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blender-archive/intern/cycles/kernel/device/gpu/image.h
Brecht Van Lommel 1df3b51988 Cycles: replace integrator state argument macros
* Rename struct KernelGlobals to struct KernelGlobalsCPU
* Add KernelGlobals, IntegratorState and ConstIntegratorState typedefs
  that every device can define in its own way.
* Remove INTEGRATOR_STATE_ARGS and INTEGRATOR_STATE_PASS macros and
  replace with these new typedefs.
* Add explicit state argument to INTEGRATOR_STATE and similar macros

In preparation for decoupling main and shadow paths.

Differential Revision: https://developer.blender.org/D12888
2021-10-18 19:02:10 +02:00

279 lines
8.9 KiB
C++

/*
* 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(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(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(
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)
{
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)
{
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