/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions
 * are met:
 *  * Redistributions of source code must retain the above copyright
 *    notice, this list of conditions and the following disclaimer.
 *  * Redistributions in binary form must reproduce the above copyright
 *    notice, this list of conditions and the following disclaimer in the
 *    documentation and/or other materials provided with the distribution.
 *  * Neither the name of NVIDIA CORPORATION nor the names of its
 *    contributors may be used to endorse or promote products derived
 *    from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
 * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * 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,
 * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
 * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
 * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
 * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */

#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
#pragma warning(disable : 4819)
#define WINDOWS_LEAN_AND_MEAN
#define NOMINMAX
#include <windows.h>
#endif

#include <Exceptions.h>
#include <ImageIO.h>
#include <ImagesCPU.h>
#include <ImagesNPP.h>
#include <helper_cuda.h>
#include <npp.h>
#include <string.h>

#include <fstream>
#include <iostream>
#include <string>

#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
#define STRCASECMP _stricmp
#define STRNCASECMP _strnicmp
#else
#define STRCASECMP strcasecmp
#define STRNCASECMP strncasecmp
#endif

inline int cudaDeviceInit(int argc, const char **argv) {
  int deviceCount;
  checkCudaErrors(cudaGetDeviceCount(&deviceCount));

  if (deviceCount == 0) {
    std::cerr << "CUDA error: no devices supporting CUDA." << std::endl;
    exit(EXIT_FAILURE);
  }

  int dev = findCudaDevice(argc, argv);

  cudaDeviceProp deviceProp;
  cudaGetDeviceProperties(&deviceProp, dev);
  std::cerr << "cudaSetDevice GPU" << dev << " = " << deviceProp.name
            << std::endl;

  checkCudaErrors(cudaSetDevice(dev));

  return dev;
}

bool printfNPPinfo(int argc, char *argv[]) {
  const NppLibraryVersion *libVer = nppGetLibVersion();

  printf("NPP Library Version %d.%d.%d\n", libVer->major, libVer->minor,
         libVer->build);

  int driverVersion, runtimeVersion;
  cudaDriverGetVersion(&driverVersion);
  cudaRuntimeGetVersion(&runtimeVersion);

  printf("  CUDA Driver  Version: %d.%d\n", driverVersion / 1000,
         (driverVersion % 100) / 10);
  printf("  CUDA Runtime Version: %d.%d\n", runtimeVersion / 1000,
         (runtimeVersion % 100) / 10);

  // Min spec is SM 1.1 devices
  bool bVal = checkCudaCapabilities(1, 1);
  return bVal;
}

int main(int argc, char *argv[]) {
  printf("%s Starting...\n\n", argv[0]);

  try {
    std::string sFilename;
    char *filePath;

    cudaDeviceInit(argc, (const char **)argv);

    if (printfNPPinfo(argc, argv) == false) {
      exit(EXIT_SUCCESS);
    }

    if (checkCmdLineFlag(argc, (const char **)argv, "input")) {
      getCmdLineArgumentString(argc, (const char **)argv, "input", &filePath);
    } else {
      filePath = sdkFindFilePath("teapot512.pgm", argv[0]);
    }

    if (filePath) {
      sFilename = filePath;
    } else {
      sFilename = "teapot512.pgm";
    }

    // if we specify the filename at the command line, then we only test
    // sFilename.
    int file_errors = 0;
    std::ifstream infile(sFilename.data(), std::ifstream::in);

    if (infile.good()) {
      std::cout << "histEqualizationNPP opened: <" << sFilename.data()
                << "> successfully!" << std::endl;
      file_errors = 0;
      infile.close();
    } else {
      std::cout << "histEqualizationNPP unable to open: <" << sFilename.data()
                << ">" << std::endl;
      file_errors++;
      infile.close();
    }

    if (file_errors > 0) {
      exit(EXIT_FAILURE);
    }

    std::string dstFileName = sFilename;

    std::string::size_type dot = dstFileName.rfind('.');

    if (dot != std::string::npos) {
      dstFileName = dstFileName.substr(0, dot);
    }

    dstFileName += "_histEqualization.pgm";

    if (checkCmdLineFlag(argc, (const char **)argv, "output")) {
      char *outputFilePath;
      getCmdLineArgumentString(argc, (const char **)argv, "output",
                               &outputFilePath);
      dstFileName = outputFilePath;
    }

    npp::ImageCPU_8u_C1 oHostSrc;
    npp::loadImage(sFilename, oHostSrc);
    npp::ImageNPP_8u_C1 oDeviceSrc(oHostSrc);

    //
    // allocate arrays for histogram and levels
    //

    const int binCount = 255;
    const int levelCount = binCount + 1;  // levels array has one more element

    Npp32s *histDevice = 0;
    Npp32s *levelsDevice = 0;

    NPP_CHECK_CUDA(cudaMalloc((void **)&histDevice, binCount * sizeof(Npp32s)));
    NPP_CHECK_CUDA(
        cudaMalloc((void **)&levelsDevice, levelCount * sizeof(Npp32s)));

