fix tab problem

pull/1252/head
Shengxin Qian 8 years ago
parent eb20d8fa78
commit 145e29564d
  1. 20
      modules/saliency/include/opencv2/saliency/saliencySpecializedClasses.hpp
  2. 2
      modules/saliency/samples/DeepGaze1Sample.cpp
  3. 10
      modules/saliency/src/BackgroundContrast.cpp

@ -162,12 +162,12 @@ You can passes your own DNN layers into the DeepGaze1 object and retrain it with
class CV_EXPORTS_W DeepGaze1 : public StaticSaliency
{
private:
/** @brief This is the field to store the input DNN
* @sa dnn::Net
*/
/** @brief This is the field to store the input DNN
* @sa dnn::Net
*/
dnn::Net net;
/** @brief This is the field to store the name of selected layer
*/
/** @brief This is the field to store the name of selected layer
*/
std::vector<std::string> layers_names;
/** @brief This is the field to store the weight of selected layer
*/
@ -297,11 +297,11 @@ This method also provides an optimization framework may help foreground based sa
class CV_EXPORTS_W BackgroundContrast : public StaticSaliency
{
private:
/** @brief
* limitOfSp is the maximum number of superpixel
* nOfLevel, usePrior, histBin is same as the seed superpixel method
* bgWei determine the weight of background when optimized with foreground method
*/
/** @brief
* limitOfSp is the maximum number of superpixel
* nOfLevel, usePrior, histBin is same as the seed superpixel method
* bgWei determine the weight of background when optimized with foreground method
*/
int limitOfSP;
int nOfLevel;
int usePrior;

@ -26,7 +26,7 @@ int main(int argc, char* argv[])
"{ help h usage ? | | show this message }"
"{ train |0 | set training on }"
"{ default |1 | use default deep net(AlexNet) and default weights }"
"{ AUC |0 | calculate AUC with input fixation map }"
"{ AUC |0 | calculate AUC with input fixation map }"
"{ img_path | | path to folder with img }"
"{ fix_path | | path to folder with fixation img for compute AUC }"
"{ model_path |bvlc_alexnet.caffemodel | path to your caffe model }"

@ -35,11 +35,11 @@ namespace saliency
BackgroundContrast::BackgroundContrast()
{
bgWei = 5;
limitOfSP = 600;
nOfLevel = 4;
usePrior = 2;
histBin = 5;
bgWei = 5;
limitOfSP = 600;
nOfLevel = 4;
usePrior = 2;
histBin = 5;
}
BackgroundContrast::BackgroundContrast( double _bgWei, int _limitOfSP, int _nOfLevel, int _usePrior, int _histBin ): limitOfSP(_limitOfSP), nOfLevel(_nOfLevel), usePrior(_usePrior), histBin(_histBin), bgWei(_bgWei) {}
BackgroundContrast::~BackgroundContrast(){}

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