2017-05-07 12:40:58 +00:00
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/*
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* Copyright 2011-2017 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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#ifndef __DEVICE_DENOISING_H__
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#define __DEVICE_DENOISING_H__
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#include "device/device.h"
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#include "render/buffers.h"
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#include "kernel/filter/filter_defines.h"
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CCL_NAMESPACE_BEGIN
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class DenoisingTask {
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public:
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/* Parameters of the denoising algorithm. */
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int radius;
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float nlm_k_2;
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float pca_threshold;
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/* Pointer and parameters of the RenderBuffers. */
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struct RenderBuffers {
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int denoising_data_offset;
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int denoising_clean_offset;
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int pass_stride;
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int offset;
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int stride;
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device_ptr ptr;
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int samples;
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} render_buffer;
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TilesInfo *tiles;
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device_vector<int> tiles_mem;
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void tiles_from_rendertiles(RenderTile *rtiles);
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int4 rect;
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int4 filter_area;
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struct DeviceFunctions {
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function<bool(device_ptr image_ptr, /* Contains the values that are smoothed. */
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device_ptr guide_ptr, /* Contains the values that are used to calculate weights. */
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device_ptr variance_ptr, /* Contains the variance of the guide image. */
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device_ptr out_ptr /* The filtered output is written into this image. */
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)> non_local_means;
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function<bool(device_ptr color_ptr,
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device_ptr color_variance_ptr,
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device_ptr output_ptr
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)> reconstruct;
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function<bool()> construct_transform;
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function<bool(device_ptr a_ptr,
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device_ptr b_ptr,
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device_ptr mean_ptr,
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device_ptr variance_ptr,
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int r,
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int4 rect
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)> combine_halves;
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function<bool(device_ptr a_ptr,
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device_ptr b_ptr,
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device_ptr sample_variance_ptr,
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device_ptr sv_variance_ptr,
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device_ptr buffer_variance_ptr
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)> divide_shadow;
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function<bool(int mean_offset,
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int variance_offset,
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device_ptr mean_ptr,
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device_ptr variance_ptr
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)> get_feature;
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2017-05-18 01:03:18 +00:00
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function<bool(device_ptr image_ptr,
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device_ptr variance_ptr,
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device_ptr depth_ptr,
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device_ptr output_ptr
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)> detect_outliers;
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2017-05-07 12:40:58 +00:00
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function<bool(device_ptr*)> set_tiles;
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} functions;
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/* Stores state of the current Reconstruction operation,
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* which is accessed by the device in order to perform the operation. */
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struct ReconstructionState {
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device_ptr temporary_1_ptr; /* There two images are used as temporary storage. */
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device_ptr temporary_2_ptr;
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int4 filter_rect;
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int4 buffer_params;
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int source_w;
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int source_h;
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} reconstruction_state;
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/* Stores state of the current NLM operation,
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* which is accessed by the device in order to perform the operation. */
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struct NLMState {
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device_ptr temporary_1_ptr; /* There three images are used as temporary storage. */
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device_ptr temporary_2_ptr;
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device_ptr temporary_3_ptr;
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int r; /* Search radius of the filter. */
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int f; /* Patch size of the filter. */
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float a; /* Variance compensation factor in the MSE estimation. */
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float k_2; /* Squared value of the k parameter of the filter. */
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void set_parameters(int r_, int f_, float a_, float k_2_) { r = r_; f = f_; a = a_, k_2 = k_2_; }
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} nlm_state;
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struct Storage {
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device_only_memory<float> transform;
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device_only_memory<int> rank;
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device_only_memory<float> XtWX;
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device_only_memory<float3> XtWY;
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int w;
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int h;
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} storage;
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DenoisingTask(Device *device) : device(device) {}
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void init_from_devicetask(const DeviceTask &task);
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bool run_denoising();
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struct DenoiseBuffers {
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int pass_stride;
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int passes;
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int w;
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int h;
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device_only_memory<float> mem;
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} buffer;
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protected:
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Device *device;
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};
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CCL_NAMESPACE_END
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#endif /* __DEVICE_DENOISING_H__ */
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