/// <summary>
/// Release all resources used.
/// </summary>
public void Dispose()
{
if (m_factory != null)
{
m_factory.Close();
m_factory.Dispose();
m_factory = null;
}
}
/// <summary>
/// Releases the resouces used.
/// </summary>
/// <param name="bDisposing">Set to <i>true</i> when called by Dispose()</param>
protected virtual void Dispose(bool bDisposing)
{
if (m_factory != null)
{
m_factory.Close();
m_factory.Dispose();
m_factory = null;
}
}
public void TestIndexQuery()
{
PreTest.Init();
Log log = new Log("Test Dataset Factory");
log.EnableTrace = true;
string strDs = "MNIST";
DatasetFactory factory = new DatasetFactory();
Stopwatch sw = new Stopwatch();
try
{
DatasetDescriptor ds = factory.LoadDataset(strDs);
factory.Open(ds.TrainingSource.ID);
sw.Start();
List <DbItem> rgItems = factory.LoadImageIndexes(false);
sw.Stop();
log.CHECK_EQ(rgItems.Count, ds.TrainingSource.ImageCount, "The query count should match the image count!");
factory.Close();
log.WriteLine("Query time = " + sw.Elapsed.TotalMilliseconds.ToString("N5") + " ms.");
sw.Restart();
int nMin = int.MaxValue;
int nMax = -int.MaxValue;
for (int i = 0; i < rgItems.Count; i++)
{
nMin = Math.Min(rgItems[i].Label, nMin);
nMax = Math.Max(rgItems[i].Label, nMax);
}
List <DbItem> rgBoosted = rgItems.Where(p => p.Boost > 0).ToList();
for (int nLabel = nMin; nLabel <= nMax; nLabel++)
{
List <DbItem> rgLabel = rgItems.Where(p => p.Label == nLabel).ToList();
}
sw.Stop();
log.WriteLine("Query time (profile) = " + sw.Elapsed.TotalMilliseconds.ToString("N5") + " ms.");
}
finally
{
factory.Dispose();
}
}
public void TestPutRawImage(bool bSaveImagesToFile)
{
DatasetFactory factory = new DatasetFactory();
factory.DeleteSources("Test123");
int nSrcId = factory.AddSource("Test123", 1, 10, 10, false, 0, bSaveImagesToFile);
factory.Open(nSrcId, 10);
byte[] rgBytes = new byte[10 * 10];
for (int i = 0; i < 20; i++)
{
rgBytes[i] = (byte)i;
SimpleDatum sd = new SimpleDatum(false, 1, 10, 10, i, DateTime.MinValue, rgBytes.ToList(), null, 0, false, i);
factory.PutRawImageCache(i, sd);
}
factory.ClearImageCash(true);
List <RawImage> rgImg = factory.GetRawImagesAt(0, 20);
for (int i = 0; i < rgImg.Count; i++)
{
SimpleDatum sd = factory.LoadDatum(rgImg[i]);
bool bEncoded = false;
byte[] rgData = sd.GetByteData(out bEncoded);
for (int j = 0; j < 100; j++)
{
if (j <= i)
{
Assert.AreEqual(rgData[j], j);
}
else
{
Assert.AreEqual(rgData[j], 0);
}
}
}
factory.DeleteSources("Test123");
factory.Close();
}
private bool loadFile(string strImagesFile, string strSourceName, int nExtractTotal, ref int nExtractIdx, int nTotal, ref int nIdx, Log log, bool bExtractFiles, Dictionary <string, int> rgNameToLabel)
{
Stopwatch sw = new Stopwatch();
reportProgress(nIdx, nTotal, " Source: " + strSourceName);
reportProgress(nIdx, nTotal, " loading " + strImagesFile + "...");
FileStream fs = null;
try
{
int nSrcId = m_factory.AddSource(strSourceName, 3, -1, -1, false);
addLabels(nSrcId, rgNameToLabel);
m_factory.Open(nSrcId, 500, Database.FORCE_LOAD.NONE, log);
int nPos = strImagesFile.ToLower().LastIndexOf(".tar");
string strPath = strImagesFile.Substring(0, nPos);
if (!Directory.Exists(strPath))
{
Directory.CreateDirectory(strPath);
}
if (bExtractFiles)
{
log.Progress = (double)nIdx / nExtractTotal;
log.WriteLine("Extracting files from '" + strImagesFile + "'...");
if ((nExtractIdx = TarFile.ExtractTar(strImagesFile, strPath, m_evtCancel, log, nExtractTotal, nExtractIdx)) == 0)
{
log.WriteLine("Aborted.");
return(false);
}
}
// Load the annotations.
