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Cycles Denoising: Split main function into logical steps

This commit is contained in:
Lukas Stockner 2018-07-04 14:22:38 +02:00
parent 969111f9b5
commit b10c64bd2f
7 changed files with 153 additions and 130 deletions
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4
intern/cycles/device/device_cpu.cpp
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@ -732,8 +732,6 @@ public:
task.map_neighbor_tiles(rtiles, this);
denoising.tiles_from_rendertiles(rtiles);
denoising.init_from_devicetask(task);
denoising.run_denoising();
task.unmap_neighbor_tiles(rtiles, this);
@ -766,7 +764,7 @@ public:
}
RenderTile tile;
DenoisingTask denoising(this);
DenoisingTask denoising(this, task);
while(task.acquire_tile(this, tile)) {
if(tile.task == RenderTile::PATH_TRACE) {

4
intern/cycles/device/device_cuda.cpp
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@ -1632,8 +1632,6 @@ public:
task.map_neighbor_tiles(rtiles, this);
denoising.tiles_from_rendertiles(rtiles);
denoising.init_from_devicetask(task);
denoising.run_denoising();
task.unmap_neighbor_tiles(rtiles, this);
@ -2074,7 +2072,7 @@ public:
/* keep rendering tiles until done */
RenderTile tile;
DenoisingTask denoising(this);
DenoisingTask denoising(this, *task);
while(task->acquire_tile(this, tile)) {
if(tile.task == RenderTile::PATH_TRACE) {

