void Integral::IntegralScan(IImage& Source, IImage& Dest)
{
PrepareFor(Source);
CheckSameSize(Source, Dest);
CheckFloat(Dest);
uint Width = Source.Width();
uint Height = Source.Height();
Kernel(scan1, Source, Dest, Width, Height);
if (GetNbGroupsW(Source) > 1)
{
make_kernel<Image2D, Image2D>(SelectProgram(Dest), "scan2")
(EnqueueArgs(*m_CL, NDRange(GetNbGroupsW(Source) - 1, Source.Height())), Dest, *m_VerticalJunctions);
}
#undef KERNEL_RANGE
#define KERNEL_RANGE(src_img) src_img.FullRange()
Kernel(scan3, In(Dest, *m_VerticalJunctions), Dest);
if (GetNbGroupsH(Source) > 1)
{
make_kernel<Image2D, Image2D>(SelectProgram(Dest), "scan4")
(EnqueueArgs(*m_CL, NDRange(Source.Width(), GetNbGroupsH(Source) - 1)), Dest, *m_HorizontalJunctions);
}
Kernel(scan5, In(Dest, *m_HorizontalJunctions), Dest);
}
void ImageProximityFFT::SqrDistance_Norm(Image& Source, Image& Template, Image& Dest)
{
CheckFloat(Dest);
CheckSameNbChannels(Source, Template);
CheckSameNbChannels(Source, Dest);
CheckSameSize(Source, Dest);
// Verify image size
if (Template.Width() > Source.Width() || Template.Height() > Source.Height())
throw cl::Error(CL_IMAGE_FORMAT_NOT_SUPPORTED, "The template image must be smaller than source image.");
// Verify image types
if(!SameType(Source, Template))
throw cl::Error(CL_IMAGE_FORMAT_MISMATCH, "The source image and the template image must be same type.");
PrepareFor(Source, Template);
m_integral.SqrIntegral(Source, *m_image_sqsums);
double templ_sqsum[4] = {0};
m_statistics.SumSqr(Template, templ_sqsum);
CrossCorr(Source, Template, Dest);
MatchSquareDiffNorm(Template.Width(), Template.Height(), *m_image_sqsums, templ_sqsum, Dest);
}
void Blob::ComputeLabels(IImage& Source, ImageBuffer& Labels, int ConnectType)
{
if (ConnectType != 4 && ConnectType != 8)
throw cl::Error(CL_INVALID_VALUE, "Wrong connect type in Blob::ComputeLabels");
if (Labels.Depth() != 32 || Labels.IsFloat())
throw cl::Error(CL_INVALID_VALUE, "Wrong Labels image type in Blob::ComputeLabels - Labels must be 32 bit integer");
if (m_TempBuffer == nullptr)
PrepareFor(Source);
CheckSameSize(Source, Labels);
CheckCompatibility(Labels, *m_TempBuffer);
m_BlobInfo.Init(ConnectType);
m_InfoBuffer.Send();
// Initialize the label image
Kernel(init_label, Source, Out(Labels, *m_TempBuffer), Labels.Step(), m_TempBuffer->Step(), m_InfoBuffer);
// These two labeling steps need to be executed at least twice each
int i = 0;
while (i <= m_BlobInfo.LastUsefulIteration)
{
i++;
Kernel(label_step1, Labels, *m_TempBuffer, Labels.Step(), m_TempBuffer->Step(), m_InfoBuffer, i);
Kernel(label_step2, Labels, *m_TempBuffer, Labels.Step(), m_TempBuffer->Step(), m_InfoBuffer, i);
if (i >= 2)
m_InfoBuffer.Read(true);
}
}
void ImageProximityFFT::Convolve(Image& Source, Image& Template, Image& Dest)
{
CheckSameSize(Source, Dest);
PrepareFor(Source, Template);
// Fill these images with black
m_transform.SetAll(*m_bigger_template, 0);
m_transform.SetAll(*m_bigger_source, 0);
for (uint i = 1; i <= Source.NbChannels(); i++)
{
// Copy the data from Source and Template in images that are F32 and are big enough
Kernel(copy_offset, In(Source), Out(*m_bigger_source), Source.Step(), m_bigger_source->Step(),
int(Template.Width()) / 2, int(Template.Height()) / 2, m_bigger_source->Width(), m_bigger_source->Height(), i);
Kernel(copy_offset, In(Template), Out(*m_bigger_template), Template.Step(), m_bigger_template->Step(),
0, 0, m_bigger_template->Width(), m_bigger_template->Height(), i);
// Forward FFT of Source and Template
m_fft.Forward(*m_bigger_source, *m_source_spect);
m_fft.Forward(*m_bigger_template, *m_templ_spect);
// We need to divide the values by the FFT area to get the proper
float Area = float(m_bigger_source->Width() * m_bigger_source->Height());
// Do the convolution using pointwise product of the spectrums
// See information here : http://en.wikipedia.org/wiki/Convolution_theorem
MulAndScaleSpectrums(*m_source_spect, *m_templ_spect, *m_result_spect, 1 / Area);
// Inverse FFT to get the result of the convolution
m_fft.Inverse(*m_result_spect, *m_bigger_source); // Reuse m_bigger_source image for the convolution result
// Copy the result to Dest
Kernel_(*m_CL, SelectProgram(Dest), copy_result, m_bigger_source->FullRange(), LOCAL_RANGE,
In(*m_bigger_source), Out(Dest), m_bigger_source->Step(), Dest.Step(), Dest.Width(), Dest.Height(), i);
}
}
void ImageProximityFFT::CrossCorr(Image& Source, Image& Template, Image& Dest)
{
CheckFloat(Dest);
CheckSameNbChannels(Source, Template);
CheckSameNbChannels(Source, Dest);
CheckSameSize(Source, Dest);
// Verify image size
if (Template.Width() > Source.Width() || Template.Height() > Source.Height())
throw cl::Error(CL_IMAGE_FORMAT_NOT_SUPPORTED, "The template image must be smaller than source image.");
// Verify image types
if(!SameType(Source, Template))
throw cl::Error(CL_IMAGE_FORMAT_MISMATCH, "The source image and the template image must be same type.");
PrepareFor(Source, Template);
Convolve(Source, Template, Dest); // Computes the cross correlation using FFT
}