From e494efb4b0884c0b68a8de7d7684ee385d8e222e Mon Sep 17 00:00:00 2001 From: sghoshcvc Date: Fri, 23 Jun 2017 19:09:17 +0200 Subject: [PATCH] Added comments --- modules/text/include/opencv2/text/ocr.hpp | 14 +++ .../include/opencv2/text/textDetector.hpp | 104 +++--------------- 2 files changed, 28 insertions(+), 90 deletions(-) diff --git a/modules/text/include/opencv2/text/ocr.hpp b/modules/text/include/opencv2/text/ocr.hpp index e0afe5ca4..9593a1415 100644 --- a/modules/text/include/opencv2/text/ocr.hpp +++ b/modules/text/include/opencv2/text/ocr.hpp @@ -633,6 +633,16 @@ public: */ CV_WRAP void preprocess(InputArray input,OutputArray output,Size sz,int outputChannels); + /** @brief this method in provides public acces to set the mean of the input images + * mean can be a mat either of same size of the image or one value per color channel + * A preprocessor can be created without the mean( the pre processor will calculate mean for every image + * in that case + * + + * @param mean which will be subtracted from the images + * + */ + CV_WRAP void set_mean(Mat mean); /** @brief Creates a functor that only resizes and changes the channels of the input @@ -655,6 +665,10 @@ public: * @return shared pointer to generated preprocessor */ CV_WRAP static Ptr createImageMeanSubtractor(InputArray meanImg); + /** @brief + * create a functor with the parameters, parameters can be changes by corresponding set functions + * @return shared pointer to generated preprocessor + */ CV_WRAP static PtrcreateImageCustomPreprocessor(double rawval=1.0,String channel_order="BGR"); diff --git a/modules/text/include/opencv2/text/textDetector.hpp b/modules/text/include/opencv2/text/textDetector.hpp index 262795733..ea1c7de9d 100644 --- a/modules/text/include/opencv2/text/textDetector.hpp +++ b/modules/text/include/opencv2/text/textDetector.hpp @@ -62,7 +62,7 @@ namespace text //base class BaseDetector declares a common API that would be used in a typical text -//recognition scenario +//detection scenario class CV_EXPORTS_W BaseDetector { public: @@ -78,46 +78,7 @@ class CV_EXPORTS_W BaseDetector std::vector* component_confidences=NULL, int component_level=0) = 0; - /** @brief Main functionality of the OCR Hierarchy. Subclasses provide - * default parameters for all parameters other than the input image. - */ -// virtual std::vector* run(InputArray image){ -// //std::string res; -// std::vector component_rects; -// std::vector component_confidences; -// //std::vector component_texts; -// Mat inputImage=image.getMat(); -// this->run(inputImage,&component_rects, -// &component_confidences,OCR_LEVEL_WORD); -// return *component_rects; -// } - -}; - - -//Classifiers should provide diferent backends -//For the moment only caffe is implemeted -//enum{ -// OCR_HOLISTIC_BACKEND_NONE, -// OCR_HOLISTIC_BACKEND_CAFFE -//}; - - - - - -/** @brief OCRHolisticWordRecognizer class provides the functionallity of segmented wordspotting. - * Given a predefined vocabulary , a TextImageClassifier is employed to select the most probable - * word given an input image. - * - * This class implements the logic of providing transcriptions given a vocabulary and and an image - * classifer. The classifier has to be any TextImageClassifier but the classifier for which this - * class was built is the DictNet. In order to load it the following files should be downloaded: - * - * - * - */ class CV_EXPORTS_W textDetector : public BaseDetector { public: @@ -125,7 +86,7 @@ public: std::vector* component_confidences=NULL, int component_level=OCR_LEVEL_WORD)=0; - /** @brief Recognize text using a segmentation based word-spotting/classifier cnn. + /** @brief detect text with a cnn, input is one image with (multiple) ocuurance of text. Takes image on input and returns recognized text in the output_text parameter. Optionally provides also the Rects for individual text elements found (e.g. words), and the list of those @@ -135,16 +96,12 @@ public: @param mask is totally ignored and is only available for compatibillity reasons - @param output_text Output text of the the word spoting, always one that exists