SimpleDatum.ANNOTATION_TYPE type = SimpleDatum.ANNOTATION_TYPE.BBOX;
int nResizeHeight = 0;
int nResizeWidth = 0;
// Create the training database images.
// Create the master list file.
List <Tuple <string, string> > rgFiles = createFileList(log, strPath);
sw.Start();
for (int i = 0; i < rgFiles.Count; i++)
{
SimpleDatum datum = loadDatum(log, rgFiles[i].Item1, rgFiles[i].Item2, nResizeHeight, nResizeWidth, type, rgNameToLabel);
m_factory.PutRawImageCache(nIdx, datum);
nIdx++;
if (m_evtCancel.WaitOne(0))
{
log.WriteLine("Aborted.");
return(false);
}
if (sw.Elapsed.TotalMilliseconds > 1000)
{
log.Progress = (double)nIdx / nTotal;
log.WriteLine("Loading file " + i.ToString() + " of " + rgFiles.Count.ToString() + "...");
sw.Restart();
}
}
m_factory.ClearImageCashe(true);
m_factory.Close();
}
finally
{
if (fs != null)
{
fs.Dispose();
}
}
return(true);
}
public void Create(DatasetConfiguration config, IXDatasetCreatorProgress progress)
{
string strCsvFile = Properties.Settings.Default.CsvFile;
string strDsName = config.Name;
string strTrainingSrc = config.Name + ".training";
string strTestingSrc = config.Name + ".testing";
m_bCancel = false;
m_iprogress = progress;
m_factory.DeleteSources(strTrainingSrc, strTestingSrc);
Log log = new Log("CSV Dataset Creator");
log.OnWriteLine += new EventHandler <LogArg>(log_OnWriteLine);
try
{
//-----------------------------------------
// Load the schema that defines the layout
// of the CSV file.
//-----------------------------------------
m_schema = loadSchema(config.Settings);
//-----------------------------------------
// Load and parse the CSV file.
//-----------------------------------------
DataConfigSetting dsCsvFile = config.Settings.Find("CSV File");
strCsvFile = dsCsvFile.Value.ToString();
if (strCsvFile.Length == 0)
{
throw new Exception("CSV data file name not specified!");
}
log.WriteLine("Loading the data file...");
if (m_bCancel)
{
return;
}
m_parser.Load(strCsvFile, m_schema);
//-----------------------------------------
// Split the data into training and testing
// sets.
//-----------------------------------------
List <DataItem> rgTraining = new List <DataItem>();
List <DataItem> rgTesting = new List <DataItem>();
DataConfigSetting dsPctTesting = config.Settings.Find("Testing Percentage");
double dfVal = (double)dsPctTesting.Value;
Random random = new Random();
for (int i = 0; i < m_parser.Data.Count; i++)
{
if (random.NextDouble() > dfVal)
{
rgTraining.Add(m_parser.Data[i]);
}
else
{
rgTesting.Add(m_parser.Data[i]);
}
}
Properties.Settings.Default.TestingPct = dfVal;
//-----------------------------------------
// Create the training data source.
