// Copyright (c) the JPEG XL Project Authors. All rights reserved.
//
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

#include "lib/jxl/enc_xyb.h"

#include <jxl/memory_manager.h>

#include <algorithm>
#include <cstdlib>

#undef HWY_TARGET_INCLUDE
#define HWY_TARGET_INCLUDE "lib/jxl/enc_xyb.cc"
#include <hwy/foreach_target.h>
#include <hwy/highway.h>

#include "lib/jxl/base/compiler_specific.h"
#include "lib/jxl/base/data_parallel.h"
#include "lib/jxl/base/fast_math-inl.h"
#include "lib/jxl/base/rect.h"
#include "lib/jxl/base/status.h"
#include "lib/jxl/cms/opsin_params.h"
#include "lib/jxl/cms/transfer_functions-inl.h"
#include "lib/jxl/color_encoding_internal.h"
#include "lib/jxl/enc_image_bundle.h"
#include "lib/jxl/image_bundle.h"
#include "lib/jxl/image_ops.h"

HWY_BEFORE_NAMESPACE();
namespace jxl {
namespace HWY_NAMESPACE {

// These templates are not found via ADL.
using hwy::HWY_NAMESPACE::Add;
using hwy::HWY_NAMESPACE::Mul;
using hwy::HWY_NAMESPACE::MulAdd;
using hwy::HWY_NAMESPACE::Sub;
using hwy::HWY_NAMESPACE::ZeroIfNegative;

// 4x3 matrix * 3x1 SIMD vectors
template <class V>
JXL_INLINE void OpsinAbsorbance(const V r, const V g, const V b,
                                const float* JXL_RESTRICT premul_absorb,
                                V* JXL_RESTRICT mixed0, V* JXL_RESTRICT mixed1,
                                V* JXL_RESTRICT mixed2) {
  const float* bias = jxl::cms::kOpsinAbsorbanceBias.data();
  const HWY_FULL(float) d;
  const size_t N = Lanes(d);
  const auto m0 = Load(d, premul_absorb + 0 * N);
  const auto m1 = Load(d, premul_absorb + 1 * N);
  const auto m2 = Load(d, premul_absorb + 2 * N);
  const auto m3 = Load(d, premul_absorb + 3 * N);
  const auto m4 = Load(d, premul_absorb + 4 * N);
  const auto m5 = Load(d, premul_absorb + 5 * N);
  const auto m6 = Load(d, premul_absorb + 6 * N);
  const auto m7 = Load(d, premul_absorb + 7 * N);
  const auto m8 = Load(d, premul_absorb + 8 * N);
  *mixed0 = MulAdd(m0, r, MulAdd(m1, g, MulAdd(m2, b, Set(d, bias[0]))));
  *mixed1 = MulAdd(m3, r, MulAdd(m4, g, MulAdd(m5, b, Set(d, bias[1]))));
  *mixed2 = MulAdd(m6, r, MulAdd(m7, g, MulAdd(m8, b, Set(d, bias[2]))));
}

template <class V>
void StoreXYB(const V r, V g, const V b, float* JXL_RESTRICT valx,
              float* JXL_RESTRICT valy, float* JXL_RESTRICT valz) {
  const HWY_FULL(float) d;
  const V half = Set(d, 0.5f);
  Store(Mul(half, Sub(r, g)), d, valx);
  Store(Mul(half, Add(r, g)), d, valy);
  Store(b, d, valz);
}

// Converts one RGB vector to XYB.
template <class V>
void LinearRGBToXYB(const V r, const V g, const V b,
                    const float* JXL_RESTRICT premul_absorb,
                    float* JXL_RESTRICT valx, float* JXL_RESTRICT valy,
                    float* JXL_RESTRICT valz) {
  V mixed0;
  V mixed1;
  V mixed2;
  OpsinAbsorbance(r, g, b, premul_absorb, &mixed0, &mixed1, &mixed2);

  // mixed* should be non-negative even for wide-gamut, so clamp to zero.
  mixed0 = ZeroIfNegative(mixed0);
  mixed1 = ZeroIfNegative(mixed1);
  mixed2 = ZeroIfNegative(mixed2);

  const HWY_FULL(float) d;
  const size_t N = Lanes(d);
  mixed0 = CubeRootAndAdd(mixed0, Load(d, premul_absorb + 9 * N));
  mixed1 = CubeRootAndAdd(mixed1, Load(d, premul_absorb + 10 * N));
  mixed2 = CubeRootAndAdd(mixed2, Load(d, premul_absorb + 11 * N));
  StoreXYB(mixed0, mixed1, mixed2, valx, valy, valz);

