private void TextBox3_TextChanged(object sender, EventArgs e)
{
TextBox3 = (TextBox)sender;
string theText3 = TextBox3.Text;
ImageSegmentation ImageSeg = new ImageSegmentation();
// ImageSeg.Compute(InpFile, OutFile);
}
private void kśrednichToolStripMenuItem_Click(object sender, EventArgs e)
{
ImageSeg = new ImageSegmentation();
Bitmap image = ImageSeg.Compute((Bitmap)this.pctbImage.Image);
ImageSeg = null;
SetImageAndHist(image);
}
////~~~~~~~~~~~~~~~~~~~~~~~~~ Some crucial methods
///
private void analyze()
{
//Do different image segmentations, depending on the choices
if (comboBox1.SelectedIndex > -1)
{
String select = comboBox1.Text;
if (select == "K Clustering")
{
//do the K clustering method
segmentation = "K Cluster";
//System.Windows.Forms.MessageBox.Show("No image imported");
}
else if (select == "Edge Detection")
{
//have this done in edge detection
segmentation = "Edge Detection";
}
else
{
System.Windows.Forms.MessageBox.Show("No Segmentation Type Selected.");
return;
}
}
//first, the base case: we analyze when the user didn't put in a picture
if (pic == null)
{
System.Windows.Forms.MessageBox.Show("No image imported");
return;
}
else
{
if (segmentation == "K Cluster")
{
//before doing the segmentation, check if "temp.jpg" exists and "Segmented Image" exists
//using the method from KMC.cs
if (searched == 0)
{
Bitmap temp = (Bitmap)pic;
//set the name of the files created from the segmentation
temp.Save("t3mp.jpg", System.Drawing.Imaging.ImageFormat.Jpeg);
//temp.Dispose();
searched = 1;
}
//string directoryName = Path.GetDirectoryName("temp.jpg");
//string sourcePath = Directory.GetCurrentDirectory();
string path = Directory.GetCurrentDirectory();
//Now the color segmented images are in a folder called "Segmented Image"
string directory = path + "\\S3gmented Image";
//if there has not been K-clustering, skip the process and go to the API
if (!(System.IO.Directory.Exists(directory)))
{
//Trying Amanda's method
ImageSegmentation.Compute("t3mp.jpg");
}
files = Directory.GetFiles(directory, "*", SearchOption.AllDirectories);
int numFiles = files.GetLength(0);
//if the user enters another term after the images were already sent to API, we don't need to send to API again
if (API_sent == 0)
{
ImageCollections = new string[numFiles];
int tempCounter = 0;
//array that collects the accurate terms list
API_results = new List <string> [numFiles];
//Now we go inside the Segmented Image folder and loop
foreach (string file in files)
{
ImageCollections[tempCounter] = file;
Google.Cloud.Vision.V1.Image integer = Google.Cloud.Vision.V1.Image.FromFile(ImageCollections[tempCounter]);
//Keeps track of the terms used
API_results[tempCounter] = Vision.containsElement(integer);
tempCounter++;
}
//so we don't have to loop over again. We already have the information
API_sent = 1;
}
//our algorithm is first loop over each picture and if the user_query match, save the matching image and the rank in the array
// then continue over and if the user_query match on the next file and if the rank in the array is lower (more front), switch the saved image
int rank = 999;
for (int i = 1; i < numFiles; i++)
{
int count = API_results[i].Count;
for (int k = 0; k < count; k++)
{
if (String.Equals(user_query, API_results[i][k]))
{
//found a better and more accurate image. higher ranked
if (rank > k)
{
//want to free up our files, so we can delete later
if (resultBitmap != null)
{
resultBitmap.Dispose();
}
resultBitmap = new Bitmap(ImageCollections[i]);
rank = k;
}
}
}
}
// no API term found
if (rank == 999)
{
System.Windows.Forms.MessageBox.Show("No search term of \"" + user_query + "\" found");
}
/*
* List<String> output = API_results[1];
* String printing = output[1];
*
* System.Windows.Forms.MessageBox.Show(printing.ToString());
*/