255
intern/cycles/device/device_denoising.cpp
View File

@ -20,12 +20,24 @@
CCL_NAMESPACE_BEGIN
DenoisingTask::DenoisingTask(Device *device)
DenoisingTask::DenoisingTask(Device *device, const DeviceTask &task)
: tiles_mem(device, "denoising tiles_mem", MEM_READ_WRITE),
storage(device),
buffer(device),
device(device)
{
radius = task.denoising_radius;
nlm_k_2 = powf(2.0f, lerp(-5.0f, 3.0f, task.denoising_strength));
if(task.denoising_relative_pca) {
pca_threshold = -powf(10.0f, lerp(-8.0f, 0.0f, task.denoising_feature_strength));
}
else {
pca_threshold = powf(10.0f, lerp(-5.0f, 3.0f, task.denoising_feature_strength));
}
render_buffer.pass_stride = task.pass_stride;
render_buffer.denoising_data_offset = task.pass_denoising_data;
render_buffer.denoising_clean_offset = task.pass_denoising_clean;
}
DenoisingTask::~DenoisingTask()
@ -41,26 +53,6 @@ DenoisingTask::~DenoisingTask()
tiles_mem.free();
}
void DenoisingTask::init_from_devicetask(const DeviceTask &task)
{
radius = task.denoising_radius;
nlm_k_2 = powf(2.0f, lerp(-5.0f, 3.0f, task.denoising_strength));
if(task.denoising_relative_pca) {
pca_threshold = -powf(10.0f, lerp(-8.0f, 0.0f, task.denoising_feature_strength));
}
else {
pca_threshold = powf(10.0f, lerp(-5.0f, 3.0f, task.denoising_feature_strength));
}
render_buffer.pass_stride = task.pass_stride;
render_buffer.denoising_data_offset = task.pass_denoising_data;
render_buffer.denoising_clean_offset = task.pass_denoising_clean;
/* Expand filter_area by radius pixels and clamp the result to the extent of the neighboring tiles */
rect = rect_from_shape(filter_area.x, filter_area.y, filter_area.z, filter_area.w);
rect = rect_expand(rect, radius);
rect = rect_clip(rect, make_int4(tiles->x[0], tiles->y[0], tiles->x[3], tiles->y[3]));
}
void DenoisingTask::tiles_from_rendertiles(RenderTile *rtiles)
{
@ -88,120 +80,142 @@ void DenoisingTask::tiles_from_rendertiles(RenderTile *rtiles)
functions.set_tiles(buffers);
}
bool DenoisingTask::run_denoising()
void DenoisingTask::setup_denoising_buffer()
{
/* Allocate denoising buffer. */
/* Expand filter_area by radius pixels and clamp the result to the extent of the neighboring tiles */
rect = rect_from_shape(filter_area.x, filter_area.y, filter_area.z, filter_area.w);
rect = rect_expand(rect, radius);
rect = rect_clip(rect, make_int4(tiles->x[0], tiles->y[0], tiles->x[3], tiles->y[3]));
buffer.passes = 14;
buffer.width = rect.z - rect.x;
buffer.stride = align_up(buffer.width, 4);
buffer.h = rect.w - rect.y;
buffer.pass_stride = align_up(buffer.stride * buffer.h, divide_up(device->mem_sub_ptr_alignment(), sizeof(float)));
buffer.mem.alloc_to_device(buffer.pass_stride * buffer.passes, false);
int alignment_floats = divide_up(device->mem_sub_ptr_alignment(), sizeof(float));
buffer.pass_stride = align_up(buffer.stride * buffer.h, alignment_floats);
/* Pad the total size by four floats since the SIMD kernels might go a bit over the end. */
int mem_size = align_up(buffer.pass_stride * buffer.passes + 4, alignment_floats);
buffer.mem.alloc_to_device(mem_size, false);
}
void DenoisingTask::prefilter_shadowing()
{
device_ptr null_ptr = (device_ptr) 0;
/* Prefilter shadow feature. */
{
device_sub_ptr unfiltered_a (buffer.mem, 0, buffer.pass_stride);
device_sub_ptr unfiltered_b (buffer.mem, 1*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr sample_var (buffer.mem, 2*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr sample_var_var (buffer.mem, 3*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr buffer_var (buffer.mem, 5*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr filtered_var (buffer.mem, 6*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_1(buffer.mem, 7*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_2(buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_3(buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr unfiltered_a (buffer.mem, 0, buffer.pass_stride);
device_sub_ptr unfiltered_b (buffer.mem, 1*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr sample_var (buffer.mem, 2*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr sample_var_var (buffer.mem, 3*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr buffer_var (buffer.mem, 5*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr filtered_var (buffer.mem, 6*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_1(buffer.mem, 7*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_2(buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_3(buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
nlm_state.temporary_1_ptr = *nlm_temporary_1;
nlm_state.temporary_2_ptr = *nlm_temporary_2;
nlm_state.temporary_3_ptr = *nlm_temporary_3;
nlm_state.temporary_1_ptr = *nlm_temporary_1;
nlm_state.temporary_2_ptr = *nlm_temporary_2;
nlm_state.temporary_3_ptr = *nlm_temporary_3;
/* Get the A/B unfiltered passes, the combined sample variance, the estimated variance of the sample variance and the buffer variance. */
functions.divide_shadow(*unfiltered_a, *unfiltered_b, *sample_var, *sample_var_var, *buffer_var);
/* Get the A/B unfiltered passes, the combined sample variance, the estimated variance of the sample variance and the buffer variance. */
functions.divide_shadow(*unfiltered_a, *unfiltered_b, *sample_var, *sample_var_var, *buffer_var);
/* Smooth the (generally pretty noisy) buffer variance using the spatial information from the sample variance. */
nlm_state.set_parameters(6, 3, 4.0f, 1.0f);
functions.non_local_means(*buffer_var, *sample_var, *sample_var_var, *filtered_var);
/* Smooth the (generally pretty noisy) buffer variance using the spatial information from the sample variance. */
nlm_state.set_parameters(6, 3, 4.0f, 1.0f);
functions.non_local_means(*buffer_var, *sample_var, *sample_var_var, *filtered_var);
/* Reuse memory, the previous data isn't needed anymore. */
device_ptr filtered_a = *buffer_var,
filtered_b = *sample_var;
/* Use the smoothed variance to filter the two shadow half images using each other for weight calculation. */
nlm_state.set_parameters(5, 3, 1.0f, 0.25f);
functions.non_local_means(*unfiltered_a, *unfiltered_b, *filtered_var, filtered_a);
functions.non_local_means(*unfiltered_b, *unfiltered_a, *filtered_var, filtered_b);
/* Reuse memory, the previous data isn't needed anymore. */
device_ptr filtered_a = *buffer_var,
filtered_b = *sample_var;
/* Use the smoothed variance to filter the two shadow half images using each other for weight calculation. */
nlm_state.set_parameters(5, 3, 1.0f, 0.25f);
functions.non_local_means(*unfiltered_a, *unfiltered_b, *filtered_var, filtered_a);
functions.non_local_means(*unfiltered_b, *unfiltered_a, *filtered_var, filtered_b);
device_ptr residual_var = *sample_var_var;
/* Estimate the residual variance between the two filtered halves. */
functions.combine_halves(filtered_a, filtered_b, null_ptr, residual_var, 2, rect);
device_ptr residual_var = *sample_var_var;
/* Estimate the residual variance between the two filtered halves. */
functions.combine_halves(filtered_a, filtered_b, null_ptr, residual_var, 2, rect);
device_ptr final_a = *unfiltered_a,
