public DataState(DataState s)
{
m_sd = s.m_sd;
}
/// <summary>
/// Step the gym one step in the data.
/// </summary>
/// <param name="nAction">Specifies the action to run on the gym.</param>
/// <param name="bGetLabel">Not used.</param>
/// <param name="extraProp">Optionally, specifies extra properties.</param>
/// <returns>A tuple containing state data, the reward, and the done state is returned.</returns>
public Tuple <State, double, bool> Step(int nAction, bool bGetLabel = false, PropertySet extraProp = null)
{
DataState data = new DataState();
ScoreCollection scores = null;
if (ActivePhase == Phase.RUN)
{
if (extraProp == null)
{
throw new Exception("The extra properties are needed when querying data during the RUN phase.");
}
int nDataCount = extraProp.GetPropertyAsInt("DataCountRequested");
string strStartTime = extraProp.GetProperty("SeedTime");
int nStartIdx = m_scores.Count - nDataCount;
DateTime dt;
if (DateTime.TryParse(strStartTime, out dt))
{
nStartIdx = m_scores.FindIndexAt(dt, nDataCount);
}
scores = m_scores.CopyFrom(nStartIdx, nDataCount);
}
else
{
int nCount = 0;
m_scores = load(out m_nDim, out m_nWidth);
if (m_bRecreateData || m_scores.Count != m_ds.TrainingSource.ImageCount)
{
Stopwatch sw = new Stopwatch();
sw.Start();
m_scores = new ScoreCollection();
while (m_nCurrentIdx < m_ds.TrainingSource.ImageCount)
{
// Query images sequentially by index in batches
List <SimpleDatum> rgSd = new List <SimpleDatum>();
for (int i = 0; i < m_nBatchSize; i++)
{
SimpleDatum sd = m_imgdb.QueryImage(m_ds.TrainingSource.ID, m_nCurrentIdx + i, IMGDB_LABEL_SELECTION_METHOD.NONE, IMGDB_IMAGE_SELECTION_METHOD.NONE);
rgSd.Add(sd);
nCount++;
if (nCount == m_ds.TrainingSource.ImageCount)
{
break;
}
}
List <ResultCollection> rgRes = m_mycaffe.Run(rgSd, ref m_blobWork);
if (m_nWidth == 0)
{
m_nWidth = rgRes[0].ResultsOriginal.Count;
m_nDim = rgRes[0].ResultsOriginal.Count * 2;
}
// Fill SimpleDatum with the ordered label,score pairs starting with the detected label.
for (int i = 0; i < rgRes.Count; i++)
{
m_scores.Add(new Score(rgSd[i].TimeStamp, rgSd[i].Index, rgRes[i]));
m_nCurrentIdx++;
}
if (sw.Elapsed.TotalMilliseconds > 1000)
{
m_log.Progress = (double)m_nCurrentIdx / (double)m_ds.TrainingSource.ImageCount;
m_log.WriteLine("Running model on image " + m_nCurrentIdx.ToString() + " of " + m_ds.TrainingSource.ImageCount.ToString() + " of '" + m_strDataset + "' dataset.");
if (m_evtCancel.WaitOne(0))
{
return(null);
}
}
}
save(m_nDim, m_nWidth, m_scores);
}
else
{
m_nCurrentIdx = m_scores.Count;
}
scores = m_scores;
}
float[] rgfRes = scores.Data;
SimpleDatum sdRes = new SimpleDatum(scores.Count, m_nWidth, 2, rgfRes, 0, rgfRes.Length);
data.SetData(sdRes);
m_nCurrentIdx = 0;
return(new Tuple <State, double, bool>(data, 0, false));
}