in the dictionary. - @param component_rects Not applicable for word spotting can be be NULL if not, a single elemnt will - be put in the vector. + @param component_rects a vector of Rects, each rect is one text bounding box. - @param component_texts Not applicable for word spotting can be be NULL if not, a single elemnt will - be put in the vector. - @param component_confidences Not applicable for word spotting can be be NULL if not, a single elemnt will - be put in the vector. + + @param component_confidences A vector of float returns confidence of text bounding boxes @param component_level must be OCR_LEVEL_WORD. */ @@ -155,76 +112,43 @@ public: /** - @brief Method that provides a quick and simple interface to a single word image classifcation + @brief Method that provides a quick and simple interface to detect text inside an image - @param inputImage an image expected to be a CV_U8C1 or CV_U8C3 of any size + @param inputImage an image expected to be a CV_U8C3 of any size - @param transcription an opencv string that will store the detected word transcription + @param Bbox a vector of Rect that will store the detected word bounding box - @param confidence a double that will be updated with the confidence the classifier has for the selected word + @param confidence a vector of float that will be updated with the confidence the classifier has for the selected bounding box */ CV_WRAP virtual void textDetectInImage(InputArray inputImage,CV_OUT std::vector& Bbox,CV_OUT std::vector& confidence)=0; - /** - @brief Method that provides a quick and simple interface to a multiple word image classifcation taking advantage - the classifiers parallel capabilities. - - @param inputImageList an list of images expected to be a CV_U8C1 or CV_U8C3 each image can be of any size and is assumed - to contain a single word. - @param transcriptions a vector of opencv strings that will store the detected word transcriptions, one for each - input image - - @param confidences a vector of double that will be updated with the confidence the classifier has for each of the - selected words. - */ - //CV_WRAP virtual void recogniseImageBatch(InputArrayOfArrays inputImageList,CV_OUT std::vector& transcriptions,CV_OUT std::vector& confidences)=0; /** @brief simple getter for the preprocessing functor */ CV_WRAP virtual Ptr getClassifier()=0; - /** @brief Creates an instance of the OCRHolisticWordRecognizer class. + /** @brief Creates an instance of the textDetector class. @param classifierPtr an instance of TextImageClassifier, normaly a DeepCNN instance - @param vocabularyFilename the relative or absolute path to the file containing all words in the vocabulary. Each text line - in the file is assumed to be a single word. The number of words in the vocabulary must be exactly the same as the outputSize - of the classifier. + */ CV_WRAP static Ptr create(Ptr classifierPtr); - /** @brief Creates an instance of the OCRHolisticWordRecognizer class and implicitly also a DeepCNN classifier. + /** @brief Creates an instance of the textDetector class and implicitly also a DeepCNN classifier. @param modelArchFilename the relative or absolute path to the prototxt file describing the classifiers architecture. @param modelWeightsFilename the relative or absolute path to the file containing the pretrained weights of the model in caffe-binary form. - @param vocabularyFilename the relative or absolute path to the file containing all words in the vocabulary. Each text line - in the file is assumed to be a single word. The number of words in the vocabulary must be exactly the same as the outputSize - of the classifier. + */ CV_WRAP static Ptr create(String modelArchFilename, String modelWeightsFilename); - /** @brief - * - * @param classifierPtr - * - * @param vocabulary - */ - // CV_WRAP static Ptr create(Ptr classifierPtr,const std::vector& vocabulary); - - /** @brief - * - * @param modelArchFilename - * - * @param modelWeightsFilename - * - * @param vocabulary - */ - // CV_WRAP static Ptr create (String modelArchFilename, String modelWeightsFilename, const std::vector& vocabulary); + };