// This window will work as the link between the capture processes and the analysis processes
public AnalysisWindow(CaptureWindow cw, bool countAnalysis, bool classAnalysis, string map, string folder)
{
InitializeComponent();
this.Width = 1200;
this.Height = 900;
if (countAnalysis)
{
countPage = new CountAnalytics(this); chartPage = new ChartPage();
}
if (classAnalysis)
{
clssPage = new ClassifyAnalytics(); if (map.Length > 1)
{
clssPage.Init(map, countPage);
}
}
pick = new Picker(cw, countAnalysis, classAnalysis, clssPage, countPage, chartPage, folder);
Navigate(pick);
closeRequest = false;
captureWindow = cw;
}
// @Override Task Constructor
public Task()
{
captureWindow = null;
numberOfCaptures = 0;
interval = 0;
index = 0;
delay = 0;
}
// Constructor
public Task(CaptureWindow cw, int nOfC, int inter, int ind, int dl, List <Uri> cpt, string f)
{
captureWindow = cw;
numberOfCaptures = nOfC;
interval = inter;
index = ind;
captures = cpt;
delay = dl;
folder = f;
}
// @Override Task Constructor
public Task()
{
captureWindow = null;
numberOfCaptures = 0;
interval = 0;
index = 0;
delay = 0;
name = "";
location = null;
size = new System.Drawing.Point();
}
// Constructor
public Task(CaptureWindow cw, int nOfC, int inter, int ind, int dl, List <Uri> cpt, string f, bool count, bool classAn, string n, PcPhysicalPoint loc, System.Drawing.Point s)
{
captureWindow = cw;
numberOfCaptures = nOfC;
interval = inter;
index = ind;
captures = cpt;
delay = dl;
folder = f;
countAnalysis = count;
classAnalysis = classAn;
name = n;
location = loc;
size = s;
}
// UI initialization with a link to every analysis related interface
public Picker(CaptureWindow cw, bool count, bool classAn, ClassifyAnalytics clss, CountAnalytics cnt, ChartPage chp, string folder)
{
InitializeComponent();
captureWindow = cw;
countAnalysis = count;
classAnalysis = classAn;
Logo_Init();
Panel_Logic_Init();
clssPage = clss;
countPage = cnt;
chartPage = chp;
saveFolder = folder;
}
// As long as the parameter "playing" is active in Capture Window, this thread will trigger the function CaptureWindow.showNextCapture at a
// speed rate given by the mentioned window
public void StartHandler(object param)
{
CaptureWindow cw = (CaptureWindow)param;
Thread.Sleep(1000);
while (true)
{
if (!cw.playing)
{
return;
}
else
{
App.Current.Dispatcher.BeginInvoke(System.Windows.Threading.DispatcherPriority.Background,
new Action(() => cw.showNextCapture()));
Thread.Sleep((int)(cw.speed * 1000));
}
}
}
// In each step, colony tracking is performed by comparing the current taken image with the
// first one (serving as background) and the last one in the look for changes
public void newStep(object param)
{
while (analysisInProgress)
{
Thread.Sleep(1000);
}
analysisInProgress = true;
object[] objects = (object[])param;
System.Drawing.Bitmap bmp = (System.Drawing.Bitmap)objects[0];
CaptureWindow cw = (CaptureWindow)objects[1];
Tracking_Images.Add(bmp);
Tracking_Images[Tracking_Images.Count - 1].Tag = DateTime.Now.ToString("hh:mm:ss");
// Firstly we will find the best matching repositioning to the images by selecting the one that minimizes the edges difference
// This is needed because of the Sprout's image acquisition impresition, which leads to minor mismatches between the same object's captures
int[] positions = Matching_Robinson.RobinsonRepositioning(background, bmp);
// Once the reposition is calculated, a difference between the taken image and the background is performed
// For this difference, Manhattan difference computation has been used. However, Eucliedean distance computation and
// Pearson's correlation index difference computation functions are included in the code and ready to be used.
Map resultDifference = DifferenceComputation.getManhattan(background, bmp, positions);
// A cluster search is computed
List <Cluster> frameBlobs = FindObjects(resultDifference, DateTime.Now.ToString("hh:mm:ss"));
// If this is the first tracking step made, the found clusters are set as base ones,
// otherwise a tracking algorithm trying to match current clusters with already monitored ones is performed
if (track.isEmpty())
{
track.firstScan(frameBlobs, step); events = new int[0];
}
else
{
events = track.assignBlobs(frameBlobs, step);
}
events = checkBounds(events, track.getLast(), bmp);
if (aw.getPicker().classAnalysis&& !aw.getClass().hasError())
{
aw.getClass().newStep(track.getLast(), bmp);
App.Current.Dispatcher.BeginInvoke(System.Windows.Threading.DispatcherPriority.ApplicationIdle,
new Action(() => cw.processClassification()));
}
step++;
App.Current.Dispatcher.BeginInvoke(System.Windows.Threading.DispatcherPriority.ApplicationIdle,
new Action(() => cw.processEvents()));
analysisInProgress = false;
}
public void setCaptureWindow(CaptureWindow cp)
{
this.captureWindow = cp;
}
public Tuple(CaptureWindow cp, int[] param)
{
captureWindow = cp;
parameters = param;
}
