FFT

Overview

The FFT application outputs a spectrum representation of an input image, saving it into spectrum.png. The user can define what backend will be used for processing.

This sample shows the following:

• Creating and destroying a VPI stream.
• Wrapping an image hosted on CPU (the input) to be used by VPI.
• Convert an image to another format
• Creating a VPI-managed 2D image where output will be written to.
• Create a FFT algorithm and call it.
• Simple stream synchronization.
• Image locking to access its contents from CPU side.
• Interpret and process the resulting spectrum information.
• Error handling.
• Environment clean up.

Instructions

The usage is:

./vpi_sample_07_fft <backend> <input image>

where

• backend: either cpu or cuda; it defines the backend that will perform the processing.
• input image: input image file name; it accepts png, jpeg and possibly others.

Note

Currently FFT isn't available on PVA backend.

Here's one example:

./vpi_sample_07_fft cpu ../assets/kodim8.png

This is using the CUDA backend and one of the provided sample images. You can try with other images, respecting the constraints imposed by the algorithm.

Results

Input image	Output image, spectrum

Source code

For convenience, here's the code that is also installed in the samples directory.

/*
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*
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*    contributors may be used to endorse or promote products derived
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*
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
 
#include <opencv2/core/version.hpp>
#if CV_MAJOR_VERSION >= 3
#    include <opencv2/imgcodecs.hpp>
#else
#    include <opencv2/highgui/highgui.hpp>
#endif
 
#include <vpi/Image.h>
#include <vpi/Status.h>
#include <vpi/Stream.h>
#include <vpi/algo/ConvertImageFormat.h>
#include <vpi/algo/FFT.h>
 
#include <cstring> // for memset
#include <iostream>
#include <sstream>
 
#define CHECK_STATUS(STMT)                                    \
    do                                                        \
    {                                                         \
        VPIStatus status = (STMT);                            \
        if (status != VPI_SUCCESS)                            \
        {                                                     \
            char buffer[VPI_MAX_STATUS_MESSAGE_LENGTH];       \
            vpiGetLastStatusMessage(buffer, sizeof(buffer));  \
            std::ostringstream ss;                            \
            ss << vpiStatusGetName(status) << ": " << buffer; \
            throw std::runtime_error(ss.str());               \
        }                                                     \
    } while (0);
 
// Auxiliary functions to process spectrum before saving it to disk.
cv::Mat LogMagnitude(cv::Mat cpx);
cv::Mat CompleteFullHermitian(cv::Mat in, cv::Size fullSize);
cv::Mat InplaceFFTShift(cv::Mat mag);
 
int main(int argc, char *argv[])
{
    VPIImage image    = NULL;
    VPIImage imageF32 = NULL;
    VPIImage spectrum = NULL;
    VPIStream stream  = NULL;
    VPIPayload fft    = NULL;
 
    int retval = 0;
 
    try
    {
        if (argc != 3)
        {
            throw std::runtime_error(std::string("Usage: ") + argv[0] + " <cpu|cuda> <input image>");
        }
 
        std::string strBackend       = argv[1];
        std::string strInputFileName = argv[2];
 
        // Load the input image
        cv::Mat cvImage = cv::imread(strInputFileName, cv::IMREAD_GRAYSCALE);
        if (cvImage.empty())
        {
            throw std::runtime_error("Can't open '" + strInputFileName + "'");
        }
 
        assert(cvImage.type() == CV_8UC1);
 
        // Now parse the backend
        VPIBackend backendType;
 
        if (strBackend == "cpu")
        {
            backendType = VPI_BACKEND_CPU;
        }
        else if (strBackend == "cuda")
        {
            backendType = VPI_BACKEND_CUDA;
        }
        else
        {
            throw std::runtime_error("Backend '" + strBackend + "' not recognized, it must be either cpu or cuda.");
        }
 
        // Create the stream for the given backend.
        CHECK_STATUS(vpiStreamCreate(backendType, &stream));
 
        // We now wrap the loaded image into a VPIImage object to be used by VPI.
        {
            // First fill VPIImageData with the, well, image data...
            VPIImageData imgData;
            memset(&imgData, 0, sizeof(imgData));
            imgData.type                 = VPI_IMAGE_FORMAT_U8;
            imgData.numPlanes            = 1;
            imgData.planes[0].width      = cvImage.cols;
            imgData.planes[0].height     = cvImage.rows;
            imgData.planes[0].pitchBytes = cvImage.step[0];
            imgData.planes[0].data       = cvImage.data;
 
            // Wrap it into a VPIImage. VPI won't make a copy of it, so the original
            // image must be in scope at all times.
            CHECK_STATUS(vpiImageCreateHostMemWrapper(&imgData, 0, &image));
        }
 
        // Temporary image that holds the float version of input
        CHECK_STATUS(vpiImageCreate(cvImage.cols, cvImage.rows, VPI_IMAGE_FORMAT_F32, 0, &imageF32));
 
