static bool RunOn(string file, OpenCvSharp.Rect boundingBox)
{
int areas = 0;
int[] quadrants = new int[4];
using (OpenCvSharp.Mat m = new OpenCvSharp.Mat(file, OpenCvSharp.ImreadModes.Grayscale))
{
//blur the image a little
using (var blurred = m.GaussianBlur(new Size(3, 3), 0))
{
//make the image binary black or white and make black the background color
using (var g = blurred.Threshold(200, 255, ThresholdTypes.BinaryInv | ThresholdTypes.Otsu))
{
var element = Cv2.GetStructuringElement(
MorphShapes.Rect,
new Size(50, 1));
//remove lines from dark background image by creating a mask
using (var mask = g.MorphologyEx(MorphTypes.Open, element, iterations: 2))
{
using (Mat newMask = new Mat())
{
//mask bits should be 0 to skip copying items
Cv2.BitwiseNot(mask, newMask);
using (Mat newImage = new Mat())
{
//make new image and apply mask so as to not copy the lines
g.CopyTo(newImage, newMask);
//create the box image
using (OpenCvSharp.Mat box = new OpenCvSharp.Mat(new Size(boundingBox.Width, boundingBox.Height), MatType.CV_8U))
{
//copy to the box
newImage[boundingBox].CopyTo(box);
using (Mat labels = new Mat())
{
using (var centroids = new Mat())
{
using (Mat stats = new Mat())
{
//find the white blobs
//populate the quadrants blobs appear in
//create total area of white stuff
int cnt = Cv2.ConnectedComponentsWithStats(box, labels, stats, centroids, PixelConnectivity.Connectivity8);
#if usequadrants
int qh = box.Size().Height / 2;
int qw = box.Size().Width / 2;
var tl = new Rect(0, 0, qw, qh);
var vl = new Rect(0, qh, qw, qh);
var tr = new Rect(qw, 0, qw, qh);
var br = new Rect(qw, qh, qw, qh);
#endif
for (var x = 1; x < stats.Size().Height; x++)
{
#if usequadrants
var left = stats.Get <int>(x, (int)ConnectedComponentsTypes.Left);
var top = stats.Get <int>(x, (int)ConnectedComponentsTypes.Top);
var width = stats.Get <int>(x, (int)ConnectedComponentsTypes.Width);
var height = stats.Get <int>(x, (int)ConnectedComponentsTypes.Height);
var re = new Rect(left, top, width, height);
if (re.IntersectsWith(tl))
{
quadrants[0] = 1;
}
if (re.IntersectsWith(vl))
{
quadrants[1] = 1;
}
if (re.IntersectsWith(tr))
{
quadrants[2] = 1;
}
if (re.IntersectsWith(br))
{
quadrants[3] = 1;
}
#endif
areas += stats.Get <int>(x, (int)ConnectedComponentsTypes.Area);
}
}
}
}
var boxarea = box.Size().Width *box.Size().Height;
double[] areasTest = new double[] { areas };
double[] boxAreas = new double[] { boxarea };
//use infer.net to determine if the mean is good or not
VariableArray <bool> ytest = Variable.Array <bool>(new Range(areasTest.Length));
BayesPointMachine(areasTest, boxAreas, Variable.Random(wPosterior), ytest);
var res = (DistributionStructArray <Bernoulli, bool>)engine.Infer(ytest);
var mean = res[0].GetMean();
Console.WriteLine(boxarea + " " + areas + " " + mean + " "
#if usequadrants
+ quadrants.Sum());