  // For wide-gamut inputs, r/g/b and valx (but not y/z) are often negative.
}

void LinearRGBRowToXYB(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,
                       float* JXL_RESTRICT row2,
                       const float* JXL_RESTRICT premul_absorb, size_t xsize) {
  const HWY_FULL(float) d;
  for (size_t x = 0; x < xsize; x += Lanes(d)) {
    const auto r = Load(d, row0 + x);
    const auto g = Load(d, row1 + x);
    const auto b = Load(d, row2 + x);
    LinearRGBToXYB(r, g, b, premul_absorb, row0 + x, row1 + x, row2 + x);
  }
}

// Input/output uses the codec.h scaling: nominally 0-1 if in-gamut.
template <class V>
V LinearFromSRGB(V encoded) {
  return TF_SRGB().DisplayFromEncoded(encoded);
}

Status LinearSRGBToXYB(const float* JXL_RESTRICT premul_absorb,
                       ThreadPool* pool, Image3F* JXL_RESTRICT image) {
  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;
  const auto process_row = [&](const uint32_t task,
                               size_t /*thread*/) -> Status {
    const size_t y = static_cast<size_t>(task);
    float* JXL_RESTRICT row0 = image->PlaneRow(0, y);
    float* JXL_RESTRICT row1 = image->PlaneRow(1, y);
    float* JXL_RESTRICT row2 = image->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {
      const auto in_r = Load(d, row0 + x);
      const auto in_g = Load(d, row1 + x);
      const auto in_b = Load(d, row2 + x);
      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row0 + x, row1 + x,
                     row2 + x);
    }
    return true;
  };
  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),
                                ThreadPool::NoInit, process_row,
                                "LinearToXYB"));
  return true;
}

Status SRGBToXYB(const float* JXL_RESTRICT premul_absorb, ThreadPool* pool,
                 Image3F* JXL_RESTRICT image) {
  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;
  const auto process_row = [&](const uint32_t task,
                               size_t /*thread*/) -> Status {
    const size_t y = static_cast<size_t>(task);
    float* JXL_RESTRICT row0 = image->PlaneRow(0, y);
    float* JXL_RESTRICT row1 = image->PlaneRow(1, y);
    float* JXL_RESTRICT row2 = image->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {
      const auto in_r = LinearFromSRGB(Load(d, row0 + x));
      const auto in_g = LinearFromSRGB(Load(d, row1 + x));
      const auto in_b = LinearFromSRGB(Load(d, row2 + x));
      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row0 + x, row1 + x,
                     row2 + x);
    }
    return true;
  };
  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),
                                ThreadPool::NoInit, process_row, "SRGBToXYB"));
  return true;
}

Status SRGBToXYBAndLinear(const float* JXL_RESTRICT premul_absorb,
                          ThreadPool* pool, Image3F* JXL_RESTRICT image,
                          Image3F* JXL_RESTRICT linear) {
  const size_t xsize = image->xsize();

  const HWY_FULL(float) d;
  const auto process_row = [&](const uint32_t task,
                               size_t /*thread*/) -> Status {
    const size_t y = static_cast<size_t>(task);
    float* JXL_RESTRICT row_image0 = image->PlaneRow(0, y);
    float* JXL_RESTRICT row_image1 = image->PlaneRow(1, y);
    float* JXL_RESTRICT row_image2 = image->PlaneRow(2, y);
    float* JXL_RESTRICT row_linear0 = linear->PlaneRow(0, y);
    float* JXL_RESTRICT row_linear1 = linear->PlaneRow(1, y);
    float* JXL_RESTRICT row_linear2 = linear->PlaneRow(2, y);

    for (size_t x = 0; x < xsize; x += Lanes(d)) {
      const auto in_r = LinearFromSRGB(Load(d, row_image0 + x));
      const auto in_g = LinearFromSRGB(Load(d, row_image1 + x));
      const auto in_b = LinearFromSRGB(Load(d, row_image2 + x));

      Store(in_r, d, row_linear0 + x);
      Store(in_g, d, row_linear1 + x);
      Store(in_b, d, row_linear2 + x);

      LinearRGBToXYB(in_r, in_g, in_b, premul_absorb, row_image0 + x,
                     row_image1 + x, row_image2 + x);
    }
    return true;
  };
  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<uint32_t>(image->ysize()),
                                ThreadPool::NoInit, process_row,
                                "SRGBToXYBAndLinear"));
  return true;
}

void ComputePremulAbsorb(float intensity_target, float* premul_absorb) {
  const HWY_FULL(float) d;
  const size_t N = Lanes(d);
  const float mul = intensity_target / 255.0f;
  for (size_t j = 0; j < 3; ++j) {
    for (size_t i = 0; i < 3; ++i) {
      const auto absorb = Set(d, jxl::cms::kOpsinAbsorbanceMatrix[j][i] * mul);
      Store(absorb, d, premul_absorb + (j * 3 + i) * N);
    }
  }
  for (size_t i = 0; i < 3; ++i) {
    const auto neg_bias_cbrt =
        Set(d, -cbrtf(jxl::cms::kOpsinAbsorbanceBias[i]));
    Store(neg_bias_cbrt, d, premul_absorb + (9 + i) * N);
  }
}

