This feature takes some inspiration from "RenderMan: An Advanced Path Tracing Architecture for Movie Rendering" and "A Hierarchical Automatic Stopping Condition for Monte Carlo Global Illumination" The basic principle is as follows: While samples are being added to a pixel, the adaptive sampler writes half of the samples to a separate buffer. This gives it two separate estimates of the same pixel, and by comparing their difference it estimates convergence. Once convergence drops below a given threshold, the pixel is considered done. When a pixel has not converged yet and needs more samples than the minimum, its immediate neighbors are also set to take more samples. This is done in order to more reliably detect sharp features such as caustics. A 3x3 box filter that is run periodically over the tile buffer is used for that purpose. After a tile has finished rendering, the values of all passes are scaled as if they were rendered with the full number of samples. This way, any code operating on these buffers, for example the denoiser, does not need to be changed for per-pixel sample counts. Reviewed By: brecht, #cycles Differential Revision: https://developer.blender.org/D4686
195 lines
4.1 KiB
C++
195 lines
4.1 KiB
C++
/*
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* Copyright 2011-2013 Blender Foundation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include <stdlib.h>
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#include <string.h>
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#include "device/device_task.h"
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#include "render/buffers.h"
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#include "util/util_algorithm.h"
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#include "util/util_time.h"
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CCL_NAMESPACE_BEGIN
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/* Device Task */
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DeviceTask::DeviceTask(Type type_)
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: type(type_),
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x(0),
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y(0),
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w(0),
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h(0),
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rgba_byte(0),
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rgba_half(0),
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buffer(0),
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sample(0),
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num_samples(1),
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shader_input(0),
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shader_output(0),
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shader_eval_type(0),
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shader_filter(0),
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shader_x(0),
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shader_w(0)
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{
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last_update_time = time_dt();
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}
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int DeviceTask::get_subtask_count(int num, int max_size)
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{
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if (max_size != 0) {
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int max_size_num;
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if (type == SHADER) {
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max_size_num = (shader_w + max_size - 1) / max_size;
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}
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else {
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max_size = max(1, max_size / w);
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max_size_num = (h + max_size - 1) / max_size;
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}
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num = max(max_size_num, num);
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}
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if (type == SHADER) {
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num = min(shader_w, num);
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}
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else if (type == RENDER) {
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}
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else {
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num = min(h, num);
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}
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return num;
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}
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void DeviceTask::split(list<DeviceTask> &tasks, int num, int max_size)
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{
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num = get_subtask_count(num, max_size);
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if (type == SHADER) {
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for (int i = 0; i < num; i++) {
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int tx = shader_x + (shader_w / num) * i;
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int tw = (i == num - 1) ? shader_w - i * (shader_w / num) : shader_w / num;
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DeviceTask task = *this;
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task.shader_x = tx;
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task.shader_w = tw;
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tasks.push_back(task);
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}
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}
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else if (type == RENDER) {
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for (int i = 0; i < num; i++)
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tasks.push_back(*this);
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}
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else {
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for (int i = 0; i < num; i++) {
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int ty = y + (h / num) * i;
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int th = (i == num - 1) ? h - i * (h / num) : h / num;
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DeviceTask task = *this;
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task.y = ty;
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task.h = th;
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tasks.push_back(task);
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}
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}
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}
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void DeviceTask::update_progress(RenderTile *rtile, int pixel_samples)
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{
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if (type == FILM_CONVERT)
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return;
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if (update_progress_sample) {
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if (pixel_samples == -1) {
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pixel_samples = shader_w;
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}
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update_progress_sample(pixel_samples, rtile ? rtile->sample : 0);
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}
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if (update_tile_sample) {
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double current_time = time_dt();
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if (current_time - last_update_time >= 1.0) {
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update_tile_sample(*rtile);
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last_update_time = current_time;
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}
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}
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}
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/* Adaptive Sampling */
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AdaptiveSampling::AdaptiveSampling()
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: use(true), adaptive_step(ADAPTIVE_SAMPLE_STEP), min_samples(0)
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{
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}
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/* Render samples in steps that align with the adaptive filtering. */
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int AdaptiveSampling::align_static_samples(int samples) const
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{
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if (samples > adaptive_step) {
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/* Make multiple of adaptive_step. */
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while (samples % adaptive_step != 0) {
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samples--;
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}
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}
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else if (samples < adaptive_step) {
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/* Make divisor of adaptive_step. */
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while (adaptive_step % samples != 0) {
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samples--;
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}
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}
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return max(samples, 1);
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}
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/* Render samples in steps that align with the adaptive filtering, with the
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* suggested number of samples dynamically changing. */
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int AdaptiveSampling::align_dynamic_samples(int offset, int samples) const
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{
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/* Round so that we end up on multiples of adaptive_samples. */
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samples += offset;
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if (samples > adaptive_step) {
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/* Make multiple of adaptive_step. */
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while (samples % adaptive_step != 0) {
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samples--;
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}
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}
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samples -= offset;
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return max(samples, 1);
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}
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bool AdaptiveSampling::need_filter(int sample) const
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{
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if (sample > min_samples) {
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return (sample & (adaptive_step - 1)) == (adaptive_step - 1);
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}
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else {
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return false;
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}
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}
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CCL_NAMESPACE_END
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