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/*
* Copyright 2011-2017 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.
*/
CCL_NAMESPACE_BEGIN
#define ccl_get_feature_sse(pass) load_float4(buffer + (pass)*pass_stride)
/* Loop over the pixels in the range [low.x, high.x) x [low.y, high.y), 4 at a time.
* pixel_buffer always points to the first of the 4 current pixel in the first pass.
* x4 and y4 contain the coordinates of the four pixels, active_pixels contains a mask that's set for all pixels within the window. */
#define FOR_PIXEL_WINDOW_SSE pixel_buffer = buffer + (low.y - rect.y)*buffer_w + (low.x - rect.x); \
for(pixel.y = low.y; pixel.y < high.y; pixel.y++) { \
float4 y4 = make_float4(pixel.y); \
for(pixel.x = low.x; pixel.x < high.x; pixel.x += 4, pixel_buffer += 4) { \
float4 x4 = make_float4(pixel.x) + make_float4(0.0f, 1.0f, 2.0f, 3.0f); \
int4 active_pixels = x4 < make_float4(high.x);
#define END_FOR_PIXEL_WINDOW_SSE } \
pixel_buffer += buffer_w - (pixel.x - low.x); \
}
ccl_device_inline void filter_get_features_sse(float4 x, float4 y,
int4 active_pixels,
const float *ccl_restrict buffer,
float4 *features,
const float4 *ccl_restrict mean,
int pass_stride)
{
features[0] = x;
features[1] = y;
features[2] = fabs(ccl_get_feature_sse(0));
features[3] = ccl_get_feature_sse(1);
features[4] = ccl_get_feature_sse(2);
features[5] = ccl_get_feature_sse(3);
features[6] = ccl_get_feature_sse(4);
features[7] = ccl_get_feature_sse(5);
features[8] = ccl_get_feature_sse(6);
features[9] = ccl_get_feature_sse(7);
if(mean) {
for(int i = 0; i < DENOISE_FEATURES; i++)
features[i] = features[i] - mean[i];
}
for(int i = 0; i < DENOISE_FEATURES; i++)
features[i] = mask(active_pixels, features[i]);
}
ccl_device_inline void filter_get_feature_scales_sse(float4 x, float4 y,
int4 active_pixels,
const float *ccl_restrict buffer,
float4 *scales,
const float4 *ccl_restrict mean,
int pass_stride)
{
scales[0] = fabs(x - mean[0]);
scales[1] = fabs(y - mean[1]);
scales[2] = fabs(fabs(ccl_get_feature_sse(0)) - mean[2]);
scales[3] = sqr(ccl_get_feature_sse(1) - mean[3]) +
sqr(ccl_get_feature_sse(2) - mean[4]) +
sqr(ccl_get_feature_sse(3) - mean[5]);
scales[4] = fabs(ccl_get_feature_sse(4) - mean[6]);
scales[5] = sqr(ccl_get_feature_sse(5) - mean[7]) +
sqr(ccl_get_feature_sse(6) - mean[8]) +
sqr(ccl_get_feature_sse(7) - mean[9]);
for(int i = 0; i < 6; i++)
scales[i] = mask(active_pixels, scales[i]);
}
ccl_device_inline void filter_calculate_scale_sse(float4 *scale)
{
scale[0] = rcp(max(reduce_max(scale[0]), make_float4(0.01f)));
scale[1] = rcp(max(reduce_max(scale[1]), make_float4(0.01f)));
scale[2] = rcp(max(reduce_max(scale[2]), make_float4(0.01f)));
scale[6] = rcp(max(reduce_max(scale[4]), make_float4(0.01f)));
scale[7] = scale[8] = scale[9] = rcp(max(reduce_max(sqrt(scale[5])), make_float4(0.01f)));
scale[3] = scale[4] = scale[5] = rcp(max(reduce_max(sqrt(scale[3])), make_float4(0.01f)));
}
CCL_NAMESPACE_END
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