generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

enhanced basic error management when input image could not be loaded

Browse Source
This commit is contained in:
Alexandre Benoit 2011-08-15 13:24:31 +00:00
parent fba70ca131
commit cd8d3afe37
1 changed files with 9 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

13
samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping.cpp
View File

@ -18,7 +18,7 @@ void help(std::string errorMessage)
std::cout<<"\nProgram call procedure : ./OpenEXRimages_HighDynamicRange_Retina_toneMapping [OpenEXR image to process]"<<std::endl; std::cout<<"\nProgram call procedure : ./OpenEXRimages_HighDynamicRange_Retina_toneMapping [OpenEXR image to process]"<<std::endl;
std::cout<<"\t[OpenEXR image to process] : the input HDR image to process, must be an OpenEXR format, see http://www.openexr.com/ to get some samples or create your own using camera bracketing and Photoshop or equivalent software for OpenEXR image synthesis"<<std::endl; std::cout<<"\t[OpenEXR image to process] : the input HDR image to process, must be an OpenEXR format, see http://www.openexr.com/ to get some samples or create your own using camera bracketing and Photoshop or equivalent software for OpenEXR image synthesis"<<std::endl;
std::cout<<"\nExamples:"<<std::endl; std::cout<<"\nExamples:"<<std::endl;
std::cout<<"\t-Image processing : ./OpenEXRimages_HighDynamicRange_Retina_toneMapping KernerEnvLatLong.exr"<<std::endl; std::cout<<"\t-Image processing : ./OpenEXRimages_HighDynamicRange_Retina_toneMapping memorial.exr"<<std::endl;
} }
// simple procedure for 1D curve tracing // simple procedure for 1D curve tracing
@ -104,7 +104,7 @@ void drawPlot(const cv::Mat curve, const std::string figureTitle, const int lowe
<<"\n\t"<<histogramClippingLimit*100<<"% index = "<<histLowerLimit<<" => normalizedHist value = "<<denseProb.at<float>(histLowerLimit)<<" => input gray level = "<<minInputValue <<"\n\t"<<histogramClippingLimit*100<<"% index = "<<histLowerLimit<<" => normalizedHist value = "<<denseProb.at<float>(histLowerLimit)<<" => input gray level = "<<minInputValue
<<"\n\t"<<(1-histogramClippingLimit)*100<<"% index = "<<histUpperLimit<<" => normalizedHist value = "<<denseProb.at<float>(histUpperLimit)<<" => input gray level = "<<maxInputValue <<"\n\t"<<(1-histogramClippingLimit)*100<<"% index = "<<histUpperLimit<<" => normalizedHist value = "<<denseProb.at<float>(histUpperLimit)<<" => input gray level = "<<maxInputValue
<<std::endl; <<std::endl;
drawPlot(denseProb, "input histogram density probability", histLowerLimit, histUpperLimit); //drawPlot(denseProb, "input histogram density probability", histLowerLimit, histUpperLimit);
drawPlot(normalizedHist, "input histogram", histLowerLimit, histUpperLimit); drawPlot(normalizedHist, "input histogram", histLowerLimit, histUpperLimit);
// rescale image range [minInputValue-maxInputValue] to [0-255] // rescale image range [minInputValue-maxInputValue] to [0-255]
@ -132,7 +132,7 @@ void drawPlot(const cv::Mat curve, const std::string figureTitle, const int lowe
void callBack_updateRetinaParams(int, void*) void callBack_updateRetinaParams(int, void*)
{ {
retina->setupOPLandIPLParvoChannel(true, true, (double)localAdaptation_photoreceptors/200.0, 0.5, 0.43, (double)retinaHcellsGain, 1, 7, (double)localAdaptation_Gcells/200.0); retina->setupOPLandIPLParvoChannel(true, true, (double)localAdaptation_photoreceptors/200.0, 0.5, 0.43, (double)retinaHcellsGain, 1.0, 7.0, (double)localAdaptation_Gcells/200.0);
} }
int colorSaturationFactor; int colorSaturationFactor;
@ -184,7 +184,12 @@ void drawPlot(const cv::Mat curve, const std::string figureTitle, const int lowe
// image processing case // image processing case
// declare the retina input buffer... that will be fed differently in regard of the input media // declare the retina input buffer... that will be fed differently in regard of the input media
inputImage = cv::imread(inputImageName, -1); // load image in RGB mode inputImage = cv::imread(inputImageName, -1); // load image in RGB mode
std::cout<<"=> image size (h,w) = "<<inputImage.size().height<<", "<<inputImage.size().width<<std::endl;
if (!inputImage.total())
{
help("could not load image, program end");
return -1;
}
// rescale between 0 and 1 // rescale between 0 and 1
normalize(inputImage, inputImage, 0.0, 1.0, cv::NORM_MINMAX); normalize(inputImage, inputImage, 0.0, 1.0, cv::NORM_MINMAX);
cv::Mat gammaTransformedImage; cv::Mat gammaTransformedImage;