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Diffstat (limited to 'intern/cycles/kernel/filter/filter_transform_sse.h')
-rw-r--r-- | intern/cycles/kernel/filter/filter_transform_sse.h | 129 |
1 files changed, 0 insertions, 129 deletions
diff --git a/intern/cycles/kernel/filter/filter_transform_sse.h b/intern/cycles/kernel/filter/filter_transform_sse.h deleted file mode 100644 index 0304d990f9f..00000000000 --- a/intern/cycles/kernel/filter/filter_transform_sse.h +++ /dev/null @@ -1,129 +0,0 @@ -/* - * 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 - -ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buffer, - CCL_FILTER_TILE_INFO, - int x, - int y, - int4 rect, - int pass_stride, - int frame_stride, - bool use_time, - float *transform, - int *rank, - int radius, - float pca_threshold) -{ - int buffer_w = align_up(rect.z - rect.x, 4); - - float4 features[DENOISE_FEATURES]; - const float *ccl_restrict pixel_buffer; - int3 pixel; - - int num_features = use_time ? 11 : 10; - - /* === Calculate denoising window. === */ - int2 low = make_int2(max(rect.x, x - radius), max(rect.y, y - radius)); - int2 high = make_int2(min(rect.z, x + radius + 1), min(rect.w, y + radius + 1)); - int num_pixels = (high.y - low.y) * (high.x - low.x) * tile_info->num_frames; - - /* === Shift feature passes to have mean 0. === */ - float4 feature_means[DENOISE_FEATURES]; - math_vector_zero_sse(feature_means, num_features); - FOR_PIXEL_WINDOW_SSE - { - filter_get_features_sse( - x4, y4, t4, active_pixels, pixel_buffer, features, use_time, NULL, pass_stride); - math_vector_add_sse(feature_means, num_features, features); - } - END_FOR_PIXEL_WINDOW_SSE - - float4 pixel_scale = make_float4(1.0f / num_pixels); - for (int i = 0; i < num_features; i++) { - feature_means[i] = reduce_add(feature_means[i]) * pixel_scale; - } - - /* === Scale the shifted feature passes to a range of [-1; 1] === - * Will be baked into the transform later. */ - float4 feature_scale[DENOISE_FEATURES]; - math_vector_zero_sse(feature_scale, num_features); - FOR_PIXEL_WINDOW_SSE - { - filter_get_feature_scales_sse( - x4, y4, t4, active_pixels, pixel_buffer, features, use_time, feature_means, pass_stride); - math_vector_max_sse(feature_scale, features, num_features); - } - END_FOR_PIXEL_WINDOW_SSE - - filter_calculate_scale_sse(feature_scale, use_time); - - /* === Generate the feature transformation. === - * This transformation maps the num_features-dimensional feature space to a reduced feature - * (r-feature) space which generally has fewer dimensions. - * This mainly helps to prevent over-fitting. */ - float4 feature_matrix_sse[DENOISE_FEATURES * DENOISE_FEATURES]; - math_matrix_zero_sse(feature_matrix_sse, num_features); - FOR_PIXEL_WINDOW_SSE - { - filter_get_features_sse( - x4, y4, t4, active_pixels, pixel_buffer, features, use_time, feature_means, pass_stride); - math_vector_mul_sse(features, num_features, feature_scale); - math_matrix_add_gramian_sse(feature_matrix_sse, num_features, features, make_float4(1.0f)); - } - END_FOR_PIXEL_WINDOW_SSE - - float feature_matrix[DENOISE_FEATURES * DENOISE_FEATURES]; - math_matrix_hsum(feature_matrix, num_features, feature_matrix_sse); - - math_matrix_jacobi_eigendecomposition(feature_matrix, transform, num_features, 1); - - *rank = 0; - /* Prevent over-fitting when a small window is used. */ - int max_rank = min(num_features, num_pixels / 3); - if (pca_threshold < 0.0f) { - float threshold_energy = 0.0f; - for (int i = 0; i < num_features; i++) { - threshold_energy += feature_matrix[i * num_features + i]; - } - threshold_energy *= 1.0f - (-pca_threshold); - - float reduced_energy = 0.0f; - for (int i = 0; i < max_rank; i++, (*rank)++) { - if (i >= 2 && reduced_energy >= threshold_energy) - break; - float s = feature_matrix[i * num_features + i]; - reduced_energy += s; - } - } - else { - for (int i = 0; i < max_rank; i++, (*rank)++) { - float s = feature_matrix[i * num_features + i]; - if (i >= 2 && sqrtf(s) < pca_threshold) - break; - } - } - - math_matrix_transpose(transform, num_features, 1); - - /* Bake the feature scaling into the transformation matrix. */ - for (int i = 0; i < num_features; i++) { - math_vector_scale(transform + i * num_features, feature_scale[i][0], *rank); - } -} - -CCL_NAMESPACE_END |