C#

class Classifier
{
   int[] posPoints //for example = {1, 10, 15}
   int[] negPoints // {20, 30, 2} (both sets have maximum of 10 points)
}

class Image
{
   double[,] imageData; //typically 24x24 greyscale, thus 36KB
}

//example method that uses images and classifiers:


void doCalculations(List<Image> images, List<Classifier> classifiers)
{
   foreach(Image image in images)
   {
      foreach(Classifier classifier in classifiers)
      {
         double value = 0;

         foreach(int p in posPoints)
         {
            value += image.imageData[p];
         }
         foreach(int p in negPoints)
         {
            value -= image.imageData[p];
         }
         
         //More code here: decide on image type based on "value"...
      }
   }
}

tvbarnard wrote:

some of the stuff you've said I've already done

int index=points[i];
if (index>0) value+=data[index];
else value-=data[-index-1];

thread1()
{
   for(int i = 0, i < classifiers.count/2; i++)
      foreach(image)...
}
thread2()
{
   for(int i = classifiers.count/2; i < classfiers.count; i++)
   foreach(clas
}

tvbarnard wrote:

require even more computations?

tvbarnard wrote:

the threading part

int boundC = classifiers.count;
int boundI = images.count;

for(int c = 0; c < boundC; c++)
{
   for(int i = 0; i < boundI; i++)
   {
      //use unsafe code to declare pointers to
      //image's data and classifier's data

      //do computations
   }
}

tvbarnard wrote:

how I could use parallism

tvbarnard wrote:

the system uses at least 200,000 classifiers

int[] classifier = new int[] { 5, 6, 22}

tvbarnard wrote:

2. Parrallel processing the images (but I ended up with errors).

Parallel.For(0, bound, delegate(int i)
{

);