final_b = *unfiltered_b;
/* Use the residual variance for a second filter pass. */
nlm_state.set_parameters(4, 2, 1.0f, 0.5f);
functions.non_local_means(filtered_a, filtered_b, residual_var, final_a);
functions.non_local_means(filtered_b, filtered_a, residual_var, final_b);
device_ptr final_a = *unfiltered_a,
final_b = *unfiltered_b;
/* Use the residual variance for a second filter pass. */
nlm_state.set_parameters(4, 2, 1.0f, 0.5f);
functions.non_local_means(filtered_a, filtered_b, residual_var, final_a);
functions.non_local_means(filtered_b, filtered_a, residual_var, final_b);
/* Combine the two double-filtered halves to a final shadow feature. */
device_sub_ptr shadow_pass(buffer.mem, 4*buffer.pass_stride, buffer.pass_stride);
functions.combine_halves(final_a, final_b, *shadow_pass, null_ptr, 0, rect);
/* Combine the two double-filtered halves to a final shadow feature. */
device_sub_ptr shadow_pass(buffer.mem, 4*buffer.pass_stride, buffer.pass_stride);
functions.combine_halves(final_a, final_b, *shadow_pass, null_ptr, 0, rect);
}
void DenoisingTask::prefilter_features()
{
device_sub_ptr unfiltered (buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr variance (buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_1(buffer.mem, 10*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_2(buffer.mem, 11*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_3(buffer.mem, 12*buffer.pass_stride, buffer.pass_stride);
nlm_state.temporary_1_ptr = *nlm_temporary_1;
nlm_state.temporary_2_ptr = *nlm_temporary_2;
nlm_state.temporary_3_ptr = *nlm_temporary_3;
int mean_from[] = { 0, 1, 2, 12, 6, 7, 8 };
int variance_from[] = { 3, 4, 5, 13, 9, 10, 11};
int pass_to[] = { 1, 2, 3, 0, 5, 6, 7};
for(int pass = 0; pass < 7; pass++) {
device_sub_ptr feature_pass(buffer.mem, pass_to[pass]*buffer.pass_stride, buffer.pass_stride);
/* Get the unfiltered pass and its variance from the RenderBuffers. */
functions.get_feature(mean_from[pass], variance_from[pass], *unfiltered, *variance);
/* Smooth the pass and store the result in the denoising buffers. */
nlm_state.set_parameters(2, 2, 1.0f, 0.25f);
functions.non_local_means(*unfiltered, *unfiltered, *variance, *feature_pass);
}
}
void DenoisingTask::prefilter_color()
{
int mean_from[] = {20, 21, 22};
int variance_from[] = {23, 24, 25};
int mean_to[] = { 8, 9, 10};
int variance_to[] = {11, 12, 13};
int num_color_passes = 3;
storage.temporary_color.alloc_to_device(3*buffer.pass_stride, false);
device_sub_ptr nlm_temporary_1(storage.temporary_color, 0*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_2(storage.temporary_color, 1*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_3(storage.temporary_color, 2*buffer.pass_stride, buffer.pass_stride);
nlm_state.temporary_1_ptr = *nlm_temporary_1;
nlm_state.temporary_2_ptr = *nlm_temporary_2;
nlm_state.temporary_3_ptr = *nlm_temporary_3;
for(int pass = 0; pass < num_color_passes; pass++) {
device_sub_ptr color_pass(storage.temporary_color, pass*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr color_var_pass(buffer.mem, variance_to[pass]*buffer.pass_stride, buffer.pass_stride);
functions.get_feature(mean_from[pass], variance_from[pass], *color_pass, *color_var_pass);
}
/* Prefilter general features. */
{
device_sub_ptr unfiltered (buffer.mem, 8*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr variance (buffer.mem, 9*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_1(buffer.mem, 10*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_2(buffer.mem, 11*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr nlm_temporary_3(buffer.mem, 12*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr depth_pass (buffer.mem, 0, buffer.pass_stride);
device_sub_ptr color_var_pass(buffer.mem, variance_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
device_sub_ptr output_pass (buffer.mem, mean_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
functions.detect_outliers(storage.temporary_color.device_pointer, *color_var_pass, *depth_pass, *output_pass);
nlm_state.temporary_1_ptr = *nlm_temporary_1;
nlm_state.temporary_2_ptr = *nlm_temporary_2;
nlm_state.temporary_3_ptr = *nlm_temporary_3;
int mean_from[] = { 0, 1, 2, 12, 6, 7, 8 };
int variance_from[] = { 3, 4, 5, 13, 9, 10, 11};
int pass_to[] = { 1, 2, 3, 0, 5, 6, 7};
for(int pass = 0; pass < 7; pass++) {
device_sub_ptr feature_pass(buffer.mem, pass_to[pass]*buffer.pass_stride, buffer.pass_stride);
/* Get the unfiltered pass and its variance from the RenderBuffers. */
functions.get_feature(mean_from[pass], variance_from[pass], *unfiltered, *variance);
/* Smooth the pass and store the result in the denoising buffers. */
nlm_state.set_parameters(2, 2, 1.0f, 0.25f);
functions.non_local_means(*unfiltered, *unfiltered, *variance, *feature_pass);
}
}
/* Copy color passes. */
{
int mean_from[] = {20, 21, 22};
int variance_from[] = {23, 24, 25};
int mean_to[] = { 8, 9, 10};
int variance_to[] = {11, 12, 13};
int num_color_passes = 3;
storage.temporary_color.alloc_to_device(3*buffer.pass_stride, false);
for(int pass = 0; pass < num_color_passes; pass++) {
device_sub_ptr color_pass(storage.temporary_color, pass*buffer.pass_stride, buffer.pass_stride);
device_sub_ptr color_var_pass(buffer.mem, variance_to[pass]*buffer.pass_stride, buffer.pass_stride);
functions.get_feature(mean_from[pass], variance_from[pass], *color_pass, *color_var_pass);
}
{
device_sub_ptr depth_pass (buffer.mem, 0, buffer.pass_stride);
device_sub_ptr color_var_pass(buffer.mem, variance_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
device_sub_ptr output_pass (buffer.mem, mean_to[0]*buffer.pass_stride, 3*buffer.pass_stride);
functions.detect_outliers(storage.temporary_color.device_pointer, *color_var_pass, *depth_pass, *output_pass);
}
}
storage.temporary_color.free();
}
void DenoisingTask::construct_transform()
{
storage.w = filter_area.z;
storage.h = filter_area.w;
storage.transform.alloc_to_device(storage.w*storage.h*TRANSFORM_SIZE, false);
storage.rank.alloc_to_device(storage.w*storage.h, false);
functions.construct_transform();
}
void DenoisingTask::reconstruct()
{
device_only_memory<float> temporary_1(device, "Denoising NLM temporary 1");
device_only_memory<float> temporary_2(device, "Denoising NLM temporary 2");
@ -222,13 +236,22 @@ bool DenoisingTask::run_denoising()
reconstruction_state.source_w = rect.z-rect.x;
reconstruction_state.source_h = rect.w-rect.y;
{
device_sub_ptr color_ptr (buffer.mem, 8*buffer.pass_stride, 3*buffer.pass_stride);
device_sub_ptr color_var_ptr(buffer.mem, 11*buffer.pass_stride, 3*buffer.pass_stride);
functions.reconstruct(*color_ptr, *color_var_ptr, render_buffer.ptr);
}
device_sub_ptr color_ptr (buffer.mem, 8*buffer.pass_stride, 3*buffer.pass_stride);
device_sub_ptr color_var_ptr(buffer.mem, 11*buffer.pass_stride, 3*buffer.pass_stride);
functions.reconstruct(*color_ptr, *color_var_ptr, render_buffer.ptr);
}
void DenoisingTask::run_denoising()
{
setup_denoising_buffer();
prefilter_shadowing();
prefilter_features();
prefilter_color();
construct_transform();
reconstruct();
return true;
}
CCL_NAMESPACE_END

