1664 lines
52 KiB
C++
1664 lines
52 KiB
C++
// SPDX-License-Identifier: Apache-2.0
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// ----------------------------------------------------------------------------
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// Copyright 2011-2023 Arm Limited
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//
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// Licensed under the Apache License, Version 2.0 (the "License"); you may not
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// use this file except in compliance with the License. You may obtain a copy
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// 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, WITHOUT
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// WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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// License for the specific language governing permissions and limitations
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// under the License.
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// ----------------------------------------------------------------------------
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#if !defined(ASTCENC_DECOMPRESS_ONLY)
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/**
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* @brief Functions for computing color endpoints and texel weights.
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*/
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#include <cassert>
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#include "astcenc_internal.h"
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#include "astcenc_vecmathlib.h"
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/**
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* @brief Compute the infilled weight for N texel indices in a decimated grid.
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*
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* @param di The weight grid decimation to use.
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* @param weights The decimated weight values to use.
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* @param index The first texel index to interpolate.
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*
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* @return The interpolated weight for the given set of SIMD_WIDTH texels.
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*/
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static vfloat bilinear_infill_vla(
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const decimation_info& di,
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const float* weights,
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unsigned int index
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) {
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// Load the bilinear filter texel weight indexes in the decimated grid
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vint weight_idx0 = vint(di.texel_weights_tr[0] + index);
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vint weight_idx1 = vint(di.texel_weights_tr[1] + index);
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vint weight_idx2 = vint(di.texel_weights_tr[2] + index);
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vint weight_idx3 = vint(di.texel_weights_tr[3] + index);
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// Load the bilinear filter weights from the decimated grid
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vfloat weight_val0 = gatherf(weights, weight_idx0);
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vfloat weight_val1 = gatherf(weights, weight_idx1);
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vfloat weight_val2 = gatherf(weights, weight_idx2);
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vfloat weight_val3 = gatherf(weights, weight_idx3);
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// Load the weight contribution factors for each decimated weight
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vfloat tex_weight_float0 = loada(di.texel_weight_contribs_float_tr[0] + index);
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vfloat tex_weight_float1 = loada(di.texel_weight_contribs_float_tr[1] + index);
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vfloat tex_weight_float2 = loada(di.texel_weight_contribs_float_tr[2] + index);
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vfloat tex_weight_float3 = loada(di.texel_weight_contribs_float_tr[3] + index);
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// Compute the bilinear interpolation to generate the per-texel weight
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return (weight_val0 * tex_weight_float0 + weight_val1 * tex_weight_float1) +
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(weight_val2 * tex_weight_float2 + weight_val3 * tex_weight_float3);
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}
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/**
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* @brief Compute the infilled weight for N texel indices in a decimated grid.
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*
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* This is specialized version which computes only two weights per texel for
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* encodings that are only decimated in a single axis.
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*
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* @param di The weight grid decimation to use.
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* @param weights The decimated weight values to use.
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* @param index The first texel index to interpolate.
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*
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* @return The interpolated weight for the given set of SIMD_WIDTH texels.
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*/
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static vfloat bilinear_infill_vla_2(
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const decimation_info& di,
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const float* weights,
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unsigned int index
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) {
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// Load the bilinear filter texel weight indexes in the decimated grid
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vint weight_idx0 = vint(di.texel_weights_tr[0] + index);
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vint weight_idx1 = vint(di.texel_weights_tr[1] + index);
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// Load the bilinear filter weights from the decimated grid
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vfloat weight_val0 = gatherf(weights, weight_idx0);
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vfloat weight_val1 = gatherf(weights, weight_idx1);
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// Load the weight contribution factors for each decimated weight
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vfloat tex_weight_float0 = loada(di.texel_weight_contribs_float_tr[0] + index);
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vfloat tex_weight_float1 = loada(di.texel_weight_contribs_float_tr[1] + index);
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// Compute the bilinear interpolation to generate the per-texel weight
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return (weight_val0 * tex_weight_float0 + weight_val1 * tex_weight_float1);
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}
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/**
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* @brief Compute the ideal endpoints and weights for 1 color component.
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*
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* @param blk The image block color data to compress.
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* @param pi The partition info for the current trial.
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* @param[out] ei The computed ideal endpoints and weights.
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* @param component The color component to compute.
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*/
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static void compute_ideal_colors_and_weights_1_comp(
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const image_block& blk,
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const partition_info& pi,
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endpoints_and_weights& ei,
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unsigned int component
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) {
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unsigned int partition_count = pi.partition_count;
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ei.ep.partition_count = partition_count;
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promise(partition_count > 0);
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unsigned int texel_count = blk.texel_count;
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promise(texel_count > 0);
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float error_weight;
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const float* data_vr = nullptr;
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assert(component < BLOCK_MAX_COMPONENTS);
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switch (component)
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{
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case 0:
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error_weight = blk.channel_weight.lane<0>();
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data_vr = blk.data_r;
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break;
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case 1:
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error_weight = blk.channel_weight.lane<1>();
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data_vr = blk.data_g;
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break;
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case 2:
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error_weight = blk.channel_weight.lane<2>();
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data_vr = blk.data_b;
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break;
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default:
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assert(component == 3);
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error_weight = blk.channel_weight.lane<3>();
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data_vr = blk.data_a;
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break;
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}
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vmask4 sep_mask = vint4::lane_id() == vint4(component);
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bool is_constant_wes { true };
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float partition0_len_sq { 0.0f };
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for (unsigned int i = 0; i < partition_count; i++)
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{
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float lowvalue { 1e10f };
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float highvalue { -1e10f };
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unsigned int partition_texel_count = pi.partition_texel_count[i];
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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float value = data_vr[tix];
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lowvalue = astc::min(value, lowvalue);
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highvalue = astc::max(value, highvalue);
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}
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if (highvalue <= lowvalue)
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{
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lowvalue = 0.0f;
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highvalue = 1e-7f;
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}
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float length = highvalue - lowvalue;
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float length_squared = length * length;
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float scale = 1.0f / length;
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if (i == 0)
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{
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partition0_len_sq = length_squared;
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}
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else
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{
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is_constant_wes = is_constant_wes && length_squared == partition0_len_sq;
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}
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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float value = (data_vr[tix] - lowvalue) * scale;
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value = astc::clamp1f(value);
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ei.weights[tix] = value;
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ei.weight_error_scale[tix] = length_squared * error_weight;
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assert(!astc::isnan(ei.weight_error_scale[tix]));
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}
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ei.ep.endpt0[i] = select(blk.data_min, vfloat4(lowvalue), sep_mask);
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ei.ep.endpt1[i] = select(blk.data_max, vfloat4(highvalue), sep_mask);
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}
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// Zero initialize any SIMD over-fetch
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unsigned int texel_count_simd = round_up_to_simd_multiple_vla(texel_count);
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for (unsigned int i = texel_count; i < texel_count_simd; i++)
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{
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ei.weights[i] = 0.0f;
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ei.weight_error_scale[i] = 0.0f;
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}
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ei.is_constant_weight_error_scale = is_constant_wes;
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}
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/**
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* @brief Compute the ideal endpoints and weights for 2 color components.
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*
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* @param blk The image block color data to compress.
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* @param pi The partition info for the current trial.
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* @param[out] ei The computed ideal endpoints and weights.
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* @param component1 The first color component to compute.
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* @param component2 The second color component to compute.