//-----------------------------------------
int nCellHorizCount = 0;
List <int> rgDim = getImageDim(m_parser, m_schema, out nCellHorizCount);
int nTrainSrcId = m_factory.AddSource(strTrainingSrc, rgDim[0], rgDim[1], rgDim[2], false, 0);
m_factory.Open(nTrainSrcId, 500, Database.FORCE_LOAD.FROM_FILE); // use file based data.
log.WriteLine("Deleting existing data from '" + m_factory.OpenSource.Name + "'.");
m_factory.DeleteSourceData();
if (!loadData(log, m_factory, m_parser, rgTraining, rgDim, true, true))
{
return;
}
m_factory.UpdateSourceCounts();
updateLabels(m_factory);
log.WriteLine("Creating the image mean...");
SimpleDatum dMean = SimpleDatum.CalculateMean(log, m_rgImages.ToArray(), new WaitHandle[] { new ManualResetEvent(false) });
m_factory.PutRawImageMean(dMean, true);
m_rgImages.Clear();
m_factory.Close();
//-----------------------------------------
// Create the testing data source.
//-----------------------------------------
int nTestSrcId = m_factory.AddSource(strTestingSrc, rgDim[0], rgDim[1], rgDim[2], false, 0);
m_factory.Open(nTestSrcId, 500, Database.FORCE_LOAD.FROM_FILE); // use file based data.
log.WriteLine("Deleting existing data from '" + m_factory.OpenSource.Name + "'.");
m_factory.DeleteSourceData();
if (!loadData(log, m_factory, m_parser, rgTesting, rgDim, false, false))
{
return;
}
m_factory.UpdateSourceCounts();
updateLabels(m_factory);
m_factory.Close();
//-----------------------------------------
// Crate the data set.
//-----------------------------------------
log.WriteLine("Done loading training and testing data.");
int nDatasetID = 0;
using (DNNEntities entities = EntitiesConnection.CreateEntities())
{
List <Source> rgSrcTraining = entities.Sources.Where(p => p.Name == strTrainingSrc).ToList();
List <Source> rgSrcTesting = entities.Sources.Where(p => p.Name == strTestingSrc).ToList();
if (rgSrcTraining.Count == 0)
{
throw new Exception("Could not find the training source '" + strTrainingSrc + "'.");
}
if (rgSrcTesting.Count == 0)
{
throw new Exception("Could not find the tesing source '" + strTestingSrc + "'.");
}
DataConfigSetting dsName = config.Settings.Find("Output Dataset Name");
int nSrcTestingCount = rgSrcTesting[0].ImageCount.GetValueOrDefault();
int nSrcTrainingCount = rgSrcTraining[0].ImageCount.GetValueOrDefault();
int nSrcTotalCount = nSrcTestingCount + nSrcTrainingCount;
double dfTestingPct = (nSrcTrainingCount == 0) ? 0.0 : nSrcTestingCount / (double)nSrcTotalCount;
Dataset ds = new Dataset();
ds.ImageHeight = rgSrcTraining[0].ImageHeight;
ds.ImageWidth = rgSrcTraining[0].ImageWidth;
ds.Name = strDsName;
ds.ImageEncoded = rgSrcTesting[0].ImageEncoded;
ds.ImageChannels = rgSrcTesting[0].ImageChannels;
ds.TestingPercent = (decimal)dfTestingPct;
ds.TestingSourceID = rgSrcTesting[0].ID;
ds.TestingTotal = rgSrcTesting[0].ImageCount;
ds.TrainingSourceID = rgSrcTraining[0].ID;
ds.TrainingTotal = rgSrcTraining[0].ImageCount;
ds.DatasetCreatorID = config.ID;
ds.DatasetGroupID = 0;
ds.ModelGroupID = 0;
entities.Datasets.Add(ds);
entities.SaveChanges();
nDatasetID = ds.ID;
}
m_factory.SetDatasetParameter(nDatasetID, "PixelSize", m_schema.CellSize.ToString());
m_factory.SetDatasetParameter(nDatasetID, "AttributeCount", m_parser.DataDescriptions.Count.ToString());