// This is different from Butteraugli's OpsinDynamicsImage() in the sense that
// it does not contain a sensitivity multiplier based on the blurred image.
Status ToXYB(const ColorEncoding& c_current, float intensity_target,
             const ImageF* black, ThreadPool* pool, Image3F* JXL_RESTRICT image,
             const JxlCmsInterface& cms, Image3F* const JXL_RESTRICT linear) {
  if (black) JXL_ENSURE(SameSize(*image, *black));
  if (linear) JXL_ENSURE(SameSize(*image, *linear));

  const HWY_FULL(float) d;
  // Pre-broadcasted constants
  HWY_ALIGN float premul_absorb[MaxLanes(d) * 12];
  ComputePremulAbsorb(intensity_target, premul_absorb);

  const bool want_linear = linear != nullptr;

  const ColorEncoding& c_linear_srgb =
      ColorEncoding::LinearSRGB(c_current.IsGray());
  // Linear sRGB inputs are rare but can be useful for the fastest encoders, for
  // which undoing the sRGB transfer function would be a large part of the cost.
  if (c_linear_srgb.SameColorEncoding(c_current)) {
    // This only happens if kitten or slower, moving ImageBundle might be
    // possible but the encoder is much slower than this copy.
    if (want_linear) {
      JXL_RETURN_IF_ERROR(CopyImageTo(*image, linear));
    }
    JXL_RETURN_IF_ERROR(LinearSRGBToXYB(premul_absorb, pool, image));
    return true;
  }

  // Common case: already sRGB, can avoid the color transform
  if (c_current.IsSRGB()) {
    // Common case: can avoid allocating/copying
    if (want_linear) {
      // Slow encoder also wants linear sRGB.
      JXL_RETURN_IF_ERROR(
          SRGBToXYBAndLinear(premul_absorb, pool, image, linear));
    } else {
      JXL_RETURN_IF_ERROR(SRGBToXYB(premul_absorb, pool, image));
    }
    return true;
  }

  JXL_RETURN_IF_ERROR(ApplyColorTransform(
      c_current, intensity_target, *image, black, Rect(*image), c_linear_srgb,
      cms, pool, want_linear ? linear : image));
  if (want_linear) {
    JXL_RETURN_IF_ERROR(CopyImageTo(*linear, image));
  }
  JXL_RETURN_IF_ERROR(LinearSRGBToXYB(premul_absorb, pool, image));
  return true;
}

// Transform RGB to YCbCr.
// Could be performed in-place (i.e. Y, Cb and Cr could alias R, B and B).
Status RgbToYcbcr(const ImageF& r_plane, const ImageF& g_plane,
                  const ImageF& b_plane, ImageF* y_plane, ImageF* cb_plane,
                  ImageF* cr_plane, ThreadPool* pool) {
  const HWY_FULL(float) df;
  const size_t S = Lanes(df);  // Step.

  const size_t xsize = r_plane.xsize();
  const size_t ysize = r_plane.ysize();
  if ((xsize == 0) || (ysize == 0)) return true;

  // Full-range BT.601 as defined by JFIF Clause 7:
  // https://www.itu.int/rec/T-REC-T.871-201105-I/en
  const auto k128 = Set(df, 128.0f / 255);
  const auto kR = Set(df, 0.299f);  // NTSC luma
  const auto kG = Set(df, 0.587f);
  const auto kB = Set(df, 0.114f);
  const auto kAmpR = Set(df, 0.701f);
  const auto kAmpB = Set(df, 0.886f);
  const auto kDiffR = Add(kAmpR, kR);
  const auto kDiffB = Add(kAmpB, kB);
  const auto kNormR = Div(Set(df, 1.0f), (Add(kAmpR, Add(kG, kB))));
  const auto kNormB = Div(Set(df, 1.0f), (Add(kR, Add(kG, kAmpB))));