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*/
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static void compute_ideal_colors_and_weights_2_comp(
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const image_block& blk,
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const partition_info& pi,
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endpoints_and_weights& ei,
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int component1,
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int component2
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) {
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unsigned int partition_count = pi.partition_count;
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ei.ep.partition_count = partition_count;
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promise(partition_count > 0);
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unsigned int texel_count = blk.texel_count;
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promise(texel_count > 0);
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partition_metrics pms[BLOCK_MAX_PARTITIONS];
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float error_weight;
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const float* data_vr = nullptr;
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const float* data_vg = nullptr;
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if (component1 == 0 && component2 == 1)
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{
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error_weight = hadd_s(blk.channel_weight.swz<0, 1>()) / 2.0f;
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data_vr = blk.data_r;
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data_vg = blk.data_g;
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}
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else if (component1 == 0 && component2 == 2)
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{
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error_weight = hadd_s(blk.channel_weight.swz<0, 2>()) / 2.0f;
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data_vr = blk.data_r;
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data_vg = blk.data_b;
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}
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else // (component1 == 1 && component2 == 2)
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{
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assert(component1 == 1 && component2 == 2);
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error_weight = hadd_s(blk.channel_weight.swz<1, 2>()) / 2.0f;
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data_vr = blk.data_g;
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data_vg = blk.data_b;
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}
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compute_avgs_and_dirs_2_comp(pi, blk, component1, component2, pms);
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bool is_constant_wes { true };
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float partition0_len_sq { 0.0f };
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vmask4 comp1_mask = vint4::lane_id() == vint4(component1);
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vmask4 comp2_mask = vint4::lane_id() == vint4(component2);
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for (unsigned int i = 0; i < partition_count; i++)
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{
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vfloat4 dir = pms[i].dir;
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if (hadd_s(dir) < 0.0f)
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{
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dir = vfloat4::zero() - dir;
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}
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line2 line { pms[i].avg, normalize_safe(dir, unit2()) };
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float lowparam { 1e10f };
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float highparam { -1e10f };
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unsigned int partition_texel_count = pi.partition_texel_count[i];
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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vfloat4 point = vfloat2(data_vr[tix], data_vg[tix]);
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float param = dot_s(point - line.a, line.b);
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ei.weights[tix] = param;
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lowparam = astc::min(param, lowparam);
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highparam = astc::max(param, highparam);
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}
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// It is possible for a uniform-color partition to produce length=0;
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// this causes NaN issues so set to small value to avoid this problem
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if (highparam <= lowparam)
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{
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lowparam = 0.0f;
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highparam = 1e-7f;
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}
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float length = highparam - lowparam;
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float length_squared = length * length;
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float scale = 1.0f / length;
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if (i == 0)
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{
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partition0_len_sq = length_squared;
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}
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else
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{
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is_constant_wes = is_constant_wes && length_squared == partition0_len_sq;
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}
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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float idx = (ei.weights[tix] - lowparam) * scale;
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idx = astc::clamp1f(idx);
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ei.weights[tix] = idx;
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ei.weight_error_scale[tix] = length_squared * error_weight;
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assert(!astc::isnan(ei.weight_error_scale[tix]));
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}
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vfloat4 lowvalue = line.a + line.b * lowparam;
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vfloat4 highvalue = line.a + line.b * highparam;
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vfloat4 ep0 = select(blk.data_min, vfloat4(lowvalue.lane<0>()), comp1_mask);
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vfloat4 ep1 = select(blk.data_max, vfloat4(highvalue.lane<0>()), comp1_mask);
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ei.ep.endpt0[i] = select(ep0, vfloat4(lowvalue.lane<1>()), comp2_mask);
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ei.ep.endpt1[i] = select(ep1, vfloat4(highvalue.lane<1>()), comp2_mask);
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}
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// Zero initialize any SIMD over-fetch
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unsigned int texel_count_simd = round_up_to_simd_multiple_vla(texel_count);
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for (unsigned int i = texel_count; i < texel_count_simd; i++)
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{
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ei.weights[i] = 0.0f;
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ei.weight_error_scale[i] = 0.0f;
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}
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ei.is_constant_weight_error_scale = is_constant_wes;
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}
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/**
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* @brief Compute the ideal endpoints and weights for 3 color components.
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*
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* @param blk The image block color data to compress.
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* @param pi The partition info for the current trial.
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* @param[out] ei The computed ideal endpoints and weights.
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* @param omitted_component The color component excluded from the calculation.
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*/
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static void compute_ideal_colors_and_weights_3_comp(
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const image_block& blk,
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const partition_info& pi,
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endpoints_and_weights& ei,
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unsigned int omitted_component
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) {
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unsigned int partition_count = pi.partition_count;
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ei.ep.partition_count = partition_count;
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promise(partition_count > 0);
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unsigned int texel_count = blk.texel_count;
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promise(texel_count > 0);
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partition_metrics pms[BLOCK_MAX_PARTITIONS];
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float error_weight;
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const float* data_vr = nullptr;
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const float* data_vg = nullptr;
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const float* data_vb = nullptr;
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if (omitted_component == 0)
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{
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error_weight = hadd_s(blk.channel_weight.swz<0, 1, 2>());
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data_vr = blk.data_g;
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data_vg = blk.data_b;
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data_vb = blk.data_a;
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}
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else if (omitted_component == 1)
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{
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error_weight = hadd_s(blk.channel_weight.swz<0, 2, 3>());
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data_vr = blk.data_r;
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data_vg = blk.data_b;
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data_vb = blk.data_a;
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}
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else if (omitted_component == 2)
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{
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error_weight = hadd_s(blk.channel_weight.swz<0, 1, 3>());
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data_vr = blk.data_r;
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data_vg = blk.data_g;
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data_vb = blk.data_a;
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}
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else
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{
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assert(omitted_component == 3);
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error_weight = hadd_s(blk.channel_weight.swz<0, 1, 2>());
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data_vr = blk.data_r;
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data_vg = blk.data_g;
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data_vb = blk.data_b;
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}
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error_weight = error_weight * (1.0f / 3.0f);
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if (omitted_component == 3)
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{
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compute_avgs_and_dirs_3_comp_rgb(pi, blk, pms);
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}
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else
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{
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compute_avgs_and_dirs_3_comp(pi, blk, omitted_component, pms);
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}
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bool is_constant_wes { true };
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float partition0_len_sq { 0.0f };
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for (unsigned int i = 0; i < partition_count; i++)
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{
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vfloat4 dir = pms[i].dir;
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if (hadd_rgb_s(dir) < 0.0f)
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{
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dir = vfloat4::zero() - dir;
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}
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line3 line { pms[i].avg, normalize_safe(dir, unit3()) };
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float lowparam { 1e10f };
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float highparam { -1e10f };
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unsigned int partition_texel_count = pi.partition_texel_count[i];
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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vfloat4 point = vfloat3(data_vr[tix], data_vg[tix], data_vb[tix]);
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float param = dot3_s(point - line.a, line.b);
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ei.weights[tix] = param;
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lowparam = astc::min(param, lowparam);
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highparam = astc::max(param, highparam);
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}
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// It is possible for a uniform-color partition to produce length=0;
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// this causes NaN issues so set to small value to avoid this problem
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if (highparam <= lowparam)
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{
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lowparam = 0.0f;
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highparam = 1e-7f;
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}
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float length = highparam - lowparam;
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float length_squared = length * length;
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float scale = 1.0f / length;
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if (i == 0)
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{
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partition0_len_sq = length_squared;
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}
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else
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{
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is_constant_wes = is_constant_wes && length_squared == partition0_len_sq;
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}
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for (unsigned int j = 0; j < partition_texel_count; j++)
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{
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unsigned int tix = pi.texels_of_partition[i][j];
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float idx = (ei.weights[tix] - lowparam) * scale;
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idx = astc::clamp1f(idx);
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ei.weights[tix] = idx;
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ei.weight_error_scale[tix] = length_squared * error_weight;
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assert(!astc::isnan(ei.weight_error_scale[tix]));
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}
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vfloat4 ep0 = line.a + line.b * lowparam;
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vfloat4 ep1 = line.a + line.b * highparam;
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vfloat4 bmin = blk.data_min;
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vfloat4 bmax = blk.data_max;
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assert(omitted_component < BLOCK_MAX_COMPONENTS);
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switch (omitted_component)
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{
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case 0:
|
|
ei.ep.endpt0[i] = vfloat4(bmin.lane<0>(), ep0.lane<0>(), ep0.lane<1>(), ep0.lane<2>());
|
|
ei.ep.endpt1[i] = vfloat4(bmax.lane<0>(), ep1.lane<0>(), ep1.lane<1>(), ep1.lane<2>());
|
|
break;
|
|
case 1:
|
|
ei.ep.endpt0[i] = vfloat4(ep0.lane<0>(), bmin.lane<1>(), ep0.lane<1>(), ep0.lane<2>());
|
|
ei.ep.endpt1[i] = vfloat4(ep1.lane<0>(), bmax.lane<1>(), ep1.lane<1>(), ep1.lane<2>());
|
|
break;
|
|
case 2:
|
|
ei.ep.endpt0[i] = vfloat4(ep0.lane<0>(), ep0.lane<1>(), bmin.lane<2>(), ep0.lane<2>());
|
|
ei.ep.endpt1[i] = vfloat4(ep1.lane<0>(), ep1.lane<1>(), bmax.lane<2>(), ep1.lane<2>());
|
|
break;
|
|
default:
|
|
ei.ep.endpt0[i] = vfloat4(ep0.lane<0>(), ep0.lane<1>(), ep0.lane<2>(), bmin.lane<3>());
|
|
ei.ep.endpt1[i] = vfloat4(ep1.lane<0>(), ep1.lane<1>(), ep1.lane<2>(), bmax.lane<3>());
|
|
break;
|
|
}
|
|
}
|
|
|
|
// Zero initialize any SIMD over-fetch
|
|
unsigned int texel_count_simd = round_up_to_simd_multiple_vla(texel_count);
|
|
for (unsigned int i = texel_count; i < texel_count_simd; i++)
|
|
{
|
|
ei.weights[i] = 0.0f;
|
|
ei.weight_error_scale[i] = 0.0f;
|
|
}
|
|
|
|
ei.is_constant_weight_error_scale = is_constant_wes;
|
|
}
|
|
|
|
/**
|
|
* @brief Compute the ideal endpoints and weights for 4 color components.