m_factory.SetDatasetParameter(nDatasetID, "AttributeCountHoriz", nCellHorizCount.ToString());
m_factory.SetDatasetParameter(nDatasetID, "AttributeCountVert", nCellHorizCount.ToString());
}
catch (Exception excpt)
{
log.WriteLine("ERROR: " + excpt.Message);
}
finally
{
Properties.Settings.Default.CsvFile = strCsvFile;
Properties.Settings.Default.Save();
if (m_bCancel)
{
log.WriteLine("ABORTED converting CSV data files.");
}
else
{
log.WriteLine("Done converting CSV data files.");
}
if (m_bCancel)
{
m_iprogress.OnCompleted(new CreateProgressArgs(1, 1, "ABORTED!", null, true));
}
else
{
m_iprogress.OnCompleted(new CreateProgressArgs(1, "COMPLETED."));
}
}
}
private ImageSet loadImageset(string strType, SourceDescriptor src, WaitHandle[] rgAbort, ref SimpleDatum imgMean, out int nLastImageIdx, int nPadW = 0, int nPadH = 0, Log log = null, IMAGEDB_LOAD_METHOD loadMethod = IMAGEDB_LOAD_METHOD.LOAD_ALL, int nImageDbLoadLimit = 0, int nImageDbLoadLimitStartIdx = 0, bool bLoadNext = false)
{
try
{
RawImageMean imgMeanRaw = null;
m_factory.Open(src);
nLastImageIdx = nImageDbLoadLimitStartIdx;
if (loadMethod != IMAGEDB_LOAD_METHOD.LOAD_ALL)
{
if (imgMean == null)
{
imgMeanRaw = m_factory.GetRawImageMean();
if (imgMeanRaw == null)
{
if (log != null)
{
log.WriteLine("WARNING: No image mean exists in the database, changing image database load from " + loadMethod.ToString() + " to " + IMAGEDB_LOAD_METHOD.LOAD_ALL.ToString());
}
loadMethod = IMAGEDB_LOAD_METHOD.LOAD_ALL;
}
}
}
int nCount = src.ImageCount;
if (nCount == 0)
{
throw new Exception("Could not find any images with " + strType + " Source = '" + src.Name + "'.");
}
if (log != null)
{
log.WriteLine("Loading '" + src.Name + "' - " + nCount.ToString("N0") + " images.");
}
ImageSet imgset = new ImageSet(m_factory, src, loadMethod, nImageDbLoadLimit);
if (OnCalculateImageMean != null)
{
imgset.OnCalculateImageMean += OnCalculateImageMean;
}
if (loadMethod != IMAGEDB_LOAD_METHOD.LOAD_ON_DEMAND)
{
bool bDataIsReal = src.IsRealData;
int nBatchSize = 20000;
Stopwatch sw = new Stopwatch();
int nImageSize = src.ImageHeight * src.ImageWidth;
if (nImageSize > 60000)
{
nBatchSize = 5000;
}
else if (nBatchSize > 20000)
{
nBatchSize = 7500;
}
else if (nImageSize > 3000)
{
nBatchSize = 10000;
}
if (nImageDbLoadLimit <= 0)
{
nImageDbLoadLimit = nCount;
}
List <int> rgIdx = getIndexList(nImageDbLoadLimitStartIdx, nImageDbLoadLimit);
int nIdx = 0;
sw.Start();
while (nIdx < rgIdx.Count)
{
int nImageIdx = rgIdx[nIdx];
int nImageCount = Math.Min(rgIdx.Count - nIdx, nBatchSize);
List <RawImage> rgImg = m_factory.GetRawImagesAt(nImageIdx, nImageCount);
for (int j = 0; j < rgImg.Count; j++)
{
SimpleDatum sd1 = m_factory.LoadDatum(rgImg[j], nPadW, nPadH);
imgset.Add(nIdx + j, sd1);
if (sw.Elapsed.TotalMilliseconds > 1000)
{
if (log != null)
{
double dfPct = (double)(nIdx + j) / (double)nCount;
log.Progress = dfPct;
log.WriteLine("image loading at " + dfPct.ToString("P") + "...");
}
sw.Restart();
if (EventWaitHandle.WaitAny(rgAbort, 0) != EventWaitHandle.WaitTimeout)
{
return(null);
}
}
}
nIdx += rgImg.Count;
if (loadMethod == IMAGEDB_LOAD_METHOD.LOAD_ALL && rgImg.Count == 0 && nIdx < nCount)
{
log.WriteLine("WARNING: Loaded " + nIdx.ToString("N0") + " images, yet " + (nCount - nIdx).ToString("N0") + " images are unaccounted for. You may need to reindex the dataset.");
