blender-archive/intern/cycles/kernel/device/gpu/image.h

/*
 * Copyright 2017 Blender Foundation
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#pragma once

CCL_NAMESPACE_BEGIN

#ifdef WITH_NANOVDB
#  define NDEBUG /* Disable "assert" in device code */
#  define NANOVDB_USE_INTRINSICS
#  include "nanovdb/NanoVDB.h"
#  include "nanovdb/util/SampleFromVoxels.h"
#endif

/* w0, w1, w2, and w3 are the four cubic B-spline basis functions. */
ccl_device float cubic_w0(float a)
{
  return (1.0f / 6.0f) * (a * (a * (-a + 3.0f) - 3.0f) + 1.0f);
}
ccl_device float cubic_w1(float a)
{
  return (1.0f / 6.0f) * (a * a * (3.0f * a - 6.0f) + 4.0f);
}
ccl_device float cubic_w2(float a)
{
  return (1.0f / 6.0f) * (a * (a * (-3.0f * a + 3.0f) + 3.0f) + 1.0f);
}
ccl_device float cubic_w3(float a)
{
  return (1.0f / 6.0f) * (a * a * a);
}

/* g0 and g1 are the two amplitude functions. */
ccl_device float cubic_g0(float a)
{
  return cubic_w0(a) + cubic_w1(a);
}
ccl_device float cubic_g1(float a)
{
  return cubic_w2(a) + cubic_w3(a);
}

/* h0 and h1 are the two offset functions */
ccl_device float cubic_h0(float a)
{
  return (cubic_w1(a) / cubic_g0(a)) - 1.0f;
}
ccl_device float cubic_h1(float a)
{
  return (cubic_w3(a) / cubic_g1(a)) + 1.0f;
}

/* Fast bicubic texture lookup using 4 bilinear lookups, adapted from CUDA samples. */
template<typename T>
ccl_device_noinline T kernel_tex_image_interp_bicubic(ccl_global const TextureInfo &info,
                                                      float x,
                                                      float y)
{
  ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;

  x = (x * info.width) - 0.5f;
  y = (y * info.height) - 0.5f;

  float px = floorf(x);
  float py = floorf(y);
  float fx = x - px;
  float fy = y - py;

  float g0x = cubic_g0(fx);
  float g1x = cubic_g1(fx);
  /* Note +0.5 offset to compensate for CUDA linear filtering convention. */
  float x0 = (px + cubic_h0(fx) + 0.5f) / info.width;
  float x1 = (px + cubic_h1(fx) + 0.5f) / info.width;
  float y0 = (py + cubic_h0(fy) + 0.5f) / info.height;
  float y1 = (py + cubic_h1(fy) + 0.5f) / info.height;

  return cubic_g0(fy) * (g0x * ccl_gpu_tex_object_read_2D<T>(tex, x0, y0) +
                         g1x * ccl_gpu_tex_object_read_2D<T>(tex, x1, y0)) +
         cubic_g1(fy) * (g0x * ccl_gpu_tex_object_read_2D<T>(tex, x0, y1) +
                         g1x * ccl_gpu_tex_object_read_2D<T>(tex, x1, y1));
}

/* Fast tricubic texture lookup using 8 trilinear lookups. */
template<typename T>
ccl_device_noinline T
kernel_tex_image_interp_tricubic(ccl_global const TextureInfo &info, float x, float y, float z)
{
  ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;

  x = (x * info.width) - 0.5f;
  y = (y * info.height) - 0.5f;
  z = (z * info.depth) - 0.5f;

  float px = floorf(x);
  float py = floorf(y);
  float pz = floorf(z);
  float fx = x - px;
  float fy = y - py;
  float fz = z - pz;

  float g0x = cubic_g0(fx);
  float g1x = cubic_g1(fx);
  float g0y = cubic_g0(fy);
  float g1y = cubic_g1(fy);
  float g0z = cubic_g0(fz);
  float g1z = cubic_g1(fz);

  /* Note +0.5 offset to compensate for CUDA linear filtering convention. */
  float x0 = (px + cubic_h0(fx) + 0.5f) / info.width;
  float x1 = (px + cubic_h1(fx) + 0.5f) / info.width;
  float y0 = (py + cubic_h0(fy) + 0.5f) / info.height;
  float y1 = (py + cubic_h1(fy) + 0.5f) / info.height;
  float z0 = (pz + cubic_h0(fz) + 0.5f) / info.depth;
  float z1 = (pz + cubic_h1(fz) + 0.5f) / info.depth;

  return g0z * (g0y * (g0x * ccl_gpu_tex_object_read_3D<T>(tex, x0, y0, z0) +
                       g1x * ccl_gpu_tex_object_read_3D<T>(tex, x1, y0, z0)) +
                g1y * (g0x * ccl_gpu_tex_object_read_3D<T>(tex, x0, y1, z0) +
                       g1x * ccl_gpu_tex_object_read_3D<T>(tex, x1, y1, z0))) +
         g1z * (g0y * (g0x * ccl_gpu_tex_object_read_3D<T>(tex, x0, y0, z1) +
                       g1x * ccl_gpu_tex_object_read_3D<T>(tex, x1, y0, z1)) +
                g1y * (g0x * ccl_gpu_tex_object_read_3D<T>(tex, x0, y1, z1) +
                       g1x * ccl_gpu_tex_object_read_3D<T>(tex, x1, y1, z1)));
}