|
|
*
|
|
* @param blk The image block color data to compress.
|
|
* @param pi The partition info for the current trial.
|
|
* @param[out] ei The computed ideal endpoints and weights.
|
|
*/
|
|
static void compute_ideal_colors_and_weights_4_comp(
|
|
const image_block& blk,
|
|
const partition_info& pi,
|
|
endpoints_and_weights& ei
|
|
) {
|
|
const float error_weight = hadd_s(blk.channel_weight) / 4.0f;
|
|
|
|
unsigned int partition_count = pi.partition_count;
|
|
|
|
unsigned int texel_count = blk.texel_count;
|
|
promise(texel_count > 0);
|
|
promise(partition_count > 0);
|
|
|
|
partition_metrics pms[BLOCK_MAX_PARTITIONS];
|
|
|
|
compute_avgs_and_dirs_4_comp(pi, blk, pms);
|
|
|
|
bool is_constant_wes { true };
|
|
float partition0_len_sq { 0.0f };
|
|
|
|
for (unsigned int i = 0; i < partition_count; i++)
|
|
{
|
|
vfloat4 dir = pms[i].dir;
|
|
if (hadd_rgb_s(dir) < 0.0f)
|
|
{
|
|
dir = vfloat4::zero() - dir;
|
|
}
|
|
|
|
line4 line { pms[i].avg, normalize_safe(dir, unit4()) };
|
|
float lowparam { 1e10f };
|
|
float highparam { -1e10f };
|
|
|
|
unsigned int partition_texel_count = pi.partition_texel_count[i];
|
|
for (unsigned int j = 0; j < partition_texel_count; j++)
|
|
{
|
|
unsigned int tix = pi.texels_of_partition[i][j];
|
|
vfloat4 point = blk.texel(tix);
|
|
float param = dot_s(point - line.a, line.b);
|
|
ei.weights[tix] = param;
|
|
|
|
lowparam = astc::min(param, lowparam);
|
|
highparam = astc::max(param, highparam);
|
|
}
|
|
|
|
// It is possible for a uniform-color partition to produce length=0;
|
|
// this causes NaN issues so set to small value to avoid this problem
|
|
if (highparam <= lowparam)
|
|
{
|
|
lowparam = 0.0f;
|
|
highparam = 1e-7f;
|
|
}
|
|
|
|
float length = highparam - lowparam;
|
|
float length_squared = length * length;
|
|
float scale = 1.0f / length;
|
|
|
|
if (i == 0)
|
|
{
|
|
partition0_len_sq = length_squared;
|
|
}
|
|
else
|
|
{
|
|
is_constant_wes = is_constant_wes && length_squared == partition0_len_sq;
|
|
}
|
|
|
|
ei.ep.endpt0[i] = line.a + line.b * lowparam;
|
|
ei.ep.endpt1[i] = line.a + line.b * highparam;
|
|
|
|
for (unsigned int j = 0; j < partition_texel_count; j++)
|
|
{
|
|
unsigned int tix = pi.texels_of_partition[i][j];
|
|
float idx = (ei.weights[tix] - lowparam) * scale;
|
|
idx = astc::clamp1f(idx);
|
|
|
|
ei.weights[tix] = idx;
|
|
ei.weight_error_scale[tix] = length_squared * error_weight;
|
|
assert(!astc::isnan(ei.weight_error_scale[tix]));
|
|
}
|
|
}
|
|
|
|
// Zero initialize any SIMD over-fetch
|
|
unsigned int texel_count_simd = round_up_to_simd_multiple_vla(texel_count);
|
|
for (unsigned int i = texel_count; i < texel_count_simd; i++)
|
|
{
|
|
ei.weights[i] = 0.0f;
|
|
ei.weight_error_scale[i] = 0.0f;
|
|
}
|
|
|
|
ei.is_constant_weight_error_scale = is_constant_wes;
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void compute_ideal_colors_and_weights_1plane(
|
|
const image_block& blk,
|
|
const partition_info& pi,
|
|
endpoints_and_weights& ei
|
|
) {
|
|
bool uses_alpha = !blk.is_constant_channel(3);
|
|
|
|
if (uses_alpha)
|
|
{
|
|
compute_ideal_colors_and_weights_4_comp(blk, pi, ei);
|
|
}
|
|
else
|
|
{
|
|
compute_ideal_colors_and_weights_3_comp(blk, pi, ei, 3);
|
|
}
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void compute_ideal_colors_and_weights_2planes(
|
|
const block_size_descriptor& bsd,
|
|
const image_block& blk,
|
|
unsigned int plane2_component,
|
|
endpoints_and_weights& ei1,
|
|
endpoints_and_weights& ei2
|
|
) {
|
|
const auto& pi = bsd.get_partition_info(1, 0);
|
|
bool uses_alpha = !blk.is_constant_channel(3);
|
|
|
|
assert(plane2_component < BLOCK_MAX_COMPONENTS);
|
|
switch (plane2_component)
|
|
{
|
|
case 0: // Separate weights for red
|
|
if (uses_alpha)
|
|
{
|
|
compute_ideal_colors_and_weights_3_comp(blk, pi, ei1, 0);
|
|
}
|
|
else
|
|
{
|
|
compute_ideal_colors_and_weights_2_comp(blk, pi, ei1, 1, 2);
|
|
}
|
|
compute_ideal_colors_and_weights_1_comp(blk, pi, ei2, 0);
|
|
break;
|
|
|
|
case 1: // Separate weights for green
|
|
if (uses_alpha)
|
|
{
|
|
compute_ideal_colors_and_weights_3_comp(blk, pi, ei1, 1);
|
|
}
|
|
else
|
|
{
|
|
compute_ideal_colors_and_weights_2_comp(blk, pi, ei1, 0, 2);
|
|
}
|
|
compute_ideal_colors_and_weights_1_comp(blk, pi, ei2, 1);
|
|
break;
|
|
|
|
case 2: // Separate weights for blue
|
|
if (uses_alpha)
|
|
{
|
|
compute_ideal_colors_and_weights_3_comp(blk, pi, ei1, 2);
|
|
}
|
|
else
|
|
{
|
|
compute_ideal_colors_and_weights_2_comp(blk, pi, ei1, 0, 1);
|
|
}
|
|
compute_ideal_colors_and_weights_1_comp(blk, pi, ei2, 2);
|
|
break;
|
|
|
|
default: // Separate weights for alpha
|
|
assert(uses_alpha);
|
|
compute_ideal_colors_and_weights_3_comp(blk, pi, ei1, 3);
|
|
compute_ideal_colors_and_weights_1_comp(blk, pi, ei2, 3);
|
|
break;
|
|
}
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
float compute_error_of_weight_set_1plane(
|
|
const endpoints_and_weights& eai,
|
|
const decimation_info& di,
|
|
const float* dec_weight_quant_uvalue
|
|
) {
|
|
vfloatacc error_summav = vfloatacc::zero();
|
|
unsigned int texel_count = di.texel_count;
|
|
promise(texel_count > 0);
|
|
|
|
// Process SIMD-width chunks, safe to over-fetch - the extra space is zero initialized
|
|
if (di.max_texel_weight_count > 2)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values = bilinear_infill_vla(di, dec_weight_quant_uvalue, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values = loada(eai.weights + i);
|
|
vfloat diff = current_values - actual_values;
|
|
vfloat significance = loada(eai.weight_error_scale + i);
|
|
vfloat error = diff * diff * significance;
|
|
|
|
haccumulate(error_summav, error);
|
|
}
|
|
}
|
|
else if (di.max_texel_weight_count > 1)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values = bilinear_infill_vla_2(di, dec_weight_quant_uvalue, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values = loada(eai.weights + i);
|
|
vfloat diff = current_values - actual_values;
|
|
vfloat significance = loada(eai.weight_error_scale + i);
|
|
vfloat error = diff * diff * significance;
|
|
|
|
haccumulate(error_summav, error);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Load the weight set directly, without interpolation
|
|
vfloat current_values = loada(dec_weight_quant_uvalue + i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values = loada(eai.weights + i);
