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#ifndef OPENCV_CORE_EIGEN_HPP
#define OPENCV_CORE_EIGEN_HPP

#ifndef EIGEN_WORLD_VERSION
#error                                                                         \
    "Wrong usage of OpenCV's Eigen utility header. Include Eigen's headers first. See https://github.com/opencv/opencv/issues/17366"
#endif

#include "opencv2/core.hpp"

#if defined _MSC_VER && _MSC_VER >= 1200
#ifndef NOMINMAX
#define NOMINMAX // fix https://github.com/opencv/opencv/issues/17548
#endif
#pragma warning(disable : 4714) //__forceinline is not inlined
#pragma warning(disable : 4127) // conditional expression is constant
#pragma warning(disable : 4244) // conversion from '__int64' to 'int', possible
                                // loss of data
#endif

#if !defined(OPENCV_DISABLE_EIGEN_TENSOR_SUPPORT)
#if EIGEN_WORLD_VERSION == 3 && EIGEN_MAJOR_VERSION >= 3
#include <unsupported/Eigen/CXX11/Tensor>
#define OPENCV_EIGEN_TENSOR_SUPPORT 1
#endif // EIGEN_WORLD_VERSION == 3 && EIGEN_MAJOR_VERSION >= 3
#endif // !defined(OPENCV_DISABLE_EIGEN_TENSOR_SUPPORT)

namespace cv {

/** @addtogroup core_eigen
These functions are provided for OpenCV-Eigen interoperability. They convert
`Mat` objects to corresponding `Eigen::Matrix` objects and vice-versa. Consult
the [Eigen
documentation](https://eigen.tuxfamily.org/dox/group__TutorialMatrixClass.html)
for information about the `Matrix` template type.

@note Using these functions requires the `Eigen/Dense` or similar header to be
included before this header.
*/
//! @{

#if defined(OPENCV_EIGEN_TENSOR_SUPPORT) || defined(CV_DOXYGEN)
/** @brief Converts an Eigen::Tensor to a cv::Mat.

The method converts an Eigen::Tensor with shape (H x W x C) to a cv::Mat where:
 H = number of rows
 W = number of columns
 C = number of channels

Usage:
\code
Eigen::Tensor<float, 3, Eigen::RowMajor> a_tensor(...);
// populate tensor with values
Mat a_mat;
eigen2cv(a_tensor, a_mat);
\endcode
*/
template <typename _Tp, int _layout>
static inline void eigen2cv(const Eigen::Tensor<_Tp, 3, _layout> &src,
                            OutputArray dst) {
  if (!(_layout & Eigen::RowMajorBit)) {
    const std::array<int, 3> shuffle{2, 1, 0};
    Eigen::Tensor<_Tp, 3, !_layout> row_major_tensor =
        src.swap_layout().shuffle(shuffle);
    Mat _src(src.dimension(0), src.dimension(1),
             CV_MAKETYPE(DataType<_Tp>::type, src.dimension(2)),
             row_major_tensor.data());
    _src.copyTo(dst);
  } else {
    Mat _src(src.dimension(0), src.dimension(1),
             CV_MAKETYPE(DataType<_Tp>::type, src.dimension(2)),
             (void *)src.data());
    _src.copyTo(dst);
  }
}

/** @brief Converts a cv::Mat to an Eigen::Tensor.

The method converts a cv::Mat to an Eigen Tensor with shape (H x W x C) where:
 H = number of rows
 W = number of columns
 C = number of channels

