From 7c7ecd71d26a22e47b0ff02397cdcac813fc22d0 Mon Sep 17 00:00:00 2001 From: Anguelos Nicolaou Date: Thu, 7 Jul 2016 15:42:39 +0200 Subject: [PATCH] Fixing warnings --- modules/text/src/ocr_holistic.cpp | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/modules/text/src/ocr_holistic.cpp b/modules/text/src/ocr_holistic.cpp index 94f9cd097..9f5b77aea 100644 --- a/modules/text/src/ocr_holistic.cpp +++ b/modules/text/src/ocr_holistic.cpp @@ -60,9 +60,9 @@ protected: void classifyMiniBatch(std::vector inputImageList, Mat outputMat){ //Classifies a list of images containing at most minibatchSz_ images - CV_Assert(inputImageList.size()<=this->minibatchSz_); + CV_Assert(int(inputImageList.size())<=this->minibatchSz_); CV_Assert(outputMat.isContinuous()); - float* ouputPtr= (float*)(outputMat.data); +#ifdef HAVE_CAFFE net_->input_blobs()[0]->Reshape(inputImageList.size(), 1,this->inputGeometry_.height,this->inputGeometry_.width); net_->Reshape(); float* inputBuffer=net_->input_blobs()[0]->mutable_cpu_data(); @@ -78,6 +78,7 @@ protected: const float* outputNetData=net_->output_blobs()[0]->cpu_data(); float*outputMatData=(float*)(outputMat.data); memcpy(outputMatData,outputNetData,sizeof(float)*this->outputSize_*inputImageList.size()); +#endif } #ifdef HAVE_CAFFE @@ -129,7 +130,7 @@ public: inputImageList.getMatVector(allImageVector); classProbabilities.create(Size(this->outputSize_,allImageVector.size()),CV_32F); Mat outputMat = classProbabilities.getMat(); - for(int imgNum=0;imgNumminibatchSz_){ + for(int imgNum=0;imgNumminibatchSz_){ int rangeEnd=imgNum+std::min(allImageVector.size()-imgNum,this->minibatchSz_); std::vector::const_iterator from=allImageVector.begin()+imgNum; std::vector::const_iterator to=allImageVector.begin()+rangeEnd; @@ -208,7 +209,7 @@ public: while (std::getline(labelsFile, line)){ labels_.push_back(std::string(line)); } - CV_Assert(this->classifier_->getOutputSize()==this->labels_.size()); + CV_Assert(this->classifier_->getOutputSize()==int(this->labels_.size())); } void recogniseImage(InputArray inputImage,CV_OUT String& transcription,CV_OUT double& confidence){