break;
}
}
if (log != null)
{
log.Progress = 0;
}
if (rgIdx.Count > 0)
{
nLastImageIdx = rgIdx[rgIdx.Count - 1] + 1;
}
}
else if (bLoadNext)
{
nLastImageIdx += nImageDbLoadLimit;
}
if (imgMean == null)
{
if (imgMeanRaw == null)
{
imgMeanRaw = m_factory.GetRawImageMean();
}
if (imgMeanRaw != null)
{
imgMean = m_factory.LoadDatum(imgMeanRaw, nPadW, nPadH);
}
else
{
if (log != null)
{
log.WriteLine("Calculating mean...");
}
imgMean = imgset.GetImageMean(log, rgAbort);
m_factory.PutRawImageMean(imgMean, true);
}
}
if (imgMean != null)
{
imgset.SetImageMean(imgMean);
}
imgset.CompleteLoad(nLastImageIdx);
return(imgset);
}
finally
{
m_factory.Close();
}
}
/// <summary>
/// The dataLoadThread is responsible for loading the data source images in the background.
/// </summary>
private void dataLoadThread()
{
m_evtRunning.Set();
DatasetFactory factory = new DatasetFactory(m_factory);
int? nNextIdx = m_loadSequence.GetNext();
Stopwatch sw = new Stopwatch();
if (m_refreshManager != null)
{
m_refreshManager.Reset();
}
try
{
sw.Start();
List <int> rgIdxBatch = new List <int>();
int nBatchSize = getBatchSize(m_src);
if (m_nLoadedCount > 0)
{
throw new Exception("The loaded count is > 0!");
}
factory.Open(m_src);
m_log.WriteLine(m_src.Name + " loading " + m_loadSequence.Count.ToString("N0") + " items...");
while (nNextIdx.HasValue || rgIdxBatch.Count > 0)
{
if (nNextIdx.HasValue)
{
rgIdxBatch.Add(nNextIdx.Value);
}
if (rgIdxBatch.Count >= nBatchSize || !nNextIdx.HasValue)
{
List <RawImage> rgImg;
if (m_refreshManager == null)
{
rgImg = factory.GetRawImagesAt(rgIdxBatch[0], rgIdxBatch.Count);
}
else
{
rgImg = factory.GetRawImagesAt(rgIdxBatch, m_evtCancel);
}
if (rgImg == null)
{
break;
}
for (int j = 0; j < rgImg.Count; j++)
{
SimpleDatum sd = factory.LoadDatum(rgImg[j]);
if (m_refreshManager != null)
{
m_refreshManager.AddLoaded(sd);
}
m_rgImages[m_nLoadedCount] = sd;
m_nLoadedCount++;
if (sw.Elapsed.TotalMilliseconds > 1000)
{
if (m_log != null && !m_bSilent)
{
double dfPct = m_nLoadedCount / (double)m_rgImages.Length;
m_log.Progress = dfPct;
m_log.WriteLine("Loading '" + m_src.Name + "' at " + dfPct.ToString("P") + " (" + m_nLoadedCount.ToString("N0") + " of " + m_rgImages.Length.ToString("N0") + ")...");
}
int nWait = WaitHandle.WaitAny(m_rgAbort.ToArray(), 0);
if (nWait != WaitHandle.WaitTimeout)
{
return;
}
sw.Restart();
}
}
rgIdxBatch = new List <int>();
}
nNextIdx = m_loadSequence.GetNext();
}
if (rgIdxBatch.Count > 0)
{
m_log.FAIL("Not all images were loaded!");
}
}
finally
{
factory.Close();
factory.Dispose();
m_evtRunning.Reset();
m_evtDone.Set();
}
}
public void Create(DatasetConfiguration config, IXDatasetCreatorProgress progress)
{
string strTrainingBatchFile1 = Properties.Settings.Default.TrainingDataFile1;
string strTrainingBatchFile2 = Properties.Settings.Default.TrainingDataFile2;
string strTrainingBatchFile3 = Properties.Settings.Default.TrainingDataFile3;
string strTrainingBatchFile4 = Properties.Settings.Default.TrainingDataFile4;
string strTrainingBatchFile5 = Properties.Settings.Default.TrainingDataFile5;
string strTestingBatchFile = Properties.Settings.Default.TestingDataFile;
string strDsName = config.Name;