Usage:
\code
Mat a_mat(...);
// populate Mat with values
Eigen::Tensor<float, 3, Eigen::RowMajor> a_tensor(...);
cv2eigen(a_mat, a_tensor);
\endcode
*/
template <typename _Tp, int _layout>
static inline void cv2eigen(const Mat &src,
                            Eigen::Tensor<_Tp, 3, _layout> &dst) {
  if (!(_layout & Eigen::RowMajorBit)) {
    Eigen::Tensor<_Tp, 3, !_layout> row_major_tensor(src.rows, src.cols,
                                                     src.channels());
    Mat _dst(src.rows, src.cols,
             CV_MAKETYPE(DataType<_Tp>::type, src.channels()),
             row_major_tensor.data());
    if (src.type() == _dst.type())
      src.copyTo(_dst);
    else
      src.convertTo(_dst, _dst.type());
    const std::array<int, 3> shuffle{2, 1, 0};
    dst = row_major_tensor.swap_layout().shuffle(shuffle);
  } else {
    dst.resize(src.rows, src.cols, src.channels());
    Mat _dst(src.rows, src.cols,
             CV_MAKETYPE(DataType<_Tp>::type, src.channels()), dst.data());
    if (src.type() == _dst.type())
      src.copyTo(_dst);
    else
      src.convertTo(_dst, _dst.type());
  }
}

/** @brief Maps cv::Mat data to an Eigen::TensorMap.

The method wraps an existing Mat data array with an Eigen TensorMap of shape (H
x W x C) where: H = number of rows W = number of columns C = number of channels

Explicit instantiation of the return type is required.

@note Caller should be aware of the lifetime of the cv::Mat instance and take
appropriate safety measures. The cv::Mat instance will retain ownership of the
data and the Eigen::TensorMap will lose access when the cv::Mat data is
deallocated.

The example below initializes a cv::Mat and produces an Eigen::TensorMap:
\code
float arr[] = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11};
Mat a_mat(2, 2, CV_32FC3, arr);
Eigen::TensorMap<Eigen::Tensor<float, 3, Eigen::RowMajor>> a_tensormap =
cv2eigen_tensormap<float>(a_mat);
\endcode
*/
template <typename _Tp>
static inline Eigen::TensorMap<Eigen::Tensor<_Tp, 3, Eigen::RowMajor>>
cv2eigen_tensormap(InputArray src) {
  Mat mat = src.getMat();
  CV_CheckTypeEQ(mat.type(),
                 CV_MAKETYPE(traits::Type<_Tp>::value, mat.channels()), "");
  return Eigen::TensorMap<Eigen::Tensor<_Tp, 3, Eigen::RowMajor>>(
      (_Tp *)mat.data, mat.rows, mat.cols, mat.channels());
}
#endif // OPENCV_EIGEN_TENSOR_SUPPORT

template <typename _Tp, int _rows, int _cols, int _options, int _maxRows,
          int _maxCols>
static inline void eigen2cv(
    const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols> &src,
    OutputArray dst) {
  if (!(src.Flags & Eigen::RowMajorBit)) {
    Mat _src(src.cols(), src.rows(), traits::Type<_Tp>::value,
             (void *)src.data(), src.outerStride() * sizeof(_Tp));
    transpose(_src, dst);
  } else {
    Mat _src(src.rows(), src.cols(), traits::Type<_Tp>::value,
             (void *)src.data(), src.outerStride() * sizeof(_Tp));
    _src.copyTo(dst);
  }
}

// Matx case
template <typename _Tp, int _rows, int _cols, int _options, int _maxRows,
          int _maxCols>
static inline void eigen2cv(
    const Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols> &src,
    Matx<_Tp, _rows, _cols> &dst) {
  if (!(src.Flags & Eigen::RowMajorBit)) {
    dst = Matx<_Tp, _cols, _rows>(static_cast<const _Tp *>(src.data())).t();
  } else {
    dst = Matx<_Tp, _rows, _cols>(static_cast<const _Tp *>(src.data()));
  }
}

template <typename _Tp, int _rows, int _cols, int _options, int _maxRows,
          int _maxCols>
static inline void
cv2eigen(const Mat &src,
         Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols> &dst) {
  CV_DbgAssert(src.rows == _rows && src.cols == _cols);
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    if (src.type() == _dst.type())
      transpose(src, _dst);
    else if (src.cols == src.rows) {
      src.convertTo(_dst, _dst.type());
      transpose(_dst, _dst);
    } else
      Mat(src.t()).convertTo(_dst, _dst.type());
  } else {
    const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    src.convertTo(_dst, _dst.type());
  }
}

