/// <summary>
/// Release the unmanaged memory associated with this object
/// </summary>
protected override void DisposeObject()
{
if (_needDispose && (_ptr != IntPtr.Zero))
{
LinemodInvoke.cveLinemodMatchRelease(ref _ptr);
}
}
/// <summary>
/// Release the unmanaged memory associated with this object
/// </summary>
protected override void DisposeObject()
{
if (_sharedPtr != IntPtr.Zero)
{
LinemodInvoke.cveLinemodDetectorRelease(ref _sharedPtr);
_ptr = IntPtr.Zero;
}
}
/// <summary>
/// Add new object template.
/// </summary>
/// <param name="sources">Source images, one for each modality.</param>
/// <param name="classId">Object class ID.</param>
/// <param name="objectMask">Mask separating object from background.</param>
/// <param name="boundingBox">Return bounding box of the extracted features.</param>
/// <returns>Template ID, or -1 if failed to extract a valid template.</returns>
public int AddTemplate(
VectorOfMat sources,
String classId,
Mat objectMask,
ref Rectangle boundingBox)
{
using (CvString csClassId = new CvString(classId))
{
return(LinemodInvoke.cveLinemodDetectorAddTemplate(
_ptr,
sources,
csClassId,
objectMask,
ref boundingBox));
}
}
/// <summary>
/// Detect objects by template matching. Matches globally at the lowest pyramid level, then refines locally stepping up the pyramid.
/// </summary>
/// <param name="sources">Source images, one for each modality.</param>
/// <param name="threshold">Similarity threshold, a percentage between 0 and 100.</param>
/// <param name="matches">Template matches, sorted by similarity score.</param>
/// <param name="classIds">If non-empty, only search for the desired object classes.</param>
/// <param name="quantizedImages">Optionally return vector<Mat> of quantized images.</param>
/// <param name="masks">The masks for consideration during matching. The masks should be CV_8UC1 where 255 represents a valid pixel. If non-empty, the vector must be the same size as sources. Each element must be empty or the same size as its corresponding source.</param>
public void Match(
VectorOfMat sources,
float threshold,
VectorOfLinemodMatch matches,
VectorOfCvString classIds = null,
IOutputArrayOfArrays quantizedImages = null,
VectorOfMat masks = null)
{
using (OutputArray oaQuantizedImages =
quantizedImages == null ? OutputArray.GetEmpty() : quantizedImages.GetOutputArray())
{
LinemodInvoke.cveLinemodDetectorMatch(
_ptr,
sources,
threshold,
matches,
classIds,
oaQuantizedImages,
masks
);
}
}
/// <summary>
/// Create modality by name.
/// </summary>
/// <param name="modalityType">The following modality types are supported: "ColorGradient", "DepthNormal"</param>
public Modality(String modalityType)
{
using (CvString csModalityType = new CvString(modalityType))
_ptr = LinemodInvoke.cveLinemodModalityCreate(csModalityType, ref _sharedPtr);
}
/// <summary>
/// Create an empty template match result.
/// </summary>
public Match()
{
_ptr = LinemodInvoke.cveLinemodMatchCreate();
_needDispose = true;
}
/// <summary>
/// Write the detector to file storage
/// </summary>
/// <param name="fs">The file storage to write the detector into.</param>
public void Write(FileStorage fs)
{
LinemodInvoke.cveLinemodDetectorWrite(_ptr, fs);
}
/// <summary>
/// Read the detector from file node
/// </summary>
/// <param name="fn">The file node to read the detector from</param>
public void Read(FileNode fn)
{
LinemodInvoke.cveLinemodDetectorRead(_ptr, fn);
}
/// <summary>
/// Create a detector using LINE-MOD algorithm with color gradients and depth normals. Default parameter settings suitable for VGA images.
/// </summary>
public LinemodDetector()
{
_ptr = LinemodInvoke.cveLinemodLinemodDetectorCreate(ref _sharedPtr);
}
/// <summary>
/// Get sampling step T at <paramref name="pyramidLevel"/>.
/// </summary>
/// <param name="pyramidLevel">The pyramid level</param>
/// <returns>Sampling step T</returns>
public int GetT(int pyramidLevel)
{
return(LinemodInvoke.cveLinemodDetectorGetT(_ptr, pyramidLevel));
}