string strTrainingSrc = config.Name + ".training";
string strTestingSrc = config.Name + ".testing";
int nIdx = 0;
int nTotal = 50000;
m_bCancel = false;
m_iprogress = progress;
m_factory.DeleteSources(strTrainingSrc, strTestingSrc);
Log log = new Log("CIFAR Dataset Creator");
log.OnWriteLine += new EventHandler <LogArg>(log_OnWriteLine);
try
{
DataConfigSetting dsTrainingDataFile1 = config.Settings.Find("Training Data File 1");
DataConfigSetting dsTrainingDataFile2 = config.Settings.Find("Training Data File 2");
DataConfigSetting dsTrainingDataFile3 = config.Settings.Find("Training Data File 3");
DataConfigSetting dsTrainingDataFile4 = config.Settings.Find("Training Data File 4");
DataConfigSetting dsTrainingDataFile5 = config.Settings.Find("Training Data File 5");
DataConfigSetting dsTestingDataFile = config.Settings.Find("Testing Data File");
strTrainingBatchFile1 = dsTrainingDataFile1.Value.ToString();
if (strTrainingBatchFile1.Length == 0)
{
throw new Exception("Training data file #1 name not specified!");
}
strTrainingBatchFile2 = dsTrainingDataFile2.Value.ToString();
if (strTrainingBatchFile2.Length == 0)
{
throw new Exception("Training data file #2 name not specified!");
}
strTrainingBatchFile3 = dsTrainingDataFile3.Value.ToString();
if (strTrainingBatchFile3.Length == 0)
{
throw new Exception("Training data file #3 name not specified!");
}
strTrainingBatchFile4 = dsTrainingDataFile4.Value.ToString();
if (strTrainingBatchFile4.Length == 0)
{
throw new Exception("Training data file #4 name not specified!");
}
strTrainingBatchFile5 = dsTrainingDataFile5.Value.ToString();
if (strTrainingBatchFile5.Length == 0)
{
throw new Exception("Training data file #5 name not specified!");
}
strTestingBatchFile = dsTestingDataFile.Value.ToString();
if (strTestingBatchFile.Length == 0)
{
throw new Exception("Testing data file name not specified!");
}
log.WriteLine("Loading the data files...");
if (m_bCancel)
{
return;
}
int nTrainSrcId = m_factory.AddSource(strTrainingSrc, 3, 32, 32, false, 0);
m_factory.Open(nTrainSrcId, 500, Database.FORCE_LOAD.FROM_FILE); // use file based data.
log.WriteLine("Deleting existing data from '" + m_factory.OpenSource.Name + "'.");
m_factory.DeleteSourceData();
if (!loadFile(log, dsTrainingDataFile1.Name, strTrainingBatchFile1, m_factory, nTotal, true, ref nIdx))
{
return;
}
if (!loadFile(log, dsTrainingDataFile2.Name, strTrainingBatchFile2, m_factory, nTotal, true, ref nIdx))
{
return;
}
if (!loadFile(log, dsTrainingDataFile3.Name, strTrainingBatchFile3, m_factory, nTotal, true, ref nIdx))
{
return;
}
if (!loadFile(log, dsTrainingDataFile4.Name, strTrainingBatchFile4, m_factory, nTotal, true, ref nIdx))
{
return;
}
if (!loadFile(log, dsTrainingDataFile5.Name, strTrainingBatchFile5, m_factory, nTotal, true, ref nIdx))
{
return;
}
m_factory.UpdateSourceCounts();
updateLabels(m_factory);
log.WriteLine("Creating the image mean...");
SimpleDatum dMean = SimpleDatum.CalculateMean(log, m_rgImages.ToArray(), new WaitHandle[] { new ManualResetEvent(false) });
m_factory.PutRawImageMean(dMean, true);
m_rgImages.Clear();
m_factory.Close();
int nTestSrcId = m_factory.AddSource(strTestingSrc, 3, 32, 32, false, 0);
m_factory.Open(nTestSrcId, 500, Database.FORCE_LOAD.FROM_FILE); // use file based data.