// Matx case
template <typename _Tp, int _rows, int _cols, int _options, int _maxRows,
          int _maxCols>
static inline void
cv2eigen(const Matx<_Tp, _rows, _cols> &src,
         Eigen::Matrix<_Tp, _rows, _cols, _options, _maxRows, _maxCols> &dst) {
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(_cols, _rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    transpose(src, _dst);
  } else {
    const Mat _dst(_rows, _cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    Mat(src).copyTo(_dst);
  }
}

template <typename _Tp>
static inline void
cv2eigen(const Mat &src,
         Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic> &dst) {
  dst.resize(src.rows, src.cols);
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    if (src.type() == _dst.type())
      transpose(src, _dst);
    else if (src.cols == src.rows) {
      src.convertTo(_dst, _dst.type());
      transpose(_dst, _dst);
    } else
      Mat(src.t()).convertTo(_dst, _dst.type());
  } else {
    const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    src.convertTo(_dst, _dst.type());
  }
}

template <typename _Tp>
static inline void cv2eigen(
    const Mat &src,
    Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> &dst) {
  CV_CheckEQ(src.dims, 2, "");
  dst.resize(src.rows, src.cols);
  const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, dst.data(),
                 (size_t)(dst.outerStride() * sizeof(_Tp)));
  src.convertTo(_dst, _dst.type());
}

// Matx case
template <typename _Tp, int _rows, int _cols>
static inline void
cv2eigen(const Matx<_Tp, _rows, _cols> &src,
         Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic> &dst) {
  dst.resize(_rows, _cols);
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(_cols, _rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    transpose(src, _dst);
  } else {
    const Mat _dst(_rows, _cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    Mat(src).copyTo(_dst);
  }
}

template <typename _Tp, int _rows, int _cols>
static inline void cv2eigen(
    const Matx<_Tp, _rows, _cols> &src,
    Eigen::Matrix<_Tp, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> &dst) {
  CV_CheckEQ(src.dims, 2, "");
  dst.resize(_rows, _cols);
  const Mat _dst(_rows, _cols, traits::Type<_Tp>::value, dst.data(),
                 (size_t)(dst.outerStride() * sizeof(_Tp)));
  Mat(src).copyTo(_dst);
}

template <typename _Tp>
static inline void cv2eigen(const Mat &src,
                            Eigen::Matrix<_Tp, Eigen::Dynamic, 1> &dst) {
  CV_Assert(src.cols == 1);
  dst.resize(src.rows);

  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    if (src.type() == _dst.type())
      transpose(src, _dst);
    else
      Mat(src.t()).convertTo(_dst, _dst.type());
  } else {
    const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    src.convertTo(_dst, _dst.type());
  }
}

// Matx case
template <typename _Tp, int _rows>
static inline void cv2eigen(const Matx<_Tp, _rows, 1> &src,
                            Eigen::Matrix<_Tp, Eigen::Dynamic, 1> &dst) {
  dst.resize(_rows);

  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(1, _rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    transpose(src, _dst);
  } else {
    const Mat _dst(_rows, 1, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    src.copyTo(_dst);
  }
}

template <typename _Tp>
static inline void cv2eigen(const Mat &src,
                            Eigen::Matrix<_Tp, 1, Eigen::Dynamic> &dst) {
  CV_Assert(src.rows == 1);
  dst.resize(src.cols);
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(src.cols, src.rows, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    if (src.type() == _dst.type())
      transpose(src, _dst);
    else
      Mat(src.t()).convertTo(_dst, _dst.type());
  } else {
    const Mat _dst(src.rows, src.cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    src.convertTo(_dst, _dst.type());
  }
}

// Matx
template <typename _Tp, int _cols>
static inline void cv2eigen(const Matx<_Tp, 1, _cols> &src,
                            Eigen::Matrix<_Tp, 1, Eigen::Dynamic> &dst) {
  dst.resize(_cols);
  if (!(dst.Flags & Eigen::RowMajorBit)) {
    const Mat _dst(_cols, 1, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    transpose(src, _dst);
  } else {
    const Mat _dst(1, _cols, traits::Type<_Tp>::value, dst.data(),
                   (size_t)(dst.outerStride() * sizeof(_Tp)));
    Mat(src).copyTo(_dst);
  }
}

//! @}

} // namespace cv

#endif