  constexpr size_t kGroupArea = kGroupDim * kGroupDim;
  const size_t lines_per_group = DivCeil(kGroupArea, xsize);
  const size_t num_stripes = DivCeil(ysize, lines_per_group);
  const auto transform = [&](int idx, int /* thread*/) -> Status {
    const size_t y0 = idx * lines_per_group;
    const size_t y1 = std::min<size_t>(y0 + lines_per_group, ysize);
    for (size_t y = y0; y < y1; ++y) {
      const float* r_row = r_plane.ConstRow(y);
      const float* g_row = g_plane.ConstRow(y);
      const float* b_row = b_plane.ConstRow(y);
      float* y_row = y_plane->Row(y);
      float* cb_row = cb_plane->Row(y);
      float* cr_row = cr_plane->Row(y);
      for (size_t x = 0; x < xsize; x += S) {
        const auto r = Load(df, r_row + x);
        const auto g = Load(df, g_row + x);
        const auto b = Load(df, b_row + x);
        const auto r_base = Mul(r, kR);
        const auto r_diff = Mul(r, kDiffR);
        const auto g_base = Mul(g, kG);
        const auto b_base = Mul(b, kB);
        const auto b_diff = Mul(b, kDiffB);
        const auto y_base = Add(r_base, Add(g_base, b_base));
        const auto y_vec = Sub(y_base, k128);
        const auto cb_vec = Mul(Sub(b_diff, y_base), kNormB);
        const auto cr_vec = Mul(Sub(r_diff, y_base), kNormR);
        Store(y_vec, df, y_row + x);
        Store(cb_vec, df, cb_row + x);
        Store(cr_vec, df, cr_row + x);
      }
    }
    return true;
  };
  JXL_RETURN_IF_ERROR(RunOnPool(pool, 0, static_cast<int>(num_stripes),
                                ThreadPool::NoInit, transform, "RgbToYcbCr"));
  return true;
}

// NOLINTNEXTLINE(google-readability-namespace-comments)
}  // namespace HWY_NAMESPACE
}  // namespace jxl
HWY_AFTER_NAMESPACE();

#if HWY_ONCE
namespace jxl {
HWY_EXPORT(ToXYB);
Status ToXYB(const ColorEncoding& c_current, float intensity_target,
             const ImageF* black, ThreadPool* pool, Image3F* JXL_RESTRICT image,
             const JxlCmsInterface& cms, Image3F* const JXL_RESTRICT linear) {
  return HWY_DYNAMIC_DISPATCH(ToXYB)(c_current, intensity_target, black, pool,
                                     image, cms, linear);
}

Status ToXYB(const ImageBundle& in, ThreadPool* pool, Image3F* JXL_RESTRICT xyb,
             const JxlCmsInterface& cms, Image3F* JXL_RESTRICT linear) {
  JxlMemoryManager* memory_manager = in.memory_manager();
  JXL_ASSIGN_OR_RETURN(*xyb,
                       Image3F::Create(memory_manager, in.xsize(), in.ysize()));
  JXL_RETURN_IF_ERROR(CopyImageTo(in.color(), xyb));
  JXL_RETURN_IF_ERROR(ToXYB(in.c_current(), in.metadata()->IntensityTarget(),
                            in.black(), pool, xyb, cms, linear));
  return true;
}

HWY_EXPORT(LinearRGBRowToXYB);
void LinearRGBRowToXYB(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,
                       float* JXL_RESTRICT row2,
                       const float* JXL_RESTRICT premul_absorb, size_t xsize) {
  HWY_DYNAMIC_DISPATCH(LinearRGBRowToXYB)
  (row0, row1, row2, premul_absorb, xsize);
}

HWY_EXPORT(ComputePremulAbsorb);
void ComputePremulAbsorb(float intensity_target, float* premul_absorb) {
  HWY_DYNAMIC_DISPATCH(ComputePremulAbsorb)(intensity_target, premul_absorb);
}

void ScaleXYBRow(float* JXL_RESTRICT row0, float* JXL_RESTRICT row1,
                 float* JXL_RESTRICT row2, size_t xsize) {
  for (size_t x = 0; x < xsize; x++) {
    row2[x] = (row2[x] - row1[x] + jxl::cms::kScaledXYBOffset[2]) *
              jxl::cms::kScaledXYBScale[2];
    row0[x] = (row0[x] + jxl::cms::kScaledXYBOffset[0]) *
              jxl::cms::kScaledXYBScale[0];
    row1[x] = (row1[x] + jxl::cms::kScaledXYBOffset[1]) *
              jxl::cms::kScaledXYBScale[1];
  }
}

void ScaleXYB(Image3F* opsin) {
  for (size_t y = 0; y < opsin->ysize(); y++) {
    float* row0 = opsin->PlaneRow(0, y);
    float* row1 = opsin->PlaneRow(1, y);
    float* row2 = opsin->PlaneRow(2, y);
    ScaleXYBRow(row0, row1, row2, opsin->xsize());
  }
}

HWY_EXPORT(RgbToYcbcr);
Status RgbToYcbcr(const ImageF& r_plane, const ImageF& g_plane,
                  const ImageF& b_plane, ImageF* y_plane, ImageF* cb_plane,
                  ImageF* cr_plane, ThreadPool* pool) {
  return HWY_DYNAMIC_DISPATCH(RgbToYcbcr)(r_plane, g_plane, b_plane, y_plane,
                                          cb_plane, cr_plane, pool);
}

}  // namespace jxl
#endif  // HWY_ONCE
