public Photo GetPhoto(int id)
{
var photo = db.Photos.FirstOrDefault(x => x.Id == id);
using (var ms = new MemoryStream(photo.Image))
{
var bmp = new Bitmap(ms);
var scaled = new Bitmap(bmp, new Size(bmp.Width / 2, bmp.Height / 2));
photo.Image = PreprocessingHelper.ToByteArray(scaled, ImageFormat.Jpeg);
return(photo);
}
}
/// <summary>
/// source code : modified from https://www.codeproject.com/Articles/884518/Csharp-Optical-Marks-Recognition-OMR-Engine-a-Mar
/// </summary>
public static bool[] GetBinaryScore(Bitmap slice, int OMCount, int sheetWhite, bool overrideWhite)
{
//make grayscale
Grayscale gsf = new Grayscale(0.2989, 0.5870, 0.1140);
slice = gsf.Apply(slice);
//initialize members
Rectangle[] cropRects = new Rectangle[OMCount];
Bitmap[] marks = new Bitmap[OMCount];
bool[] answers = new bool[OMCount];
//sub-devide line into options count (horizontal only)
for (int i = 0; i < OMCount; i++)
{
cropRects[i] = new Rectangle(i * slice.Width / OMCount, 0, slice.Width / OMCount, slice.Height);
}
//the user specified that the line is actually multiple o Marks. lets crop them
for (int i = 0; i < OMCount; i++)
{
marks[i] = new Bitmap(cropRects[i].Width, cropRects[i].Height);
using (Graphics g = Graphics.FromImage(marks[i]))
{
g.DrawImage(slice, new Rectangle(0, 0, marks[i].Width, marks[i].Height),
cropRects[i],
GraphicsUnit.Pixel);
}
}
if (!overrideWhite)
{
sheetWhite = PreprocessingHelper.GetWhiteLevel(new Bitmap(slice));
}
for (int i = 0; i < OMCount; i++)
{
int temp = 0;
temp = Math.Max(PreprocessingHelper.AvgColor((System.Drawing.Image)marks[i], sheetWhite / 2), 0);
temp = (int)Math.Round(100 - (double)temp / (double)255 * 100D);
//the lesser the temp var, the more sensative the detection becomes. This Value can be calibrated with further experimentation
answers[i] = temp > 20;
}
return(answers);
}