log.WriteLine("Deleting existing data from '" + m_factory.OpenSource.Name + "'.");
m_factory.DeleteSourceData();
nIdx = 0;
nTotal = 10000;
if (!loadFile(log, dsTestingDataFile.Name, strTestingBatchFile, m_factory, nTotal, false, ref nIdx))
{
return;
}
m_factory.CopyImageMean(strTrainingSrc, strTestingSrc);
m_factory.UpdateSourceCounts();
updateLabels(m_factory);
m_factory.Close();
log.WriteLine("Done loading training and testing data.");
using (DNNEntities entities = EntitiesConnection.CreateEntities())
{
List <Source> rgSrcTraining = entities.Sources.Where(p => p.Name == strTrainingSrc).ToList();
List <Source> rgSrcTesting = entities.Sources.Where(p => p.Name == strTestingSrc).ToList();
if (rgSrcTraining.Count == 0)
{
throw new Exception("Could not find the training source '" + strTrainingSrc + "'.");
}
if (rgSrcTesting.Count == 0)
{
throw new Exception("Could not find the tesing source '" + strTestingSrc + "'.");
}
DataConfigSetting dsName = config.Settings.Find("Output Dataset Name");
int nSrcTestingCount = rgSrcTesting[0].ImageCount.GetValueOrDefault();
int nSrcTrainingCount = rgSrcTraining[0].ImageCount.GetValueOrDefault();
int nSrcTotalCount = nSrcTestingCount + nSrcTrainingCount;
double dfTestingPct = (nSrcTrainingCount == 0) ? 0.0 : nSrcTestingCount / (double)nSrcTotalCount;
Dataset ds = new Dataset();
ds.ImageHeight = rgSrcTraining[0].ImageHeight;
ds.ImageWidth = rgSrcTraining[0].ImageWidth;
ds.Name = strDsName;
ds.ImageEncoded = rgSrcTesting[0].ImageEncoded;
ds.ImageChannels = rgSrcTesting[0].ImageChannels;
ds.TestingPercent = (decimal)dfTestingPct;
ds.TestingSourceID = rgSrcTesting[0].ID;
ds.TestingTotal = rgSrcTesting[0].ImageCount;
ds.TrainingSourceID = rgSrcTraining[0].ID;
ds.TrainingTotal = rgSrcTraining[0].ImageCount;
ds.DatasetCreatorID = config.ID;
ds.DatasetGroupID = 0;
ds.ModelGroupID = 0;
entities.Datasets.Add(ds);
entities.SaveChanges();
}
}
catch (Exception excpt)
{
log.WriteLine("ERROR: " + excpt.Message);
}
finally
{
Properties.Settings.Default.TrainingDataFile1 = strTrainingBatchFile1;
Properties.Settings.Default.TrainingDataFile2 = strTrainingBatchFile2;
Properties.Settings.Default.TrainingDataFile3 = strTrainingBatchFile3;
Properties.Settings.Default.TrainingDataFile4 = strTrainingBatchFile4;
Properties.Settings.Default.TrainingDataFile5 = strTrainingBatchFile5;
Properties.Settings.Default.TestingDataFile = strTestingBatchFile;
Properties.Settings.Default.Save();
if (m_bCancel)
{
log.WriteLine("ABORTED converting CIFAR data files.");
}
else
{
log.WriteLine("Done converting CIFAR data files.");
}
if (m_bCancel)
{
m_iprogress.OnCompleted(new CreateProgressArgs(nIdx, nTotal, "ABORTED!", null, true));
}
else
{
m_iprogress.OnCompleted(new CreateProgressArgs(1, "COMPLETED."));
}
}
}
