private void backWorkLoadData_DoWork(object sender, DoWorkEventArgs e)
//private void btn_load_Click(object sender, EventArgs e)
{
ExperimentsNames wsiIndexItem = new ExperimentsNames();
this.Invoke(new MethodInvoker(delegate() { wsiIndexItem = (ExperimentsNames)cmbBox_experiments.SelectedItem; }));
int wsiIndex = wsiIndexItem.Order;
richTextBox1.Invoke((MethodInvoker) delegate {
richTextBox1.Text = $"Načitávam facts";
});
factorsOfMisclassification = LoadDatabase.Load_Factors(ExplanationDatabase.factOfMisclass_dir_path[wsiIndex], richTextBox1);
string cancer_path = ExplanationDatabase.wsi_paths[wsiIndex];
string label_path = ExplanationDatabase.wsi_labels_paths[wsiIndex];
var cancer_img = new Bitmap(cancer_path);
this.cancerBm = cancer_img;
richTextBox1.Invoke((MethodInvoker) delegate {
richTextBox1.Text = $"Načitávam label";
});
var label_img = new Bitmap(label_path);
this.labelBm = label_img;
this.memberships = LoadDatabase.LoadMemberships(wsiIndex);
this.data_memberships = LoadDatabase.LoadDataMembership();
this.data_paths = LoadDatabase.LoadDataPaths();
trackBar1.Invoke((MethodInvoker) delegate {
trackBar1.Visible = true;
});
pcBx_cancer.Image = cancer_img;
pcBx_label.Image = label_img;
this.history = new ExperimentHistory();
this.wsi_name = wsiIndexItem.Name;
folderPathToSaveResult = ExplanationDatabase.WSI_DATA_PATH + wsi_name + "\\results";
Directory.CreateDirectory(folderPathToSaveResult);
// load sugggested point to examine
this.suggestedPoints = Utilities.LoadSuggestedPoints(this.wsi_name);
this.suggestedPoints.Shuffle();
}
private void pcBx_cancer_Click(object sender, EventArgs e)
{
if (pcBx_cancer.Image != null && pcBx_label.Image != null)
{
MouseEventArgs me = (MouseEventArgs)e;
Point coordinates = me.Location;
if (me.Button == System.Windows.Forms.MouseButtons.Left)
{
var coord = Utilities.GetAbsolutCoordinates(coordinates, ORIGINAL_SIZE, pcBx_cancer);
this.actualCoord = coord;
int x = coord[0];
int y = coord[1];
var pxColor = labelBm.GetPixel(x, y);
int predictedLabel = ExplanationDatabase.GetLabel(pxColor);
var facts = LoadDatabase.GetFactors(factorsOfMisclassification, predictedLabel, x, y);
richTextBox1.Text = Utilities.ExtractSemantic(predictedLabel, facts);
Utilities.HighlightWords(ExplanationDatabase.classes.Values.ToArray(), richTextBox1);
// show image on wchich decision was made
float[] membValue = LoadDatabase.GetMembershipVector(memberships, x, y);
string decisionImagePath = LoadDatabase.GetTheMostSimilarImagePath(
predictedLabel, predictedLabel, membValue[predictedLabel - 1], data_memberships, data_paths);
pcBx_decisionImg.Image = new Bitmap(decisionImagePath);
pcBx_decisionImg.Refresh();
//label_pcBx_decisionImg.Text = $"Tkanivo {ExplanationDatabase.classes[predictedLabel]}";
label_pcBx_decisionImg.Text = $"Tissue {ExplanationDatabase.classes[predictedLabel]}";
// show high similar image if there are any
var pcBoxList = MergePcBxAndClear();
var labelList = MergeLabelsAndClear();
var highProbLabels = Utilities.GetElementsByValue(facts, "3");
var lowProbLabels = Utilities.GetElementsByValue(facts, "2");
foreach (var prob in highProbLabels)
{
string imgPath = LoadDatabase.GetTheMostSimilarImagePath(
predictedLabel, prob, membValue[prob - 1], data_memberships, data_paths);
if (pcBoxList.Count > 0)
{
pcBoxList[0].Image = new Bitmap(imgPath);
Graphics graphics = Graphics.FromImage((Image)pcBoxList[0].Image);
Pen pen = new Pen(Color.Red, 8);
Rectangle rect = new Rectangle(0, 0, 150, 150);
graphics.DrawRectangle(pen, rect);
pcBoxList[0].Refresh();
labelList[0].Text = $"Tissue {ExplanationDatabase.classes[prob]}";
//labelList[0].Text = $"Tkanivo {ExplanationDatabase.classes[prob]}";
pcBoxList.RemoveAt(0);
labelList.RemoveAt(0);
}
}
foreach (var prob in lowProbLabels)
{
string imgPath = LoadDatabase.GetTheMostSimilarImagePath(
predictedLabel, prob, membValue[prob - 1], data_memberships, data_paths);
if (pcBoxList.Count > 0)
{
pcBoxList[0].Image = new Bitmap(imgPath);
Graphics graphics = Graphics.FromImage((Image)pcBoxList[0].Image);
Pen pen = new Pen(Color.Yellow, 8);
Rectangle rect = new Rectangle(0, 0, 150, 150);
graphics.DrawRectangle(pen, rect);
pcBoxList[0].Refresh();
labelList[0].Text = $"Tissue {ExplanationDatabase.classes[prob]}";
//labelList[0].Text = $"Tkanivo {ExplanationDatabase.classes[prob]}";
pcBoxList.RemoveAt(0);
labelList.RemoveAt(0);
}
}
this.actualPredicted = predictedLabel;
groupBox_accuracy.Enabled = true;
this.pointer = this.SetNormalizePoint(coordinates);
this.newPointer = this.SetNormalizePoint(coordinates);
pcBx_label.Refresh();
pcBx_cancer.Refresh();
}
}
}
