I have a question about using the adaptiveThreshold function from OpenCV in C++. (Here is it's documentation.)
void adaptiveThreshold(InputArray src, OutputArray dst, double maxValue, int adaptiveMethod, int thresholdType, int blockSize, double C)
After reading this article, I am pretty clear on how this function can be used to find a good threshold for images (represented as Mat object in OpenVC).
My case is a little bit different in that I would like to use it only for a vector instead of a Mat. So basically I have a vector of double values and I need to find a good threshold and was wondering if there is an easy way to adapt the adaptiveThreshold function for that matter. I experimented with more static methods to generate a threshold like using the mean average or the median, but these don't work well in my case.
Does anyone have a suggestion on how to approach this? I am guessing I would have to adjust the src and dst parameters and somehow pass my vector, but a straightforward approach to do so did not work.
Create a cv::Mat that wraps the vector. The relevant constructor is declared:
//! builds matrix from std::vector with or without copying the data
template<typename _Tp> explicit Mat(const vector<_Tp>& vec, bool copyData=false);
So you should be able to do:
std::vector<double> vec(10, 0.0); // your vector here
bool copyData = false;
cv::Mat M(vec, copyData); // default is not to copy data
The resulting Mat will be a single column.