|
|
vfloat diff = current_values - actual_values;
|
|
vfloat significance = loada(eai.weight_error_scale + i);
|
|
vfloat error = diff * diff * significance;
|
|
|
|
haccumulate(error_summav, error);
|
|
}
|
|
}
|
|
|
|
// Resolve the final scalar accumulator sum
|
|
return hadd_s(error_summav);
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
float compute_error_of_weight_set_2planes(
|
|
const endpoints_and_weights& eai1,
|
|
const endpoints_and_weights& eai2,
|
|
const decimation_info& di,
|
|
const float* dec_weight_quant_uvalue_plane1,
|
|
const float* dec_weight_quant_uvalue_plane2
|
|
) {
|
|
vfloatacc error_summav = vfloatacc::zero();
|
|
unsigned int texel_count = di.texel_count;
|
|
promise(texel_count > 0);
|
|
|
|
// Process SIMD-width chunks, safe to over-fetch - the extra space is zero initialized
|
|
if (di.max_texel_weight_count > 2)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Plane 1
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values1 = bilinear_infill_vla(di, dec_weight_quant_uvalue_plane1, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values1 = loada(eai1.weights + i);
|
|
vfloat diff = current_values1 - actual_values1;
|
|
vfloat error1 = diff * diff * loada(eai1.weight_error_scale + i);
|
|
|
|
// Plane 2
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values2 = bilinear_infill_vla(di, dec_weight_quant_uvalue_plane2, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values2 = loada(eai2.weights + i);
|
|
diff = current_values2 - actual_values2;
|
|
vfloat error2 = diff * diff * loada(eai2.weight_error_scale + i);
|
|
|
|
haccumulate(error_summav, error1 + error2);
|
|
}
|
|
}
|
|
else if (di.max_texel_weight_count > 1)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Plane 1
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values1 = bilinear_infill_vla_2(di, dec_weight_quant_uvalue_plane1, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values1 = loada(eai1.weights + i);
|
|
vfloat diff = current_values1 - actual_values1;
|
|
vfloat error1 = diff * diff * loada(eai1.weight_error_scale + i);
|
|
|
|
// Plane 2
|
|
// Compute the bilinear interpolation of the decimated weight grid
|
|
vfloat current_values2 = bilinear_infill_vla_2(di, dec_weight_quant_uvalue_plane2, i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values2 = loada(eai2.weights + i);
|
|
diff = current_values2 - actual_values2;
|
|
vfloat error2 = diff * diff * loada(eai2.weight_error_scale + i);
|
|
|
|
haccumulate(error_summav, error1 + error2);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Plane 1
|
|
// Load the weight set directly, without interpolation
|
|
vfloat current_values1 = loada(dec_weight_quant_uvalue_plane1 + i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values1 = loada(eai1.weights + i);
|
|
vfloat diff = current_values1 - actual_values1;
|
|
vfloat error1 = diff * diff * loada(eai1.weight_error_scale + i);
|
|
|
|
// Plane 2
|
|
// Load the weight set directly, without interpolation
|
|
vfloat current_values2 = loada(dec_weight_quant_uvalue_plane2 + i);
|
|
|
|
// Compute the error between the computed value and the ideal weight
|
|
vfloat actual_values2 = loada(eai2.weights + i);
|
|
diff = current_values2 - actual_values2;
|
|
vfloat error2 = diff * diff * loada(eai2.weight_error_scale + i);
|
|
|
|
haccumulate(error_summav, error1 + error2);
|
|
}
|
|
}
|
|
|
|
// Resolve the final scalar accumulator sum
|
|
return hadd_s(error_summav);
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void compute_ideal_weights_for_decimation(
|
|
const endpoints_and_weights& ei,
|
|
const decimation_info& di,
|
|
float* dec_weight_ideal_value
|
|
) {
|
|
unsigned int texel_count = di.texel_count;
|
|
unsigned int weight_count = di.weight_count;
|
|
bool is_direct = texel_count == weight_count;
|
|
promise(texel_count > 0);
|
|
promise(weight_count > 0);
|
|
|
|
// Ensure that the end of the output arrays that are used for SIMD paths later are filled so we
|
|
// can safely run SIMD elsewhere without a loop tail. Note that this is always safe as weight
|
|
// arrays always contain space for 64 elements
|
|
unsigned int prev_weight_count_simd = round_down_to_simd_multiple_vla(weight_count - 1);
|
|
storea(vfloat::zero(), dec_weight_ideal_value + prev_weight_count_simd);
|
|
|
|
// If we have a 1:1 mapping just shortcut the computation. Transfer enough to also copy the
|
|
// zero-initialized SIMD over-fetch region
|
|
if (is_direct)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight(ei.weights + i);
|
|
storea(weight, dec_weight_ideal_value + i);
|
|
}
|
|
|
|
return;
|
|
}
|
|
|
|
// Otherwise compute an estimate and perform single refinement iteration
|
|
alignas(ASTCENC_VECALIGN) float infilled_weights[BLOCK_MAX_TEXELS];
|
|
|
|
// Compute an initial average for each decimated weight
|
|
bool constant_wes = ei.is_constant_weight_error_scale;
|
|
vfloat weight_error_scale(ei.weight_error_scale[0]);
|
|
|
|
// This overshoots - this is OK as we initialize the array tails in the
|
|
// decimation table structures to safe values ...
|
|
for (unsigned int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
// Start with a small value to avoid div-by-zero later
|
|
vfloat weight_weight(1e-10f);
|
|
vfloat initial_weight = vfloat::zero();
|
|
|
|
// Accumulate error weighting of all the texels using this weight
|
|
vint weight_texel_count(di.weight_texel_count + i);
|
|
unsigned int max_texel_count = hmax(weight_texel_count).lane<0>();
|
|
promise(max_texel_count > 0);
|
|
|
|
for (unsigned int j = 0; j < max_texel_count; j++)
|
|
{
|
|
vint texel(di.weight_texels_tr[j] + i);
|
|
vfloat weight = loada(di.weights_texel_contribs_tr[j] + i);
|
|
|
|
if (!constant_wes)
|
|
{
|
|
weight_error_scale = gatherf(ei.weight_error_scale, texel);
|
|
}
|
|
|
|
vfloat contrib_weight = weight * weight_error_scale;
|
|
|
|
weight_weight += contrib_weight;
|
|
initial_weight += gatherf(ei.weights, texel) * contrib_weight;
|
|
}
|
|
|
|
storea(initial_weight / weight_weight, dec_weight_ideal_value + i);
|
|
}
|
|
|
|
// Populate the interpolated weight grid based on the initial average
|
|
// Process SIMD-width texel coordinates at at time while we can. Safe to
|
|
// over-process full SIMD vectors - the tail is zeroed.