        // Now create the output image. Note that for real inputs, the output spectrum is a Hermitian
        // matrix (conjugate-symmetric), so only the non-redundant components are output, basically the
        // left half. We adjust the output width accordingly.
        CHECK_STATUS(vpiImageCreate(cvImage.cols / 2 + 1, cvImage.rows, VPI_IMAGE_FORMAT_2F32, 0, &spectrum));
 
        // Create the FFT payload that does real (space) to complex (frequency) transformation
        CHECK_STATUS(
            vpiCreateFFT(backendType, cvImage.cols, cvImage.rows, VPI_IMAGE_FORMAT_F32, VPI_IMAGE_FORMAT_2F32, &fft));
 
        // Now our processing pipeline:
 
        // Convert image to float
        CHECK_STATUS(vpiSubmitConvertImageFormat(stream, backendType, image, imageF32, VPI_CONVERSION_CAST, 1, 0));
 
        // Submit it for processing passing the image to be gradient and the result image
        CHECK_STATUS(vpiSubmitFFT(stream, fft, imageF32, spectrum, 0));
 
        // Wait until the algorithm finishes processing
        CHECK_STATUS(vpiStreamSync(stream));
 
        // Now let's retrieve the result spectrum
        {
            // Lock output image to retrieve its data on cpu memory
            VPIImageData outData;
            CHECK_STATUS(vpiImageLock(spectrum, VPI_LOCK_READ, &outData));
 
            assert(outData.type == VPI_IMAGE_FORMAT_2F32);
 
            // Wrap spectrum to be used by OpenCV
            cv::Mat cvSpectrum(outData.planes[0].height, outData.planes[0].width, CV_32FC2, outData.planes[0].data,
                               outData.planes[0].pitchBytes);
 
            // Process it
            cv::Mat mag = InplaceFFTShift(LogMagnitude(CompleteFullHermitian(cvSpectrum, cvImage.size())));
 
            // Normalize the result to fit in 8-bits
            normalize(mag, mag, 0, 255, cv::NORM_MINMAX);
 
            // Write to disk
            imwrite("spectrum_" + strBackend + ".png", mag);
 
            // Done handling output image, don't forget to unlock it.
            CHECK_STATUS(vpiImageUnlock(spectrum));
        }
    }
    catch (std::exception &e)
    {
        std::cerr << e.what() << std::endl;
        retval = 1;
    }
 
    // Clean up
 
    // Make sure stream is synchronized before destroying the objects
    // that might still be in use.
    if (stream != NULL)
    {
        vpiStreamSync(stream);
    }
 
    vpiImageDestroy(image);
    vpiImageDestroy(imageF32);
    vpiImageDestroy(spectrum);
    vpiStreamDestroy(stream);
 
    // Payload is owned by the stream, so it's already destroyed
    // since the stream is now destroyed.
 
    return retval;
}
 
// Auxiliary functions --------------------------------
 
cv::Mat LogMagnitude(cv::Mat cpx)
{
    // Split spectrum into real and imaginary parts
    cv::Mat reim[2];
    assert(cpx.channels() == 2);
    split(cpx, reim);
 
    // Calculate the magnitude
    cv::Mat mag;
    magnitude(reim[0], reim[1], mag);
 
    // Convert to logarithm scale
    mag += cv::Scalar::all(1);
    log(mag, mag);
    mag = mag(cv::Rect(0, 0, mag.cols & -2, mag.rows & -2));
 
    return mag;
}
 
cv::Mat CompleteFullHermitian(cv::Mat in, cv::Size fullSize)
{
    assert(in.type() == CV_32FC2);
 
    cv::Mat out(fullSize, CV_32FC2);
    for (int i = 0; i < out.rows; ++i)
    {
        for (int j = 0; j < out.cols; ++j)
        {
            cv::Vec2f p;
            if (j < in.cols)
            {
                p = in.at<cv::Vec2f>(i, j);
            }
            else
            {
                p    = in.at<cv::Vec2f>((out.rows - i) % out.rows, (out.cols - j) % out.cols);
                p[1] = -p[1];
            }
            out.at<cv::Vec2f>(i, j) = p;
        }
    }
 
    return out;
}
 
cv::Mat InplaceFFTShift(cv::Mat mag)
{
    // Rearrange the quadrants of the fourier spectrum
    // so that the origin is at the image center.
 
    // Create a ROI for each 4 quadrants.
    int cx = mag.cols / 2;
    int cy = mag.rows / 2;
    cv::Mat qTL(mag, cv::Rect(0, 0, cx, cy));   // top-left
    cv::Mat qTR(mag, cv::Rect(cx, 0, cx, cy));  // top-right
    cv::Mat qBL(mag, cv::Rect(0, cy, cx, cy));  // bottom-left
    cv::Mat qBR(mag, cv::Rect(cx, cy, cx, cy)); // bottom-right
 
    // swap top-left with bottom-right quadrants
    cv::Mat tmp;
    qTL.copyTo(tmp);
    qBR.copyTo(qTL);
    tmp.copyTo(qBR);
 
    // swap top-right with bottom-left quadrants
    qTR.copyTo(tmp);
    qBL.copyTo(qTR);
    tmp.copyTo(qBL);
 
    return mag;
}