14
intern/cycles/device/device_denoising.h
View File

@ -138,12 +138,10 @@ public:
{}
} storage;
DenoisingTask(Device *device);
DenoisingTask(Device *device, const DeviceTask &task);
~DenoisingTask();
void init_from_devicetask(const DeviceTask &task);
bool run_denoising();
void run_denoising();
struct DenoiseBuffers {
int pass_stride;
@ -160,6 +158,14 @@ public:
protected:
Device *device;
void set_render_buffer(RenderTile *rtiles);
void setup_denoising_buffer();
void prefilter_shadowing();
void prefilter_features();
void prefilter_color();
void construct_transform();
void reconstruct();
};
CCL_NAMESPACE_END

2
intern/cycles/device/opencl/opencl_base.cpp
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@ -1095,8 +1095,6 @@ void OpenCLDeviceBase::denoise(RenderTile &rtile, DenoisingTask& denoising, cons
task.map_neighbor_tiles(rtiles, this);
denoising.tiles_from_rendertiles(rtiles);
denoising.init_from_devicetask(task);
denoising.run_denoising();
task.unmap_neighbor_tiles(rtiles, this);

2
intern/cycles/device/opencl/opencl_mega.cpp
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@ -107,7 +107,7 @@ public:
}
else if(task->type == DeviceTask::RENDER) {
RenderTile tile;
DenoisingTask denoising(this);
DenoisingTask denoising(this, *task);
/* Keep rendering tiles until done. */
while(task->acquire_tile(this, tile)) {

2
intern/cycles/device/opencl/opencl_split.cpp
View File

@ -129,7 +129,7 @@ public:
}
else if(task->type == DeviceTask::RENDER) {
RenderTile tile;
DenoisingTask denoising(this);
DenoisingTask denoising(this, *task);
/* Allocate buffer for kernel globals */
device_only_memory<KernelGlobalsDummy> kgbuffer(this, "kernel_globals");