public static HClassSvm Deserialize(Stream stream)
{
HClassSvm hclassSvm = new HClassSvm();
hclassSvm.DeserializeClassSvm(HSerializedItem.Deserialize(stream));
return(hclassSvm);
}
/// <summary>
/// Selects an optimal combination of features to classify the provided data.
/// Instance represents: Handle of the training data.
/// </summary>
/// <param name="selectionMethod">Method to perform the selection. Default: "greedy"</param>
/// <param name="genParamName">Names of generic parameters to configure the selection process and the classifier. Default: []</param>
/// <param name="genParamValue">Values of generic parameters to configure the selection process and the classifier. Default: []</param>
/// <param name="selectedFeatureIndices">The selected feature set, contains indices.</param>
/// <param name="score">The achieved score using two-fold cross-validation.</param>
/// <returns>A trained SVM classifier using only the selected features.</returns>
public HClassSvm SelectFeatureSetSvm(
string selectionMethod,
string genParamName,
double genParamValue,
out HTuple selectedFeatureIndices,
out HTuple score)
{
IntPtr proc = HalconAPI.PreCall(1800);
this.Store(proc, 0);
HalconAPI.StoreS(proc, 1, selectionMethod);
HalconAPI.StoreS(proc, 2, genParamName);
HalconAPI.StoreD(proc, 3, genParamValue);
HalconAPI.InitOCT(proc, 0);
HalconAPI.InitOCT(proc, 1);
HalconAPI.InitOCT(proc, 2);
int err1 = HalconAPI.CallProcedure(proc);
HClassSvm hclassSvm;
int err2 = HClassSvm.LoadNew(proc, 0, err1, out hclassSvm);
int err3 = HTuple.LoadNew(proc, 1, err2, out selectedFeatureIndices);
int procResult = HTuple.LoadNew(proc, 2, HTupleType.DOUBLE, err3, out score);
HalconAPI.PostCall(proc, procResult);
GC.KeepAlive((object)this);
return(hclassSvm);
}
public HClassSvm Clone()
{
HSerializedItem serializedItemHandle = this.SerializeClassSvm();
HClassSvm hclassSvm = new HClassSvm();
hclassSvm.DeserializeClassSvm(serializedItemHandle);
serializedItemHandle.Dispose();
return(hclassSvm);
}
/// <summary>
/// Add training data to a support vector machine (SVM).
/// Instance represents: Training data for a classifier.
/// </summary>
/// <param name="SVMHandle">Handle of a SVM which receives the training data.</param>
public void AddClassTrainDataSvm(HClassSvm SVMHandle)
{
IntPtr proc = HalconAPI.PreCall(1792);
this.Store(proc, 1);
HalconAPI.Store(proc, 0, (HTool)SVMHandle);
int procResult = HalconAPI.CallProcedure(proc);
HalconAPI.PostCall(proc, procResult);
GC.KeepAlive((object)this);
GC.KeepAlive((object)SVMHandle);
}
internal static int LoadNew(IntPtr proc, int parIndex, int err, out HClassSvm[] obj)
{
HTuple tuple;
err = HTuple.LoadNew(proc, parIndex, err, out tuple);
obj = new HClassSvm[tuple.Length];
for (int index = 0; index < tuple.Length; ++index)
{
obj[index] = new HClassSvm(tuple[index].IP);
}
return(err);
}
/// <summary>
/// Get the training data of a support vector machine (SVM).
/// Modified instance represents: Handle of the training data of the classifier.
/// </summary>
/// <param name="SVMHandle">Handle of a SVM that contains training data.</param>
public void GetClassTrainDataSvm(HClassSvm SVMHandle)
{
this.Dispose();
IntPtr proc = HalconAPI.PreCall(1791);
HalconAPI.Store(proc, 0, (HTool)SVMHandle);
HalconAPI.InitOCT(proc, 0);
int err = HalconAPI.CallProcedure(proc);
int procResult = this.Load(proc, 0, err);
HalconAPI.PostCall(proc, procResult);
GC.KeepAlive((object)this);
GC.KeepAlive((object)SVMHandle);
}
/// <summary>
/// Approximate a trained support vector machine by a reduced support vector machine for faster classification.
/// Instance represents: Original SVM handle.
/// </summary>
/// <param name="method">Type of postprocessing to reduce number of SV. Default: "bottom_up"</param>
/// <param name="minRemainingSV">Minimum number of remaining SVs. Default: 2</param>
/// <param name="maxError">Maximum allowed error of reduction. Default: 0.001</param>
/// <returns>SVMHandle of reduced SVM.</returns>
public HClassSvm ReduceClassSvm(string method, int minRemainingSV, double maxError)
{
IntPtr proc = HalconAPI.PreCall(1852);
this.Store(proc, 0);
HalconAPI.StoreS(proc, 1, method);
HalconAPI.StoreI(proc, 2, minRemainingSV);
HalconAPI.StoreD(proc, 3, maxError);
HalconAPI.InitOCT(proc, 0);
int err = HalconAPI.CallProcedure(proc);
HClassSvm hclassSvm;
int procResult = HClassSvm.LoadNew(proc, 0, err, out hclassSvm);
HalconAPI.PostCall(proc, procResult);
GC.KeepAlive((object)this);
return(hclassSvm);
}
/// <summary>
/// Create a look-up table using a Support-Vector-Machine to classify byte images.
/// Modified instance represents: Handle of the LUT classifier.
/// </summary>
/// <param name="SVMHandle">SVM handle.</param>
/// <param name="genParamName">Names of the generic parameters that can be adjusted for the LUT classifier creation. Default: []</param>
/// <param name="genParamValue">Values of the generic parameters that can be adjusted for the LUT classifier creation. Default: []</param>
public HClassLUT(HClassSvm SVMHandle, HTuple genParamName, HTuple genParamValue)
{
IntPtr proc = HalconAPI.PreCall(1821);
HalconAPI.Store(proc, 0, (HTool)SVMHandle);
HalconAPI.Store(proc, 1, genParamName);
HalconAPI.Store(proc, 2, genParamValue);
HalconAPI.InitOCT(proc, 0);
int err = HalconAPI.CallProcedure(proc);
HalconAPI.UnpinTuple(genParamName);
HalconAPI.UnpinTuple(genParamValue);
int procResult = this.Load(proc, 0, err);
HalconAPI.PostCall(proc, procResult);
GC.KeepAlive((object)this);
GC.KeepAlive((object)SVMHandle);
}
internal static int LoadNew(IntPtr proc, int parIndex, int err, out HClassSvm obj)
{
obj = new HClassSvm(HTool.UNDEF);
return(obj.Load(proc, parIndex, err));
}