|
|
if (di.max_texel_weight_count <= 2)
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla_2(di, dec_weight_ideal_value, i);
|
|
storea(weight, infilled_weights + i);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i = 0; i < texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla(di, dec_weight_ideal_value, i);
|
|
storea(weight, infilled_weights + i);
|
|
}
|
|
}
|
|
|
|
// Perform a single iteration of refinement
|
|
// Empirically determined step size; larger values don't help but smaller drops image quality
|
|
constexpr float stepsize = 0.25f;
|
|
constexpr float chd_scale = -WEIGHTS_TEXEL_SUM;
|
|
|
|
for (unsigned int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight_val = loada(dec_weight_ideal_value + i);
|
|
|
|
// Accumulate error weighting of all the texels using this weight
|
|
// Start with a small value to avoid div-by-zero later
|
|
vfloat error_change0(1e-10f);
|
|
vfloat error_change1(0.0f);
|
|
|
|
// Accumulate error weighting of all the texels using this weight
|
|
vint weight_texel_count(di.weight_texel_count + i);
|
|
unsigned int max_texel_count = hmax(weight_texel_count).lane<0>();
|
|
promise(max_texel_count > 0);
|
|
|
|
for (unsigned int j = 0; j < max_texel_count; j++)
|
|
{
|
|
vint texel(di.weight_texels_tr[j] + i);
|
|
vfloat contrib_weight = loada(di.weights_texel_contribs_tr[j] + i);
|
|
|
|
if (!constant_wes)
|
|
{
|
|
weight_error_scale = gatherf(ei.weight_error_scale, texel);
|
|
}
|
|
|
|
vfloat scale = weight_error_scale * contrib_weight;
|
|
vfloat old_weight = gatherf(infilled_weights, texel);
|
|
vfloat ideal_weight = gatherf(ei.weights, texel);
|
|
|
|
error_change0 += contrib_weight * scale;
|
|
error_change1 += (old_weight - ideal_weight) * scale;
|
|
}
|
|
|
|
vfloat step = (error_change1 * chd_scale) / error_change0;
|
|
step = clamp(-stepsize, stepsize, step);
|
|
|
|
// Update the weight; note this can store negative values
|
|
storea(weight_val + step, dec_weight_ideal_value + i);
|
|
}
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void compute_quantized_weights_for_decimation(
|
|
const decimation_info& di,
|
|
float low_bound,
|
|
float high_bound,
|
|
const float* dec_weight_ideal_value,
|
|
float* weight_set_out,
|
|
uint8_t* quantized_weight_set,
|
|
quant_method quant_level
|
|
) {
|
|
int weight_count = di.weight_count;
|
|
promise(weight_count > 0);
|
|
const quant_and_transfer_table& qat = quant_and_xfer_tables[quant_level];
|
|
|
|
// The available quant levels, stored with a minus 1 bias
|
|
static const float quant_levels_m1[12] {
|
|
1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 7.0f, 9.0f, 11.0f, 15.0f, 19.0f, 23.0f, 31.0f
|
|
};
|
|
|
|
vint steps_m1(get_quant_level(quant_level) - 1);
|
|
float quant_level_m1 = quant_levels_m1[quant_level];
|
|
|
|
// Quantize the weight set using both the specified low/high bounds and standard 0..1 bounds
|
|
|
|
// TODO: Oddity to investigate; triggered by test in issue #265.
|
|
if (high_bound <= low_bound)
|
|
{
|
|
low_bound = 0.0f;
|
|
high_bound = 1.0f;
|
|
}
|
|
|
|
float rscale = high_bound - low_bound;
|
|
float scale = 1.0f / rscale;
|
|
|
|
float scaled_low_bound = low_bound * scale;
|
|
rscale *= 1.0f / 64.0f;
|
|
|
|
vfloat scalev(scale);
|
|
vfloat scaled_low_boundv(scaled_low_bound);
|
|
vfloat quant_level_m1v(quant_level_m1);
|
|
vfloat rscalev(rscale);
|
|
vfloat low_boundv(low_bound);
|
|
|
|
// This runs to the rounded-up SIMD size, which is safe as the loop tail is filled with known
|
|
// safe data in compute_ideal_weights_for_decimation and arrays are always 64 elements
|
|
if (get_quant_level(quant_level) <= 16)
|
|
{
|
|
vint4 tab0(reinterpret_cast<const int*>(qat.quant_to_unquant));
|
|
vint tab0p;
|
|
vtable_prepare(tab0, tab0p);
|
|
|
|
for (int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat ix = loada(dec_weight_ideal_value + i) * scalev - scaled_low_boundv;
|
|
ix = clampzo(ix);
|
|
|
|
// Look up the two closest indexes and return the one that was closest
|
|
vfloat ix1 = ix * quant_level_m1v;
|
|
|
|
vint weightl = float_to_int(ix1);
|
|
vint weighth = min(weightl + vint(1), steps_m1);
|
|
|
|
vint ixli = vtable_8bt_32bi(tab0p, weightl);
|
|
vint ixhi = vtable_8bt_32bi(tab0p, weighth);
|
|
|
|
vfloat ixl = int_to_float(ixli);
|
|
vfloat ixh = int_to_float(ixhi);
|
|
|
|
vmask mask = (ixl + ixh) < (vfloat(128.0f) * ix);
|
|
vint weight = select(ixli, ixhi, mask);
|
|
ixl = select(ixl, ixh, mask);
|
|
|
|
// Invert the weight-scaling that was done initially
|
|
storea(ixl * rscalev + low_boundv, weight_set_out + i);
|
|
vint scn = pack_low_bytes(weight);
|
|
store_nbytes(scn, quantized_weight_set + i);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
vint4 tab0(reinterpret_cast<const int*>(qat.quant_to_unquant));
|
|
vint4 tab1(reinterpret_cast<const int*>(qat.quant_to_unquant + 16));
|
|
vint tab0p, tab1p;
|
|
vtable_prepare(tab0, tab1, tab0p, tab1p);
|
|
|
|
for (int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat ix = loada(dec_weight_ideal_value + i) * scalev - scaled_low_boundv;
|
|
ix = clampzo(ix);
|
|
|
|
// Look up the two closest indexes and return the one that was closest
|
|
vfloat ix1 = ix * quant_level_m1v;
|
|
|
|
vint weightl = float_to_int(ix1);
|
|
vint weighth = min(weightl + vint(1), steps_m1);
|
|
|
|
vint ixli = vtable_8bt_32bi(tab0p, tab1p, weightl);
|
|
vint ixhi = vtable_8bt_32bi(tab0p, tab1p, weighth);
|
|
|
|
vfloat ixl = int_to_float(ixli);
|
|
vfloat ixh = int_to_float(ixhi);
|
|
|
|
vmask mask = (ixl + ixh) < (vfloat(128.0f) * ix);
|
|
vint weight = select(ixli, ixhi, mask);
|
|
ixl = select(ixl, ixh, mask);
|
|
|
|
// Invert the weight-scaling that was done initially
|
|
storea(ixl * rscalev + low_boundv, weight_set_out + i);
|
|
vint scn = pack_low_bytes(weight);
|
|
store_nbytes(scn, quantized_weight_set + i);
|
|
}
|
|
}
|
|
}
|
|
|
|
/**
|
|
* @brief Compute the RGB + offset for a HDR endpoint mode #7.
|
|
*
|
|
* Since the matrix needed has a regular structure we can simplify the inverse calculation. This
|
|
* gives us ~24 multiplications vs. 96 for a generic inverse.
|
|
*
|
|
* mat[0] = vfloat4(rgba_ws.x, 0.0f, 0.0f, wght_ws.x);
|
|
* mat[1] = vfloat4( 0.0f, rgba_ws.y, 0.0f, wght_ws.y);
|
|
* mat[2] = vfloat4( 0.0f, 0.0f, rgba_ws.z, wght_ws.z);
|
|
* mat[3] = vfloat4(wght_ws.x, wght_ws.y, wght_ws.z, psum);
|
|
* mat = invert(mat);
|
|
*
|
|
* @param rgba_weight_sum Sum of partition component error weights.
|
|
* @param weight_weight_sum Sum of partition component error weights * texel weight.
|
|
* @param rgbq_sum Sum of partition component error weights * texel weight * color data.
|
|
* @param psum Sum of RGB color weights * texel weight^2.
