private void DoWork(object sender, DoWorkEventArgs e)
{
var currentProgress = inputProgressBar.Value;
var filesProcessed = 0;
var totalFilesCount = 0;
var inputDirectories = Directory.GetDirectories(inputFolderPath);
if (inputDirectories.Length == 0)
{
throw new Exception("No categories was found!");
}
var labels = new string[inputDirectories.Length];
for (var i = 0; i < inputDirectories.Length; i++)
{
labels[i] = inputDirectories[i].Substring(inputFolderPath.Length + 1);
}
for (var i = 0; i < inputDirectories.Length; i++)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
var inputFilePaths = Directory.GetFiles(inputDirectories[i] + "\\", "*." + extension);
if (inputFilePaths.Length == 0)
{
throw new Exception("No files in category was found!");
}
else
{
totalFilesCount += inputFilePaths.Length;
}
}
totalFilesCount *= 2;
for (var k = 0; k < inputDirectories.Length; k++)
{
var inputFilePaths = Directory.GetFiles(inputDirectories[k] + "\\", "*." + extension);
foreach (var inputFP in inputFilePaths)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
if (!ImageProcessor.PrepareImageFromFile(inputFP, width, height, extension))
{
throw new Exception("Error processing the image!");
}
filesProcessed += 1;
var progress = 100 * filesProcessed / totalFilesCount;
if (progress > currentProgress)
{
bw.ReportProgress(progress);
}
}
}
var setFolder = inputFolderPath.Substring(inputFolderPath.LastIndexOf('\\') + 1);
for (int k = 0; k < inputDirectories.Length; k++)
{
var tmpPath = Path.Combine(Directory.GetCurrentDirectory(), "temp");
var label = inputDirectories[k].Substring(inputDirectories[k].LastIndexOf('\\') + 1);
var inputFilePaths = Directory.GetFiles(Path.Combine(tmpPath, setFolder, label) + "\\", "*." + extension);
using var fileStream = File.Open(outputFilePath, FileMode.Append, FileAccess.Write);
using StreamWriter sw = new StreamWriter(fileStream);
foreach (var inputFP in inputFilePaths)
{
if (bw.CancellationPending)
{
e.Cancel = true;
return;
}
var output = "";
var image = new Bitmap(inputFP);
var imageWidth = image.Width;
var imageHeight = image.Height;
var partWidth = imageWidth / int.Parse(Resources.PARTITION);
var partHeight = imageHeight / int.Parse(Resources.PARTITION);
for (var j = 0; j < int.Parse(Resources.PARTITION); j++)
{
for (var i = 0; i < int.Parse(Resources.PARTITION); i++)
{
var pixels = ImageProcessor.CountBlackPixels(image, i * partWidth, j * partHeight, (i + 1) * partWidth - 1, (j + 1) * partHeight - 1);
output += pixels + ",";
}
}
output += labels[k];
sw.WriteLine(output);
filesProcessed += 1;
var progress = 100 * filesProcessed / totalFilesCount;
if (progress > currentProgress)
{
bw.ReportProgress(progress);
}
}
}
Directory.Delete(Path.Combine(Directory.GetCurrentDirectory(), "temp", setFolder), true);
}
private void ConvertedDocumentView_Load(object sender, EventArgs e)
{
List <Rectangle> tmp = new List <Rectangle>();
if (template == DocTemplate.PersonEvidence)
{
initialImage = Resources.PEF;
}
documentWrapper.Size = inputImageSize;
int width = owner.ClientSize.Width > inputImageSize.Width + 16 ? inputImageSize.Width : owner.ClientSize.Width - 28;
int height = owner.ClientSize.Height > inputImageSize.Height + 67 ? inputImageSize.Height + 28 : owner.ClientSize.Height - 75;
ClientSize = new Size(width, height);
MaximumSize = new Size(width + 16, height + 39);
inputImage = initialImage.ToImage <Bgr, byte>();
outputImage = inputImage.Convert <Gray, byte>().ThresholdBinary(new Gray(100), new Gray(255));
VectorOfVectorOfPoint contours = new VectorOfVectorOfPoint();
Mat hierarhy = new Mat();
CvInvoke.FindContours(outputImage, contours, hierarhy, RetrType.Tree, ChainApproxMethod.ChainApproxSimple);
Dictionary <int, double> contoursDict = new Dictionary <int, double>();
for (int i = 0; i < contours.Size; i++)
{
double area = CvInvoke.ContourArea(contours[i]);
contoursDict.Add(i, area);
}
var items = contoursDict.OrderByDescending(i => i.Value).Skip(1).Take(predictions.Count);
foreach (var item in items)
{
int key = int.Parse(item.Key.ToString());
tmp.Add(CvInvoke.BoundingRectangle(contours[key]));
}
var skipItemsCount = 0;
tmp.Sort((item1, item2) => item1.Y.CompareTo(item2.Y));
partitions.ForEach(part => {
var items = tmp.Skip(skipItemsCount).Take(part).ToList <Rectangle>();
items.Sort((item1, item2) => item1.X.CompareTo(item2.X));
skipItemsCount += part;
foreach (var bbox in items)
{
int w = bbox.Width;
int h = bbox.Height;
int x = bbox.X + w / 10;
int y = bbox.Y + h / 10;
w -= 2 * w / 10;
h -= 2 * h / 10;
BBoxes.Add(new Rectangle(x, y, w, h));
}
});
for (int i = 0; i < predictions.Count; i++)
{
ImageProcessor.ReplacePrediction(predictions.ElementAt(i).Value, initialImage, BBoxes.ElementAt(i));
}
scaleX = (float)inputImageSize.Width / initialImage.Size.Width;
scaleY = (float)inputImageSize.Height / initialImage.Size.Height;
documentWrapper.Image = new Bitmap(initialImage, inputImageSize);
correctArea = new Region(new Rectangle(new Point(0, 0), documentWrapper.Image.Size));
tmp = new List <Rectangle>();
BBoxes.ForEach(bbox =>
{
var rect = new Rectangle((int)(bbox.X * scaleX), (int)(bbox.Y * scaleY),
(int)(bbox.Width * scaleX), (int)(bbox.Height * scaleY));
tmp.Add(rect);
correctArea.Exclude(rect);
});
BBoxesScaled = tmp;
}
