I'm trying to set up an object recognition system with 12x30 images with 1280x1024 pixels.
I'm using Visual Studio 2013, Windows 8.1 x64 with 8GB RAM and compile as x86.
I get the following error message:
> C:\opencv\sources\modules\core\src\alloc.cpp:52: error: (-4) Failed to allocate 74747652 bytes in function cv::OutOfMemoryError
According to the Task Manager, my software needs less than 1.600.000K memory and the RAM is at 84%. So I think that should not be the problem.
This is the code, where I get the error:
cv::Ptr detector = cv::SurfFeatureDetector::create("SURF");
cv::Ptr extractor = cv::SurfDescriptorExtractor::create("SURF");
std::map> imageList;
// Filling the imageList
printMessageSlot("Starting: Compute Descriptors");
std::vector keypoints;
cv::Mat descriptors;
cv::Mat training_descriptors(1, extractor->descriptorSize(), extractor->descriptorType());
for (const auto &imgList : imageList)
{
for (const auto &img : imgList.second)
{
detector->detect(img, keypoints);
extractor->compute(img, keypoints, descriptors);
training_descriptors.push_back(descriptors);
}
}
printMessageSlot("Ending: Compute Descriptors");
I'm not really sure what causes the problem. I tried to set the Heap and Stack Reservation Size in Visual Studio to 2GB, but I get the error message that there is not enought memory for that command.
I really don't know how to solve this. I could try to read just one folder (corresponding to object class) of Images, calculate the descriptors and than override the Images with the next folder/class. But that feels like more complicated than it should be.
How does it works, when I have more than that few (360) Images?
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