|
|
*/
|
|
static inline vfloat4 compute_rgbo_vector(
|
|
vfloat4 rgba_weight_sum,
|
|
vfloat4 weight_weight_sum,
|
|
vfloat4 rgbq_sum,
|
|
float psum
|
|
) {
|
|
float X = rgba_weight_sum.lane<0>();
|
|
float Y = rgba_weight_sum.lane<1>();
|
|
float Z = rgba_weight_sum.lane<2>();
|
|
float P = weight_weight_sum.lane<0>();
|
|
float Q = weight_weight_sum.lane<1>();
|
|
float R = weight_weight_sum.lane<2>();
|
|
float S = psum;
|
|
|
|
float PP = P * P;
|
|
float QQ = Q * Q;
|
|
float RR = R * R;
|
|
|
|
float SZmRR = S * Z - RR;
|
|
float DT = SZmRR * Y - Z * QQ;
|
|
float YP = Y * P;
|
|
float QX = Q * X;
|
|
float YX = Y * X;
|
|
float mZYP = -Z * YP;
|
|
float mZQX = -Z * QX;
|
|
float mRYX = -R * YX;
|
|
float ZQP = Z * Q * P;
|
|
float RYP = R * YP;
|
|
float RQX = R * QX;
|
|
|
|
// Compute the reciprocal of matrix determinant
|
|
float rdet = 1.0f / (DT * X + mZYP * P);
|
|
|
|
// Actually compute the adjugate, and then apply 1/det separately
|
|
vfloat4 mat0(DT, ZQP, RYP, mZYP);
|
|
vfloat4 mat1(ZQP, SZmRR * X - Z * PP, RQX, mZQX);
|
|
vfloat4 mat2(RYP, RQX, (S * Y - QQ) * X - Y * PP, mRYX);
|
|
vfloat4 mat3(mZYP, mZQX, mRYX, Z * YX);
|
|
vfloat4 vect = rgbq_sum * rdet;
|
|
|
|
return vfloat4(dot_s(mat0, vect),
|
|
dot_s(mat1, vect),
|
|
dot_s(mat2, vect),
|
|
dot_s(mat3, vect));
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void recompute_ideal_colors_1plane(
|
|
const image_block& blk,
|
|
const partition_info& pi,
|
|
const decimation_info& di,
|
|
const uint8_t* dec_weights_uquant,
|
|
endpoints& ep,
|
|
vfloat4 rgbs_vectors[BLOCK_MAX_PARTITIONS],
|
|
vfloat4 rgbo_vectors[BLOCK_MAX_PARTITIONS]
|
|
) {
|
|
unsigned int weight_count = di.weight_count;
|
|
unsigned int total_texel_count = blk.texel_count;
|
|
unsigned int partition_count = pi.partition_count;
|
|
|
|
promise(weight_count > 0);
|
|
promise(total_texel_count > 0);
|
|
promise(partition_count > 0);
|
|
|
|
alignas(ASTCENC_VECALIGN) float dec_weight[BLOCK_MAX_WEIGHTS];
|
|
for (unsigned int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vint unquant_value(dec_weights_uquant + i);
|
|
vfloat unquant_valuef = int_to_float(unquant_value) * vfloat(1.0f / 64.0f);
|
|
storea(unquant_valuef, dec_weight + i);
|
|
}
|
|
|
|
alignas(ASTCENC_VECALIGN) float undec_weight[BLOCK_MAX_TEXELS];
|
|
float* undec_weight_ref;
|
|
if (di.max_texel_weight_count == 1)
|
|
{
|
|
undec_weight_ref = dec_weight;
|
|
}
|
|
else if (di.max_texel_weight_count <= 2)
|
|
{
|
|
for (unsigned int i = 0; i < total_texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla_2(di, dec_weight, i);
|
|
storea(weight, undec_weight + i);
|
|
}
|
|
|
|
undec_weight_ref = undec_weight;
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i = 0; i < total_texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla(di, dec_weight, i);
|
|
storea(weight, undec_weight + i);
|
|
}
|
|
|
|
undec_weight_ref = undec_weight;
|
|
}
|
|
|
|
vfloat4 rgba_sum(blk.data_mean * static_cast<float>(blk.texel_count));
|
|
|
|
for (unsigned int i = 0; i < partition_count; i++)
|
|
{
|
|
unsigned int texel_count = pi.partition_texel_count[i];
|
|
const uint8_t *texel_indexes = pi.texels_of_partition[i];
|
|
|
|
// Only compute a partition mean if more than one partition
|
|
if (partition_count > 1)
|
|
{
|
|
rgba_sum = vfloat4::zero();
|
|
promise(texel_count > 0);
|
|
for (unsigned int j = 0; j < texel_count; j++)
|
|
{
|
|
unsigned int tix = texel_indexes[j];
|
|
rgba_sum += blk.texel(tix);
|
|
}
|
|
}
|
|
|
|
rgba_sum = rgba_sum * blk.channel_weight;
|
|
vfloat4 rgba_weight_sum = max(blk.channel_weight * static_cast<float>(texel_count), 1e-17f);
|
|
vfloat4 scale_dir = normalize((rgba_sum / rgba_weight_sum).swz<0, 1, 2>());
|
|
|
|
float scale_max = 0.0f;
|
|
float scale_min = 1e10f;
|
|
|
|
float wmin1 = 1.0f;
|
|
float wmax1 = 0.0f;
|
|
|
|
float left_sum_s = 0.0f;
|
|
float middle_sum_s = 0.0f;
|
|
float right_sum_s = 0.0f;
|
|
|
|
vfloat4 color_vec_x = vfloat4::zero();
|
|
vfloat4 color_vec_y = vfloat4::zero();
|
|
|
|
vfloat4 scale_vec = vfloat4::zero();
|
|
|
|
float weight_weight_sum_s = 1e-17f;
|
|
|
|
vfloat4 color_weight = blk.channel_weight;
|
|
float ls_weight = hadd_rgb_s(color_weight);
|
|
|
|
for (unsigned int j = 0; j < texel_count; j++)
|
|
{
|
|
unsigned int tix = texel_indexes[j];
|
|
vfloat4 rgba = blk.texel(tix);
|
|
|
|
float idx0 = undec_weight_ref[tix];
|
|
|
|
float om_idx0 = 1.0f - idx0;
|
|
wmin1 = astc::min(idx0, wmin1);
|
|
wmax1 = astc::max(idx0, wmax1);
|
|
|
|
float scale = dot3_s(scale_dir, rgba);
|
|
scale_min = astc::min(scale, scale_min);
|
|
scale_max = astc::max(scale, scale_max);
|
|
|
|
left_sum_s += om_idx0 * om_idx0;
|
|
middle_sum_s += om_idx0 * idx0;
|
|
right_sum_s += idx0 * idx0;
|
|
weight_weight_sum_s += idx0;
|
|
|
|
vfloat4 color_idx(idx0);
|
|
vfloat4 cwprod = rgba;
|
|
vfloat4 cwiprod = cwprod * color_idx;
|
|
|
|
color_vec_y += cwiprod;
|
|
color_vec_x += cwprod - cwiprod;
|
|
|
|
scale_vec += vfloat2(om_idx0, idx0) * (scale * ls_weight);
|
|
}
|
|
|
|
vfloat4 left_sum = vfloat4(left_sum_s) * color_weight;
|
|
vfloat4 middle_sum = vfloat4(middle_sum_s) * color_weight;
|
|
vfloat4 right_sum = vfloat4(right_sum_s) * color_weight;
|
|
vfloat4 lmrs_sum = vfloat3(left_sum_s, middle_sum_s, right_sum_s) * ls_weight;
|
|
|
|
color_vec_x = color_vec_x * color_weight;
|
|
color_vec_y = color_vec_y * color_weight;
|
|
|
|
// Initialize the luminance and scale vectors with a reasonable default
|
|
float scalediv = scale_min / astc::max(scale_max, 1e-10f);
|
|
scalediv = astc::clamp1f(scalediv);
|
|
|
|
vfloat4 sds = scale_dir * scale_max;
|
|
|
|
rgbs_vectors[i] = vfloat4(sds.lane<0>(), sds.lane<1>(), sds.lane<2>(), scalediv);
|
|
|
|
if (wmin1 >= wmax1 * 0.999f)
|
|
{
|
|
// If all weights in the partition were equal, then just take average of all colors in
|
|
// the partition and use that as both endpoint colors
