public void RunOCR(Bitmap inputImage)
{
inputImagePV.Image = inputImage;
Bitmap removeBorderImage = BorderRemoval.RemoveBorder(inputImage);
removeBorderPV.Image = removeBorderImage;
Bitmap removeNoiseImage = NoiseCleaner.RemoveNoiseWithBorder(removeBorderImage);
noiseRemovalPV.Image = removeNoiseImage;
Bitmap croppedImage = WhitespaceCropper.CropWhitespace(removeNoiseImage);
croppedPV.Image = croppedImage;
if (EmptyImageDetector.IsImageEmpty(croppedImage))
{
recognizedGradeLabel.Text = "0";
recognitionConfidenceLabel.Text = "empty";
}
else
{
Bitmap digestImage = DigestExtractor.ExtractDigestImage(croppedImage);
digestPV.Image = digestImage;
GradeDigest digest = GradeDigest.FromImage(digestImage);
RecognitionResult recognitionResult = GradeOCR.Program.RecognizeGrade(digest);
recognizedGradeLabel.Text = recognitionResult.Grade.ToString();
recognitionConfidenceLabel.Text = recognitionResult.Confident ? "sure" : "unsure";
}
}
public static GradeDigest FromImage(Bitmap src)
{
if (src.Width != digestSize || src.Height != digestSize)
{
throw new Exception(String.Format(
"Wrong digest image dimension: required {0}x{1}, got {2}x{3}",
digestSize, digestSize, src.Width, src.Height));
}
GradeDigest gd = new GradeDigest();
bool[] bitData = new bool[digestSize * digestSize];
unsafe {
BitmapData bd = src.LockBits(new Rectangle(0, 0, src.Width, src.Height), ImageLockMode.ReadOnly, PixelFormat.Format32bppArgb);
byte * ptr = (byte *)bd.Scan0.ToPointer();
for (int q = 0; q < src.Width * src.Height; q++)
{
bitData[q] = *ptr == 0;
ptr += 4;
}
src.UnlockBits(bd);
}
gd.data = PackBits(bitData);
return(gd);
}
public static Bitmap GenerateDifferenceImage(GradeDigest gd1, GradeDigest gd2)
{
Bitmap res = new Bitmap(GradeDigest.digestSize, GradeDigest.digestSize, PixelFormat.Format32bppArgb);
unsafe {
BitmapData bd = res.LockBits(new Rectangle(0, 0, res.Width, res.Height), ImageLockMode.WriteOnly, PixelFormat.Format32bppArgb);
uint * ptr = (uint *)bd.Scan0.ToPointer();
for (int q = 0; q < gd1.data.Length * 64; q++)
{
bool b1 = (gd1.data[q / 64] & ((ulong)1 << (q % 64))) != 0;
bool b2 = (gd2.data[q / 64] & ((ulong)1 << (q % 64))) != 0;
if (b1 && b2)
{
*(ptr++) = 0xff00ff00;
}
else if (b1 && !b2)
{
*(ptr++) = 0xffff0000;
}
else if (!b1 && b2)
{
*(ptr++) = 0xff0000ff;
}
else
{
*(ptr++) = 0xffffffff;
}
}
res.UnlockBits(bd);
}
return(res);
}
public static RecognitionResult RecognizeGrade(GradeDigest digest)
{
List <int> gradeCodes = new List <int> {
2, 3, 4, 5
};
double[] output = new double[4];
gradeRecognitionNetwork.NetOUT(NNUtils.ToNetworkInput(GradeDigest.UnpackBits(digest.data)), out output);
return(new RecognitionResult(
grade: gradeCodes[NNUtils.Answer(output)],
confident: NNUtils.AnswerConfidence(output) < recognitionConfidenceThreshold
));
}
public static Option <GradeDigest> GetGradeDigest(Bitmap img)
{
Bitmap croppedImage =
WhitespaceCropper.CropWhitespace(
NoiseCleaner.RemoveNoiseWithBorder(
BorderRemoval.RemoveBorder(img)));
if (EmptyImageDetector.IsImageEmpty(croppedImage))
{
return(new None <GradeDigest>());
}
else
{
return(new Some <GradeDigest>(
GradeDigest.FromImage(
DigestExtractor.ExtractDigestImage(croppedImage))));
}
}
public static GradeDigestSet Read(Stream inStream)
{
List <GradeDigest> digests = new List <GradeDigest>();
uint digestCount = ByteUtils.ReadUInt(inStream);
for (int q = 0; q < digestCount; q++)
{
GradeDigest gd = new GradeDigest();
gd.grade = ByteUtils.SafeReadByte(inStream);
for (int w = 0; w < gd.data.Length; w++)
{
gd.data[w] = ByteUtils.ReadULong(inStream);
}
digests.Add(gd);
}
return(new GradeDigestSet(digests));
}
public double MatchDigests(GradeDigest gd1, GradeDigest gd2)
{
int union = 0;
int intersection = 0;
for (int q = 0; q < gd1.data.Length; q++)
{
intersection += ByteUtils.CountBits(gd1.data[q] & gd2.data[q]);
union += ByteUtils.CountBits(gd1.data[q] | gd2.data[q]);
}
if (union == 0)
{
return(0);
}
else
{
return((double)intersection / (double)union);
}
}
public RecognitionResult FindBestMatch(GradeDigest digest)
{
double maxMatch = 0;
int bestIndex = 0;
GradeDigest bestDigest = digestList[0];
for (int q = 0; q < digestList.Count; q++)
{
var gd = digestList[q];
double match = MatchDigests(digest, gd);
if (maxMatch < match && match < 0.9999)
{
maxMatch = match;
bestDigest = gd;
bestIndex = q;
}
}
throw new NotImplementedException();
}