    //
    // compute histogram
    //

    NppiSize oSizeROI = {(int)oDeviceSrc.width(),
                         (int)oDeviceSrc.height()};  // full image
    // create device scratch buffer for nppiHistogram
    size_t nDeviceBufferSize;
    nppiHistogramEvenGetBufferSize_8u_C1R(oSizeROI, levelCount,
                                          &nDeviceBufferSize);
    Npp8u *pDeviceBuffer;
    NPP_CHECK_CUDA(cudaMalloc((void **)&pDeviceBuffer, nDeviceBufferSize));

    // compute levels values on host
    Npp32s levelsHost[levelCount];
    NPP_CHECK_NPP(nppiEvenLevelsHost_32s(levelsHost, levelCount, 0, binCount));
    // compute the histogram
    NPP_CHECK_NPP(nppiHistogramEven_8u_C1R(
        oDeviceSrc.data(), oDeviceSrc.pitch(), oSizeROI, histDevice, levelCount,
        0, binCount, pDeviceBuffer));
    // copy histogram and levels to host memory
    Npp32s histHost[binCount];
    NPP_CHECK_CUDA(cudaMemcpy(histHost, histDevice, binCount * sizeof(Npp32s),
                              cudaMemcpyDeviceToHost));

    Npp32s lutHost[levelCount];

    // fill LUT
    {
      Npp32s *pHostHistogram = histHost;
      Npp32s totalSum = 0;

      for (; pHostHistogram < histHost + binCount; ++pHostHistogram) {
        totalSum += *pHostHistogram;
      }

      NPP_ASSERT(totalSum <= oSizeROI.width * oSizeROI.height);

      if (totalSum == 0) {
        totalSum = 1;
      }

      float multiplier = 1.0f / float(oSizeROI.width * oSizeROI.height) * 0xFF;

      Npp32s runningSum = 0;
      Npp32s *pLookupTable = lutHost;

      for (pHostHistogram = histHost; pHostHistogram < histHost + binCount;
           ++pHostHistogram) {
        *pLookupTable = (Npp32s)(runningSum * multiplier + 0.5f);
        pLookupTable++;
        runningSum += *pHostHistogram;
      }

      lutHost[binCount] = 0xFF;  // last element is always 1
    }

    //
    // apply LUT transformation to the image
    //
    // Create a device image for the result.
    npp::ImageNPP_8u_C1 oDeviceDst(oDeviceSrc.size());

#if CUDART_VERSION >= 5000
    // Note for CUDA 5.0, that nppiLUT_Linear_8u_C1R requires these pointers to
    // be in GPU device memory
    Npp32s *lutDevice = 0;
    Npp32s *lvlsDevice = 0;

    NPP_CHECK_CUDA(
        cudaMalloc((void **)&lutDevice, sizeof(Npp32s) * (levelCount)));
    NPP_CHECK_CUDA(
        cudaMalloc((void **)&lvlsDevice, sizeof(Npp32s) * (levelCount)));

    NPP_CHECK_CUDA(cudaMemcpy(lutDevice, lutHost, sizeof(Npp32s) * (levelCount),
                              cudaMemcpyHostToDevice));
    NPP_CHECK_CUDA(cudaMemcpy(lvlsDevice, levelsHost,
                              sizeof(Npp32s) * (levelCount),
                              cudaMemcpyHostToDevice));

    NPP_CHECK_NPP(nppiLUT_Linear_8u_C1R(
        oDeviceSrc.data(), oDeviceSrc.pitch(), oDeviceDst.data(),
        oDeviceDst.pitch(), oSizeROI,
        lutDevice,  // value and level arrays are in GPU device memory
        lvlsDevice, levelCount));

    NPP_CHECK_CUDA(cudaFree(lutDevice));
    NPP_CHECK_CUDA(cudaFree(lvlsDevice));
#else
    NPP_CHECK_NPP(nppiLUT_Linear_8u_C1R(
        oDeviceSrc.data(), oDeviceSrc.pitch(), oDeviceDst.data(),
        oDeviceDst.pitch(), oSizeROI,
        lutHost,  // value and level arrays are in host memory
        levelsHost, levelCount));
#endif

    // copy the result image back into the storage that contained the
    // input image
    npp::ImageCPU_8u_C1 oHostDst(oDeviceDst.size());
    oDeviceDst.copyTo(oHostDst.data(), oHostDst.pitch());

    cudaFree(histDevice);
    cudaFree(levelsDevice);
    cudaFree(pDeviceBuffer);
    nppiFree(oDeviceSrc.data());
    nppiFree(oDeviceDst.data());

    // save the result
    npp::saveImage(dstFileName.c_str(), oHostDst);
    std::cout << "Saved image file " << dstFileName << std::endl;
    exit(EXIT_SUCCESS);
  } catch (npp::Exception &rException) {
    std::cerr << "Program error! The following exception occurred: \n";
    std::cerr << rException << std::endl;
    std::cerr << "Aborting." << std::endl;
    exit(EXIT_FAILURE);
  } catch (...) {
    std::cerr << "Program error! An unknow type of exception occurred. \n";
    std::cerr << "Aborting." << std::endl;
    exit(EXIT_FAILURE);
  }

  return 0;
}