ptr<cv::text::textDetector> wordSpotter=
+      //      cv::text::textDetector::create(cnn);
+    std::cout<<"Created Text Spotter with text Boxes";
+
+    std::vector<cv::Rect> bbox;
+    std::vector<float> outProbabillities;
+    textSpotter->textDetectInImage(image,bbox,outProbabillities);
+   // textbox_draw(image, bbox,outProbabillities);
+    float thres =0.6;
+    std::vector<cv::Mat> imageList;
+    for(int imageIdx=0;imageIdx<(int)bbox.size();imageIdx++){
+        if(outProbabillities[imageIdx]>thres){
+            imageList.push_back(image(bbox.at(imageIdx)));
+        }
+
+    }
+    // call dict net here for all detected parts
+    cv::Ptr<cv::text::DeepCNN> cnn=cv::text::DeepCNN::createDictNet(
+                "dictnet_vgg_deploy.prototxt","dictnet_vgg.caffemodel");
+
+    cv::Ptr<cv::text::OCRHolisticWordRecognizer> wordSpotter=
+            cv::text::OCRHolisticWordRecognizer::create(cnn,"dictnet_vgg_labels.txt");
+
+    std::vector<cv::String> wordList;
+    std::vector<double> wordProbabillities;
+    wordSpotter->recogniseImageBatch(imageList,wordList,wordProbabillities);
+    // write the output in file
+    std::ofstream out;
+    out.open(argv[1]);
+
+
+    for (int i=0;i<(int)wordList.size(); i++)
+    {
+        cv::Point tl_ = bbox.at(i).tl();
+        cv::Point br_ = bbox.at(i).br();
+
+        out<<argv[2]<<","<<tl_.x<<","<<tl_.y<<","<<tl_.y<<","<<tl_.y<<","<<br_.x<<","<<br_.y<<","<<wordList[i]<<std::endl;
+
+    }
+    out.close();
+    textbox_draw(image, bbox,outProbabillities,wordList);
+
+
+    cv::imshow("TextBox Demo",image);
+    std::cout << "Done!" << std::endl << std::endl;
+    std::cout << "Press any key to exit." << std::endl << std::endl;
+    if ((cv::waitKey()&0xff) == ' ')
+        return 0;
+
+
+}
+