//string name = ImageCollections[1];
//testNum = Vision.containsElement(ImageCollections[1], theText1);
//for the test purpose, get the second image that has been cropped
//resultBitmap = new Bitmap(ImageCollections[2]);
//Google.Cloud.Vision.V1.Image i = Google.Cloud.Vision.V1.Image.FromFile(ImageCollections[2]);
//testNum = Vision.containsElement(i, theText1);
//System.Windows.Forms.MessageBox.Show(testNum.ToString());
//pictureBox1.SizeMode = PictureBoxSizeMode.Zoom;
if (resultBitmap != null)
{
pictureBox1.Image = resultBitmap;
}
}
//System.Windows.Forms.MessageBox.Show(segmentation);
if (segmentation == "Edge Detection")
{
if (resultBitmap != null)
{
resultBitmap.Dispose();
}
//System.Windows.Forms.MessageBox.Show("Here");
resultBitmap = Filter.ApplyFilter((Bitmap)pic, EdgeFilter);
//Image finaloutput = (Image)resultBitmap;
//pictureBox2.SizeMode = PictureBoxSizeMode.Zoom;
//resultBitmap.UnlockBits
pictureBox1.SizeMode = PictureBoxSizeMode.Zoom;
pictureBox1.Image = resultBitmap;
}
}
}
public void TestMethod1()
{
Stopwatch stopwatch = new Stopwatch();
ImageSegmentation segmentation = new ImageSegmentation();
////foreach ((Image image, int? frameIndex, _) in Imaging.Image.FromFile(@"D:\source.bmp"))
////foreach ((Image image, _, _) in Imaging.Image.FromFile(@"C:\Users\Alexander\Desktop\hcfa.png"))
////foreach ((Image image, _, _) in Imaging.Image.FromFile(@"C:\Users\Alexander\Desktop\07227200002.tif"))
foreach ((Image image, int?frameIndex, _) in Imaging.Image.FromFile(@"L:\FormXtra\HCFA\BW\SET1\07227200002.tif"))
////foreach ((Image image, int? frameIndex, _) in Imaging.Image.FromFile(@"C:\Users\avolgunin\Desktop\hcfa.png"))
////foreach ((Image image, _, _) in Image.FromFile(@"C:\DNN\dnn\test4.jpg"))
{
Image xxx = image.ConvertTo(null, 1).CleanOverscan(0.5f, 0.5f).Deskew(null).Despeckle(null);
Image yyy = xxx.CreateTemplate(null, xxx.BitsPerPixel);
////LineDetector.FindLines(xxx, new LineDetectionOptions());
/*Pix pix = Pix.FromImage(xxx);*/
////int[] a = new int[10000];
////for (int kw = 49; kw <= 49; kw++)
{
////xxx.Dilate(yyy, StructuringElement.Brick(1, kw), 1, BorderType.BorderConst, 0);
////pix.DilateGray(1, kw);
////Pix pix = Pix.FromImage(image);
stopwatch.Restart();
for (int i = 0; i < 1; i++)
{
segmentation.Segment(xxx, null, CancellationToken.None);
////xxx.Binarize(yyy, 0, 0, 0, 0, true, 0, 0);
////Statistic.Smooth(a.Length, a, 0);
////pix.DilateGray(1, kw);
////xxx.Convert8To1(yyy, 128);
////xxx.Dilate(yyy, StructuringElement.Brick(1, kw), 1, BorderType.BorderConst, 0);
////xxx.Dilate3x3(yyy, BorderType.BorderConst, 0);
////xxx.Dilate(yyy, StructuringElement.Brick(3, 3), 1, BorderType.BorderConst, 0);
}
#if false
stopwatch.Restart();
for (int i = 0; i < 10; i++)
{
workImage.FindConnectedComponents(8);
}
////workImage.DistanceToBackground(4, 8);
stopwatch.Stop();
Console.WriteLine("{0:F4} ms", stopwatch.ElapsedMilliseconds /* / Count*/);
using (Pix pixComp = Pix.FromImage(workImage))
{
stopwatch.Restart();
using (Pix pixDist = pixComp.DistanceFunction(4, 8, 1))
{
}
stopwatch.Stop();
Console.WriteLine("{0:F4} ms", stopwatch.ElapsedMilliseconds /* / Count*/);
}
#endif
/*workImage = workImage.CleanOverscan(0.5f, 0.5f).Deskew(null).Despeckle(null);
* workImage.SetResolution(300, 300);
* ISet<LineShape> components = LineDetector.FindLines(workImage, new LineDetectionOptions());*/
stopwatch.Stop();
////Console.WriteLine("{0}: {1:F4} ms", kw, stopwatch.ElapsedMilliseconds/* / Count*/);
Console.WriteLine("{0:F4} ms", stopwatch.ElapsedMilliseconds /* / Count*/);
}
Console.WriteLine(segmentation.PrintPerformanceReport(1));
}
}
private async Task applyImageSegmentation()
{
ImageSegmentation imageSegmentation = new ImageSegmentation(this.ModifiedPicture);
await imageSegmentation.ApplyImageSegmentation(6, 10);
}