|
|
vfloat4 avg = (color_vec_x + color_vec_y) / rgba_weight_sum;
|
|
|
|
vmask4 notnan_mask = avg == avg;
|
|
ep.endpt0[i] = select(ep.endpt0[i], avg, notnan_mask);
|
|
ep.endpt1[i] = select(ep.endpt1[i], avg, notnan_mask);
|
|
|
|
rgbs_vectors[i] = vfloat4(sds.lane<0>(), sds.lane<1>(), sds.lane<2>(), 1.0f);
|
|
}
|
|
else
|
|
{
|
|
// Otherwise, complete the analytic calculation of ideal-endpoint-values for the given
|
|
// set of texel weights and pixel colors
|
|
vfloat4 color_det1 = (left_sum * right_sum) - (middle_sum * middle_sum);
|
|
vfloat4 color_rdet1 = 1.0f / color_det1;
|
|
|
|
float ls_det1 = (lmrs_sum.lane<0>() * lmrs_sum.lane<2>()) - (lmrs_sum.lane<1>() * lmrs_sum.lane<1>());
|
|
float ls_rdet1 = 1.0f / ls_det1;
|
|
|
|
vfloat4 color_mss1 = (left_sum * left_sum)
|
|
+ (2.0f * middle_sum * middle_sum)
|
|
+ (right_sum * right_sum);
|
|
|
|
float ls_mss1 = (lmrs_sum.lane<0>() * lmrs_sum.lane<0>())
|
|
+ (2.0f * lmrs_sum.lane<1>() * lmrs_sum.lane<1>())
|
|
+ (lmrs_sum.lane<2>() * lmrs_sum.lane<2>());
|
|
|
|
vfloat4 ep0 = (right_sum * color_vec_x - middle_sum * color_vec_y) * color_rdet1;
|
|
vfloat4 ep1 = (left_sum * color_vec_y - middle_sum * color_vec_x) * color_rdet1;
|
|
|
|
vmask4 det_mask = abs(color_det1) > (color_mss1 * 1e-4f);
|
|
vmask4 notnan_mask = (ep0 == ep0) & (ep1 == ep1);
|
|
vmask4 full_mask = det_mask & notnan_mask;
|
|
|
|
ep.endpt0[i] = select(ep.endpt0[i], ep0, full_mask);
|
|
ep.endpt1[i] = select(ep.endpt1[i], ep1, full_mask);
|
|
|
|
float scale_ep0 = (lmrs_sum.lane<2>() * scale_vec.lane<0>() - lmrs_sum.lane<1>() * scale_vec.lane<1>()) * ls_rdet1;
|
|
float scale_ep1 = (lmrs_sum.lane<0>() * scale_vec.lane<1>() - lmrs_sum.lane<1>() * scale_vec.lane<0>()) * ls_rdet1;
|
|
|
|
if (fabsf(ls_det1) > (ls_mss1 * 1e-4f) && scale_ep0 == scale_ep0 && scale_ep1 == scale_ep1 && scale_ep0 < scale_ep1)
|
|
{
|
|
float scalediv2 = scale_ep0 / scale_ep1;
|
|
vfloat4 sdsm = scale_dir * scale_ep1;
|
|
rgbs_vectors[i] = vfloat4(sdsm.lane<0>(), sdsm.lane<1>(), sdsm.lane<2>(), scalediv2);
|
|
}
|
|
}
|
|
|
|
// Calculations specific to mode #7, the HDR RGB-scale mode - skip if known LDR
|
|
if (blk.rgb_lns[0] || blk.alpha_lns[0])
|
|
{
|
|
vfloat4 weight_weight_sum = vfloat4(weight_weight_sum_s) * color_weight;
|
|
float psum = right_sum_s * hadd_rgb_s(color_weight);
|
|
|
|
vfloat4 rgbq_sum = color_vec_x + color_vec_y;
|
|
rgbq_sum.set_lane<3>(hadd_rgb_s(color_vec_y));
|
|
|
|
vfloat4 rgbovec = compute_rgbo_vector(rgba_weight_sum, weight_weight_sum, rgbq_sum, psum);
|
|
rgbo_vectors[i] = rgbovec;
|
|
|
|
// We can get a failure due to the use of a singular (non-invertible) matrix
|
|
// If it failed, compute rgbo_vectors[] with a different method ...
|
|
if (astc::isnan(dot_s(rgbovec, rgbovec)))
|
|
{
|
|
vfloat4 v0 = ep.endpt0[i];
|
|
vfloat4 v1 = ep.endpt1[i];
|
|
|
|
float avgdif = hadd_rgb_s(v1 - v0) * (1.0f / 3.0f);
|
|
avgdif = astc::max(avgdif, 0.0f);
|
|
|
|
vfloat4 avg = (v0 + v1) * 0.5f;
|
|
vfloat4 ep0 = avg - vfloat4(avgdif) * 0.5f;
|
|
rgbo_vectors[i] = vfloat4(ep0.lane<0>(), ep0.lane<1>(), ep0.lane<2>(), avgdif);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
/* See header for documentation. */
|
|
void recompute_ideal_colors_2planes(
|
|
const image_block& blk,
|
|
const block_size_descriptor& bsd,
|
|
const decimation_info& di,
|
|
const uint8_t* dec_weights_uquant_plane1,
|
|
const uint8_t* dec_weights_uquant_plane2,
|
|
endpoints& ep,
|
|
vfloat4& rgbs_vector,
|
|
vfloat4& rgbo_vector,
|
|
int plane2_component
|
|
) {
|
|
unsigned int weight_count = di.weight_count;
|
|
unsigned int total_texel_count = blk.texel_count;
|
|
|
|
promise(total_texel_count > 0);
|
|
promise(weight_count > 0);
|
|
|
|
alignas(ASTCENC_VECALIGN) float dec_weight_plane1[BLOCK_MAX_WEIGHTS_2PLANE];
|
|
alignas(ASTCENC_VECALIGN) float dec_weight_plane2[BLOCK_MAX_WEIGHTS_2PLANE];
|
|
|
|
assert(weight_count <= BLOCK_MAX_WEIGHTS_2PLANE);
|
|
|
|
for (unsigned int i = 0; i < weight_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vint unquant_value1(dec_weights_uquant_plane1 + i);
|
|
vfloat unquant_value1f = int_to_float(unquant_value1) * vfloat(1.0f / 64.0f);
|
|
storea(unquant_value1f, dec_weight_plane1 + i);
|
|
|
|
vint unquant_value2(dec_weights_uquant_plane2 + i);
|
|
vfloat unquant_value2f = int_to_float(unquant_value2) * vfloat(1.0f / 64.0f);
|
|
storea(unquant_value2f, dec_weight_plane2 + i);
|
|
}
|
|
|
|
alignas(ASTCENC_VECALIGN) float undec_weight_plane1[BLOCK_MAX_TEXELS];
|
|
alignas(ASTCENC_VECALIGN) float undec_weight_plane2[BLOCK_MAX_TEXELS];
|
|
|
|
float* undec_weight_plane1_ref;
|
|
float* undec_weight_plane2_ref;
|
|
|
|
if (di.max_texel_weight_count == 1)
|
|
{
|
|
undec_weight_plane1_ref = dec_weight_plane1;
|
|
undec_weight_plane2_ref = dec_weight_plane2;
|
|
}
|
|
else if (di.max_texel_weight_count <= 2)
|
|
{
|
|
for (unsigned int i = 0; i < total_texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla_2(di, dec_weight_plane1, i);
|
|
storea(weight, undec_weight_plane1 + i);
|
|
|
|
weight = bilinear_infill_vla_2(di, dec_weight_plane2, i);
|
|
storea(weight, undec_weight_plane2 + i);
|
|
}
|
|
|
|
undec_weight_plane1_ref = undec_weight_plane1;
|
|
undec_weight_plane2_ref = undec_weight_plane2;
|
|
}
|
|
else
|
|
{
|
|
for (unsigned int i = 0; i < total_texel_count; i += ASTCENC_SIMD_WIDTH)
|
|
{
|
|
vfloat weight = bilinear_infill_vla(di, dec_weight_plane1, i);
|
|
storea(weight, undec_weight_plane1 + i);
|
|
|
|
weight = bilinear_infill_vla(di, dec_weight_plane2, i);
|
|
storea(weight, undec_weight_plane2 + i);
|
|
}
|
|
|
|
undec_weight_plane1_ref = undec_weight_plane1;
|
|
undec_weight_plane2_ref = undec_weight_plane2;
|
|
}
|
|
|
|
unsigned int texel_count = bsd.texel_count;
|
|
vfloat4 rgba_weight_sum = max(blk.channel_weight * static_cast<float>(texel_count), 1e-17f);
|
|
