/*
 * Created by Marcos Luciano
 * https://www.github.com/marcoslucianops
 */

#include "calibrator.h"

#include <fstream>
#include <iterator>

Int8EntropyCalibrator2::Int8EntropyCalibrator2(const int& batchSize, const int& channels, const int& height, const int& width,
    const float& scaleFactor, const float* offsets, const std::string& imgPath, const std::string& calibTablePath) :
    batchSize(batchSize), inputC(channels), inputH(height), inputW(width), scaleFactor(scaleFactor), offsets(offsets),
    calibTablePath(calibTablePath), imageIndex(0)
{
  inputCount = batchSize * channels * height * width;
  std::fstream f(imgPath);
  if (f.is_open()) {
      std::string temp;
      while (std::getline(f, temp)) {
        imgPaths.push_back(temp);
      }
  }
  batchData = new float[inputCount];
  CUDA_CHECK(cudaMalloc(&deviceInput, inputCount * sizeof(float)));
}

Int8EntropyCalibrator2::~Int8EntropyCalibrator2()
{
  CUDA_CHECK(cudaFree(deviceInput));
  if (batchData) {
    delete[] batchData;
  }
}

int
Int8EntropyCalibrator2::getBatchSize() const noexcept
{
  return batchSize;
}

bool
Int8EntropyCalibrator2::getBatch(void** bindings, const char** names, int nbBindings) noexcept
{
  if (imageIndex + batchSize > uint(imgPaths.size())) {
    return false;
  }

  float* ptr = batchData;
  for (size_t i = imageIndex; i < imageIndex + batchSize; ++i) {
    cv::Mat img = cv::imread(imgPaths[i]);
    if (img.empty()){
      std::cerr << "Failed to read image for calibration" << std::endl;
      return false;
    }
  
    std::vector<float> inputData = prepareImage(img, inputC, inputH, inputW, scaleFactor, offsets);

    size_t len = inputData.size();
    memcpy(ptr, inputData.data(), len * sizeof(float));
    ptr += inputData.size();

    std::cout << "Load image: " << imgPaths[i] << std::endl;
    std::cout << "Progress: " << (i + 1) * 100. / imgPaths.size() << "%" << std::endl;
  }

  imageIndex += batchSize;

  CUDA_CHECK(cudaMemcpy(deviceInput, batchData, inputCount * sizeof(float), cudaMemcpyHostToDevice));
  bindings[0] = deviceInput;

  return true;
}

const void*
Int8EntropyCalibrator2::readCalibrationCache(std::size_t &length) noexcept
{
  calibrationCache.clear();
  std::ifstream input(calibTablePath, std::ios::binary);
  input >> std::noskipws;
  if (readCache && input.good()) {
    std::copy(std::istream_iterator<char>(input), std::istream_iterator<char>(), std::back_inserter(calibrationCache));
  }
  length = calibrationCache.size();
  return length ? calibrationCache.data() : nullptr;
}

void
Int8EntropyCalibrator2::writeCalibrationCache(const void* cache, std::size_t length) noexcept
{
  std::ofstream output(calibTablePath, std::ios::binary);
  output.write(reinterpret_cast<const char*>(cache), length);
}

std::vector<float>
prepareImage(cv::Mat& img, int input_c, int input_h, int input_w, float scaleFactor, const float* offsets)
{
  cv::Mat out;

  cv::cvtColor(img, out, cv::COLOR_BGR2RGB);

  int image_w = img.cols;
  int image_h = img.rows;

  if (image_w != input_w || image_h != input_h) {
    float resizeFactor = std::max(input_w / (float) image_w, input_h / (float) img.rows);
    cv::resize(out, out, cv::Size(0, 0), resizeFactor, resizeFactor, cv::INTER_CUBIC);
    cv::Rect crop(cv::Point(0.5 * (out.cols - input_w), 0.5 * (out.rows - input_h)), cv::Size(input_w, input_h));
    out = out(crop);
  }

  out.convertTo(out, CV_32F, scaleFactor);
  cv::subtract(out, cv::Scalar(offsets[2] / 255, offsets[1] / 255, offsets[0] / 255), out, cv::noArray(), -1);

  std::vector<cv::Mat> input_channels(input_c);
  cv::split(out, input_channels);
  std::vector<float> result(input_h * input_w * input_c);
  auto data = result.data();
  int channelLength = input_h * input_w;
  for (int i = 0; i < input_c; ++i) {
    memcpy(data, input_channels[i].data, channelLength * sizeof(float));
    data += channelLength;
  }

  return result;
}