#Weighted average method map code

Otherwise, it is set to white (grayscale = 255). If the intensity level of a pixel is smaller than the threshold, the pixel is set to black (grayscale = 0). The basic idea is to find a point between the peak of the foreground pixel values and the peak of the background pixel values. Image histogram can be used to automatically determine the value of the threshold to be used for converting a grayscale image to a binary image. The image histogram is a statistical graph with grayscale value on the x-axis and the number of pixels for each grayscale on the y-axis. The global thresholding method takes advantage of the image histogram. The image is divided into several sub-blocks, and the distribution of gray-value in each block was analyzed. With the local thresholding method, a threshold is calculated at each pixel, which depends on some local statistics such as mean, range, and the variance of the pixel neighborhood. The images below show an example of before and after binarization. Global thresholding - calculates the threshold once for all pixels.Local thresholding - calculates the threshold pixel by pixel.The critical task is to find a suitable threshold. This transformation is useful in detecting blobs and further reduces the computational complexity. Binarization: Grayscale to black/white Conversionīinarization converts a grayscale image to a black/white image.

#Weighted average method map code

It would be trivial to change it to divide by D, instead, to match your code (but not your stated intent).RGB_image = cv2.imread('thai-government-lottery.png') Note that the functor in the above code divides by D+1. Thrust::make_permutation_iterator(Q.begin(),MapQ.end()))), Thrust::make_permutation_iterator(D.begin(),MapP.end()), Thrust::make_permutation_iterator(P.begin(),MapP.end()), Thrust::make_zip_iterator(thrust::make_tuple( Thrust::make_permutation_iterator(Q.begin(),MapQ.begin()))), Thrust::make_permutation_iterator(P.begin(),MapP.begin()), Thrust::transform(thrust::device, thrust::make_zip_iterator(thrust::make_tuple( Since we need to pass multiple vectors to thrust::transform in this realization, we will introduce thrust::zip_iterator $ cat t332.cu Regarding your question, everything can be done with a single call to thrust::transform with an appropriately defined functor. Refer to the thrust quick start guide for an example of this.Īlso note that both in your question and your code you refer to dividing by D+1, but your code is actually dividing by D, not D+1. Note that when passing the end of a permutation iterator, we do not use the end of the source vector: thrust::make_permutation_iterator(P.end(),MapP.end()),īut instead the beginning: thrust::make_permutation_iterator(P.begin(),MapP.end()), I'll assume you want element-wise operation on the vectors, since that is the behavior of your supplied demonstrator code. Thrust::copy(thrust::device, temp.begin(), temp.end(), thrust::make_permutation_iterator(P.begin(),MapP.begin())) // use permutation iterator replace contents of P with the weighted sum using pts in map M thrust::transform(thrust::device, temp.begin(), temp.end(), thrust::make_transform_iterator(D.begin(), increment()), temp.begin(), thrust::divides()) Thrust::make_permutation_iterator(Q.begin(),MapQ.begin()), Thrust::transform(thrust::device, temp.begin(), temp.end(), thrust::transform(thrust::device, temp.begin(), temp.end(), Q.begin(), temp.begin(), thrust::plus()) // use permutation iterator Thrust::make_permutation_iterator(D.begin(),MapP.begin()), Thrust::make_permutation_iterator(P.end(),MapP.end()), Thrust::transform(thrust::device, thrust::make_permutation_iterator(P.begin(),MapP.begin()),

thrust::transform(thrust::device, P.begin(), P.end(), D.begin(), temp.begin(), thrust::multiplies()) // use permutation iterator MapP=0 MapP=5 MapP=4 MapP=2 MapP=7 MapP=1 MapP=9 MapP=3 MapP=6 MapP=8 Thrust::sequence(thrust::device, D.begin(), D.begin() + N, 1) Thrust::device_vector Q = random_vector(N,9) Thrust::device_vector P = random_vector(N,1) Thrust::uniform_real_distribution u01(0.0f, 10.0f) Unsigned int seed = thrust::default_random_engine::default_seed) Thrust::device_vector random_vector(const size_t N, Can anyone suggest a better way to do it? #include I need to compute (P*D+Q)/(D+1) for all points from P & Q which have been selected using the respective maps. I have two device_vector maps(MapP & MapQ of size say 10) for P & Q which has the indices of points to be selected from P & Q. I have two device_vector P & Q (say of size 100).