simple cleaning and added comments

modules/text/include/opencv2/text/erfilter.hpp

@@ -65,6 +65,7 @@ component tree of the image. :
  */
 struct CV_EXPORTS ERStat
 {
+
 public:
     //! Constructor
     explicit ERStat(int level = 256, int pixel = 0, int x = 0, int y = 0);

modules/text/src/ocr_holistic.cpp

@@ -459,56 +459,6 @@ protected:
 #endif
     }
 
-//    void process_(Mat inputImage, Mat &outputMat)
-//    {
-//        // do forward pass and stores the output in outputMat
-//        //Process one image
-//        CV_Assert(this->minibatchSz_==1);
-//        //CV_Assert(outputMat.isContinuous());
-
-//#ifdef HAVE_CAFFE
-//        net_->input_blobs()[0]->Reshape(1, this->channelCount_,this->inputGeometry_.height,this->inputGeometry_.width);
-//        net_->Reshape();
-//        float* inputBuffer=net_->input_blobs()[0]->mutable_cpu_data();
-//        float* inputData=inputBuffer;
-
-//        std::vector<Mat> input_channels;
-//        Mat preprocessed;
-//        // if the image have multiple color channels the input layer should be populated accordingly
-//        for (int channel=0;channel < this->channelCount_;channel++){
-
-//            cv::Mat netInputWraped(this->inputGeometry_.height, this->inputGeometry_.width, CV_32FC1, inputData);
-//            input_channels.push_back(netInputWraped);
-//            //input_data += width * height;
-//            inputData+=(this->inputGeometry_.height*this->inputGeometry_.width);
-//        }
-//        this->preprocess(inputImage,preprocessed);
-//        split(preprocessed, input_channels);
-
-//        //preprocessed.copyTo(netInputWraped);
-
-
-//        this->net_->Forward();
-//        const float* outputNetData=net_->output_blobs()[0]->cpu_data();
-//        // const float* outputNetData1=net_->output_blobs()[1]->cpu_data();
-
-
-
-
-//        this->outputGeometry_ = Size(net_->output_blobs()[0]->width(),net_->output_blobs()[0]->height());
-//        int outputSz = this->outputSize_ * this->outputGeometry_.height * this->outputGeometry_.width;
-//        outputMat.create(this->outputGeometry_.height , this->outputGeometry_.width,CV_32FC1);
-//        float*outputMatData=(float*)(outputMat.data);
-
-//        memcpy(outputMatData,outputNetData,sizeof(float)*outputSz);
-
-
-
-//#endif
-//    }
-
-
-
 #ifdef HAVE_CAFFE
     Ptr<caffe::Net<float> > net_;
 #endif
@@ -587,15 +537,6 @@ public:
         inputImageList.push_back(image.getMat());
         classifyBatch(inputImageList,classProbabilities);
     }
-//    void detect(InputArray image, OutputArray Bbox_prob)
-//    {
-
-//        Bbox_prob.create(this->outputGeometry_,CV_32F); // dummy initialization is it needed
-//        Mat outputMat = Bbox_prob.getMat();
-//        process_(image.getMat(),outputMat);
-//        //copy back to outputArray
-//        outputMat.copyTo(Bbox_prob);
-//    }
 
     void classifyBatch(InputArrayOfArrays inputImageList, OutputArray classProbabilities)
     {

modules/text/src/text_detector.cpp

@@ -74,7 +74,7 @@ public:
     void textDetectInImage(InputArray inputImage,CV_OUT std::vector<Rect>& Bbox,CV_OUT std::vector<float>& confidence)
     {
                 Mat netOutput;
-                // call the detect function of deepCNN class
+                // call the detect function of deepTextCNN class
                 this->classifier_->detect(inputImage,netOutput);
                // get the output geometry i.e height and width of output blob from caffe
                 Size OutputGeometry_ = this->classifier_->getOutputGeometry();
@@ -102,12 +102,11 @@ public:
              int component_level=0)
     {
         CV_Assert(component_level==OCR_LEVEL_WORD);//Componnents not applicable for word spotting
-        //double confidence;
-        //String transcription;
+
         std::vector<Rect> bbox;
         std::vector<float> score;
         textDetectInImage(image,bbox,score);
-        //output_text=transcription.c_str();
+
         if(component_rects!=NULL)
         {
             component_rects->resize(bbox.size());  // should be a user behavior

modules/text/src/text_detectorCNN.cpp

@@ -26,27 +26,6 @@ inline bool fileExists (String filename) {
     return f.good();
 }
 
-//************************************************************************************
-//******************   TextImageClassifier   *****************************************
-//************************************************************************************
-
-//void TextImageClassifier::preprocess(const Mat& input,Mat& output)
-//{
-//    this->preprocessor_->preprocess_(input,output,this->inputGeometry_,this->channelCount_);
-//}
-
-//void TextImageClassifier::setPreprocessor(Ptr<ImagePreprocessor> ptr)
-//{
-//    CV_Assert(!ptr.empty());
-//    preprocessor_=ptr;
-//}
-
-//Ptr<ImagePreprocessor> TextImageClassifier::getPreprocessor()
-//{
-//    return preprocessor_;
-//}
-
-
 class DeepCNNTextDetectorCaffeImpl: public DeepCNNTextDetector{
 protected:
 
@@ -54,9 +33,7 @@ protected:
     void process_(Mat inputImage, Mat &outputMat)
     {
         // do forward pass and stores the output in outputMat
-        //Process one image
-        // CV_Assert(this->outputGeometry_.batchSize==1);
-        //CV_Assert(outputMat.isContinuous());
+
 
 #ifdef HAVE_CAFFE
         net_->input_blobs()[0]->Reshape(1, this->inputChannelCount_,this->inputGeometry_.height,this->inputGeometry_.width);
@@ -191,12 +168,6 @@ public:
         outputMat.copyTo(Bbox_prob);
     }
 
-
-
-    //int getOutputSize()
-    //{
-    //  return this->outputSize_;
-    //}
     Size getOutputGeometry()
     {
         return this->outputGeometry_;
@@ -290,54 +261,7 @@ void DeepCNNTextDetector::preprocess(const Mat& input,Mat& output)
     this->preprocessor_->preprocess(input,output,inputHtWd,this->inputChannelCount_);
 }
 
-//namespace cnn_config{
-//namespace caffe_backend{
-
-//#ifdef HAVE_CAFFE
-
-//bool getCaffeGpuMode()
-//{
-//    return caffe::Caffe::mode()==caffe::Caffe::GPU;
-//}
-
-//void setCaffeGpuMode(bool useGpu)
-//{
-//    if(useGpu)
-//    {
-//        caffe::Caffe::set_mode(caffe::Caffe::GPU);
-//    }else
-//    {
-//        caffe::Caffe::set_mode(caffe::Caffe::CPU);
-//    }
-//}
-
-//bool getCaffeAvailable()
-//{
-//    return true;
-//}
-
-//#else
-
-//bool getCaffeGpuMode()
-//{
-//    CV_Error(Error::StsError,"Caffe not available during compilation!");
-//    return 0;
-//}
-
-//void setCaffeGpuMode(bool useGpu)
-//{
-//    CV_Error(Error::StsError,"Caffe not available during compilation!");
-//    CV_Assert(useGpu==1);//Compilation directives force
-//}
-
-//bool getCaffeAvailable(){
-//    return 0;
-//}
-
-//#endif
-
-//}//namespace caffe
-//}//namespace cnn_config
+
 
 }  } //namespace text namespace cv