/* * 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 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(tex, x0, y0) + g1x * ccl_gpu_tex_object_read_2D(tex, x1, y0)) + cubic_g1(fy) * (g0x * ccl_gpu_tex_object_read_2D(tex, x0, y1) + g1x * ccl_gpu_tex_object_read_2D(tex, x1, y1)); } /* Fast tricubic texture lookup using 8 trilinear lookups. */ template 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(tex, x0, y0, z0) + g1x * ccl_gpu_tex_object_read_3D(tex, x1, y0, z0)) + g1y * (g0x * ccl_gpu_tex_object_read_3D(tex, x0, y1, z0) + g1x * ccl_gpu_tex_object_read_3D(tex, x1, y1, z0))) + g1z * (g0y * (g0x * ccl_gpu_tex_object_read_3D(tex, x0, y0, z1) + g1x * ccl_gpu_tex_object_read_3D(tex, x1, y0, z1)) + g1y * (g0x * ccl_gpu_tex_object_read_3D(tex, x0, y1, z1) + g1x * ccl_gpu_tex_object_read_3D(tex, x1, y1, z1))); } #ifdef WITH_NANOVDB template 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 ccl_device_noinline T kernel_tex_image_interp_nanovdb( const TextureInfo &info, float x, float y, float z, uint interpolation) { using namespace nanovdb; NanoGrid *const grid = (NanoGrid *)info.data; typedef typename nanovdb::NanoGrid::AccessorType AccessorType; AccessorType acc = grid->getAccessor(); switch (interpolation) { case INTERPOLATION_CLOSEST: return SampleFromVoxels(acc)(Vec3f(x, y, z)); case INTERPOLATION_LINEAR: return SampleFromVoxels(acc)(Vec3f(x - 0.5f, y - 0.5f, z - 0.5f)); default: SampleFromVoxels s(acc); return kernel_tex_image_interp_tricubic_nanovdb(s, x - 0.5f, y - 0.5f, z - 0.5f); } } #endif ccl_device float4 kernel_tex_image_interp(const 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(info, x, y); } else { ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data; return ccl_gpu_tex_object_read_2D(tex, x, y); } } /* float, byte and half */ else { float f; if (info.interpolation == INTERPOLATION_CUBIC) { f = kernel_tex_image_interp_bicubic(info, x, y); } else { ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data; f = ccl_gpu_tex_object_read_2D(tex, x, y); } return make_float4(f, f, f, 1.0f); } } ccl_device float4 kernel_tex_image_interp_3d(const 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(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( 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(info, x, y, z); } else { ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data; return ccl_gpu_tex_object_read_3D(tex, x, y, z); } } else { float f; if (interpolation == INTERPOLATION_CUBIC) { f = kernel_tex_image_interp_tricubic(info, x, y, z); } else { ccl_gpu_tex_object tex = (ccl_gpu_tex_object)info.data; f = ccl_gpu_tex_object_read_3D(tex, x, y, z); } return make_float4(f, f, f, 1.0f); } } CCL_NAMESPACE_END