#ifdef WITH_NANOVDB
template<typename T, typename S>
ccl_device T kernel_tex_image_interp_tricubic_nanovdb(S &s, float x, float y, float z)
{
  float px = floorf(x);
  float py = floorf(y);
  float pz = floorf(z);
  float fx = x - px;
  float fy = y - py;
  float fz = z - pz;

  float g0x = cubic_g0(fx);
  float g1x = cubic_g1(fx);
  float g0y = cubic_g0(fy);
  float g1y = cubic_g1(fy);
  float g0z = cubic_g0(fz);
  float g1z = cubic_g1(fz);

  float x0 = px + cubic_h0(fx);
  float x1 = px + cubic_h1(fx);
  float y0 = py + cubic_h0(fy);
  float y1 = py + cubic_h1(fy);
  float z0 = pz + cubic_h0(fz);
  float z1 = pz + cubic_h1(fz);

  using namespace nanovdb;

  return g0z * (g0y * (g0x * s(Vec3f(x0, y0, z0)) + g1x * s(Vec3f(x1, y0, z0))) +
                g1y * (g0x * s(Vec3f(x0, y1, z0)) + g1x * s(Vec3f(x1, y1, z0)))) +
         g1z * (g0y * (g0x * s(Vec3f(x0, y0, z1)) + g1x * s(Vec3f(x1, y0, z1))) +
                g1y * (g0x * s(Vec3f(x0, y1, z1)) + g1x * s(Vec3f(x1, y1, z1))));
}

template<typename T>
ccl_device_noinline T kernel_tex_image_interp_nanovdb(
    ccl_global const TextureInfo &info, float x, float y, float z, uint interpolation)
{
  using namespace nanovdb;

  NanoGrid<T> *const grid = (NanoGrid<T> *)info.data;
  typedef typename nanovdb::NanoGrid<T>::AccessorType AccessorType;
  AccessorType acc = grid->getAccessor();

  switch (interpolation) {
    case INTERPOLATION_CLOSEST:
      return SampleFromVoxels<AccessorType, 0, false>(acc)(Vec3f(x, y, z));
    case INTERPOLATION_LINEAR:
      return SampleFromVoxels<AccessorType, 1, false>(acc)(Vec3f(x - 0.5f, y - 0.5f, z - 0.5f));
    default:
      SampleFromVoxels<AccessorType, 1, false> s(acc);
      return kernel_tex_image_interp_tricubic_nanovdb<T>(s, x - 0.5f, y - 0.5f, z - 0.5f);
  }
}
#endif

ccl_device float4 kernel_tex_image_interp(KernelGlobals kg, int id, float x, float y)
{
  ccl_global const TextureInfo &info = kernel_tex_fetch(__texture_info, id);

  /* float4, byte4, ushort4 and half4 */
  const int texture_type = info.data_type;
  if (texture_type == IMAGE_DATA_TYPE_FLOAT4 || texture_type == IMAGE_DATA_TYPE_BYTE4 ||
      texture_type == IMAGE_DATA_TYPE_HALF4 || texture_type == IMAGE_DATA_TYPE_USHORT4) {
    if (info.interpolation == INTERPOLATION_CUBIC) {
      return kernel_tex_image_interp_bicubic<float4>(info, x, y);
    }
    else {
      ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;
      return ccl_gpu_tex_object_read_2D<float4>(tex, x, y);
    }
  }
  /* float, byte and half */
  else {
    float f;

    if (info.interpolation == INTERPOLATION_CUBIC) {
      f = kernel_tex_image_interp_bicubic<float>(info, x, y);
    }
    else {
      ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;
      f = ccl_gpu_tex_object_read_2D<float>(tex, x, y);
    }

    return make_float4(f, f, f, 1.0f);
  }
}

ccl_device float4 kernel_tex_image_interp_3d(KernelGlobals kg,
                                             int id,
                                             float3 P,
                                             InterpolationType interp)
{
  ccl_global const TextureInfo &info = kernel_tex_fetch(__texture_info, id);

  if (info.use_transform_3d) {
    P = transform_point(&info.transform_3d, P);
  }

  const float x = P.x;
  const float y = P.y;
  const float z = P.z;

  uint interpolation = (interp == INTERPOLATION_NONE) ? info.interpolation : interp;
  const int texture_type = info.data_type;

#ifdef WITH_NANOVDB
  if (texture_type == IMAGE_DATA_TYPE_NANOVDB_FLOAT) {
    float f = kernel_tex_image_interp_nanovdb<float>(info, x, y, z, interpolation);
    return make_float4(f, f, f, 1.0f);
  }
  if (texture_type == IMAGE_DATA_TYPE_NANOVDB_FLOAT3) {
    nanovdb::Vec3f f = kernel_tex_image_interp_nanovdb<nanovdb::Vec3f>(
        info, x, y, z, interpolation);
    return make_float4(f[0], f[1], f[2], 1.0f);
  }
#endif
  if (texture_type == IMAGE_DATA_TYPE_FLOAT4 || texture_type == IMAGE_DATA_TYPE_BYTE4 ||
      texture_type == IMAGE_DATA_TYPE_HALF4 || texture_type == IMAGE_DATA_TYPE_USHORT4) {
    if (interpolation == INTERPOLATION_CUBIC) {
      return kernel_tex_image_interp_tricubic<float4>(info, x, y, z);
    }
    else {
      ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;
      return ccl_gpu_tex_object_read_3D<float4>(tex, x, y, z);
    }
  }
  else {
    float f;

    if (interpolation == INTERPOLATION_CUBIC) {
      f = kernel_tex_image_interp_tricubic<float>(info, x, y, z);
    }
    else {
      ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data;
      f = ccl_gpu_tex_object_read_3D<float>(tex, x, y, z);
    }

    return make_float4(f, f, f, 1.0f);
  }
}

CCL_NAMESPACE_END