vfloat4 scale_dir = normalize(blk.data_mean.swz<0, 1, 2>());
|
|
|
|
float scale_max = 0.0f;
|
|
float scale_min = 1e10f;
|
|
|
|
float wmin1 = 1.0f;
|
|
float wmax1 = 0.0f;
|
|
|
|
float wmin2 = 1.0f;
|
|
float wmax2 = 0.0f;
|
|
|
|
float left1_sum_s = 0.0f;
|
|
float middle1_sum_s = 0.0f;
|
|
float right1_sum_s = 0.0f;
|
|
|
|
float left2_sum_s = 0.0f;
|
|
float middle2_sum_s = 0.0f;
|
|
float right2_sum_s = 0.0f;
|
|
|
|
vfloat4 color_vec_x = vfloat4::zero();
|
|
vfloat4 color_vec_y = vfloat4::zero();
|
|
|
|
vfloat4 scale_vec = vfloat4::zero();
|
|
|
|
vfloat4 weight_weight_sum = vfloat4(1e-17f);
|
|
|
|
vmask4 p2_mask = vint4::lane_id() == vint4(plane2_component);
|
|
vfloat4 color_weight = blk.channel_weight;
|
|
float ls_weight = hadd_rgb_s(color_weight);
|
|
|
|
for (unsigned int j = 0; j < texel_count; j++)
|
|
{
|
|
vfloat4 rgba = blk.texel(j);
|
|
|
|
float idx0 = undec_weight_plane1_ref[j];
|
|
|
|
float om_idx0 = 1.0f - idx0;
|
|
wmin1 = astc::min(idx0, wmin1);
|
|
wmax1 = astc::max(idx0, wmax1);
|
|
|
|
float scale = dot3_s(scale_dir, rgba);
|
|
scale_min = astc::min(scale, scale_min);
|
|
scale_max = astc::max(scale, scale_max);
|
|
|
|
left1_sum_s += om_idx0 * om_idx0;
|
|
middle1_sum_s += om_idx0 * idx0;
|
|
right1_sum_s += idx0 * idx0;
|
|
|
|
float idx1 = undec_weight_plane2_ref[j];
|
|
|
|
float om_idx1 = 1.0f - idx1;
|
|
wmin2 = astc::min(idx1, wmin2);
|
|
wmax2 = astc::max(idx1, wmax2);
|
|
|
|
left2_sum_s += om_idx1 * om_idx1;
|
|
middle2_sum_s += om_idx1 * idx1;
|
|
right2_sum_s += idx1 * idx1;
|
|
|
|
vfloat4 color_idx = select(vfloat4(idx0), vfloat4(idx1), p2_mask);
|
|
|
|
vfloat4 cwprod = rgba;
|
|
vfloat4 cwiprod = cwprod * color_idx;
|
|
|
|
color_vec_y += cwiprod;
|
|
color_vec_x += cwprod - cwiprod;
|
|
|
|
scale_vec += vfloat2(om_idx0, idx0) * (ls_weight * scale);
|
|
weight_weight_sum += color_idx;
|
|
}
|
|
|
|
vfloat4 left1_sum = vfloat4(left1_sum_s) * color_weight;
|
|
vfloat4 middle1_sum = vfloat4(middle1_sum_s) * color_weight;
|
|
vfloat4 right1_sum = vfloat4(right1_sum_s) * color_weight;
|
|
vfloat4 lmrs_sum = vfloat3(left1_sum_s, middle1_sum_s, right1_sum_s) * ls_weight;
|
|
|
|
vfloat4 left2_sum = vfloat4(left2_sum_s) * color_weight;
|
|
vfloat4 middle2_sum = vfloat4(middle2_sum_s) * color_weight;
|
|
vfloat4 right2_sum = vfloat4(right2_sum_s) * color_weight;
|
|
|
|
color_vec_x = color_vec_x * color_weight;
|
|
color_vec_y = color_vec_y * color_weight;
|
|
|
|
// Initialize the luminance and scale vectors with a reasonable default
|
|
float scalediv = scale_min / astc::max(scale_max, 1e-10f);
|
|
scalediv = astc::clamp1f(scalediv);
|
|
|
|
vfloat4 sds = scale_dir * scale_max;
|
|
|
|
rgbs_vector = vfloat4(sds.lane<0>(), sds.lane<1>(), sds.lane<2>(), scalediv);
|
|
|
|
if (wmin1 >= wmax1 * 0.999f)
|
|
{
|
|
// If all weights in the partition were equal, then just take average of all colors in
|
|
// the partition and use that as both endpoint colors
|
|
vfloat4 avg = (color_vec_x + color_vec_y) / rgba_weight_sum;
|
|
|
|
vmask4 p1_mask = vint4::lane_id() != vint4(plane2_component);
|
|
vmask4 notnan_mask = avg == avg;
|
|
vmask4 full_mask = p1_mask & notnan_mask;
|
|
|
|
ep.endpt0[0] = select(ep.endpt0[0], avg, full_mask);
|
|
ep.endpt1[0] = select(ep.endpt1[0], avg, full_mask);
|
|
|
|
rgbs_vector = vfloat4(sds.lane<0>(), sds.lane<1>(), sds.lane<2>(), 1.0f);
|
|
}
|
|
else
|
|
{
|
|
// Otherwise, complete the analytic calculation of ideal-endpoint-values for the given
|
|
// set of texel weights and pixel colors
|
|
vfloat4 color_det1 = (left1_sum * right1_sum) - (middle1_sum * middle1_sum);
|
|
vfloat4 color_rdet1 = 1.0f / color_det1;
|
|
|
|
float ls_det1 = (lmrs_sum.lane<0>() * lmrs_sum.lane<2>()) - (lmrs_sum.lane<1>() * lmrs_sum.lane<1>());
|
|
float ls_rdet1 = 1.0f / ls_det1;
|
|
|
|
vfloat4 color_mss1 = (left1_sum * left1_sum)
|
|
+ (2.0f * middle1_sum * middle1_sum)
|
|
+ (right1_sum * right1_sum);
|
|
|
|
float ls_mss1 = (lmrs_sum.lane<0>() * lmrs_sum.lane<0>())
|
|
+ (2.0f * lmrs_sum.lane<1>() * lmrs_sum.lane<1>())
|
|
+ (lmrs_sum.lane<2>() * lmrs_sum.lane<2>());
|
|
|
|
vfloat4 ep0 = (right1_sum * color_vec_x - middle1_sum * color_vec_y) * color_rdet1;
|
|
vfloat4 ep1 = (left1_sum * color_vec_y - middle1_sum * color_vec_x) * color_rdet1;
|
|
|
|
float scale_ep0 = (lmrs_sum.lane<2>() * scale_vec.lane<0>() - lmrs_sum.lane<1>() * scale_vec.lane<1>()) * ls_rdet1;
|
|
float scale_ep1 = (lmrs_sum.lane<0>() * scale_vec.lane<1>() - lmrs_sum.lane<1>() * scale_vec.lane<0>()) * ls_rdet1;
|
|
|
|
vmask4 p1_mask = vint4::lane_id() != vint4(plane2_component);
|
|
vmask4 det_mask = abs(color_det1) > (color_mss1 * 1e-4f);
|
|
vmask4 notnan_mask = (ep0 == ep0) & (ep1 == ep1);
|
|
vmask4 full_mask = p1_mask & det_mask & notnan_mask;
|
|
|
|
ep.endpt0[0] = select(ep.endpt0[0], ep0, full_mask);
|
|
ep.endpt1[0] = select(ep.endpt1[0], ep1, full_mask);
|
|
|
|
if (fabsf(ls_det1) > (ls_mss1 * 1e-4f) && scale_ep0 == scale_ep0 && scale_ep1 == scale_ep1 && scale_ep0 < scale_ep1)
|
|
{
|
|
float scalediv2 = scale_ep0 / scale_ep1;
|
|
vfloat4 sdsm = scale_dir * scale_ep1;
|
|
rgbs_vector = vfloat4(sdsm.lane<0>(), sdsm.lane<1>(), sdsm.lane<2>(), scalediv2);
|
|
}
|
|
}
|
|
|
|
if (wmin2 >= wmax2 * 0.999f)
|
|
{
|
|
// If all weights in the partition were equal, then just take average of all colors in
|
|
// the partition and use that as both endpoint colors
|
|
vfloat4 avg = (color_vec_x + color_vec_y) / rgba_weight_sum;
|
|
|
|
vmask4 notnan_mask = avg == avg;
|
|
vmask4 full_mask = p2_mask & notnan_mask;
|
|
|
|
ep.endpt0[0] = select(ep.endpt0[0], avg, full_mask);
|
|
ep.endpt1[0] = select(ep.endpt1[0], avg, full_mask);
|
|
}
|
|
else
|
|
{
|
|
// Otherwise, complete the analytic calculation of ideal-endpoint-values for the given
|
|
// set of texel weights and pixel colors
|
|
vfloat4 color_det2 = (left2_sum * right2_sum) - (middle2_sum * middle2_sum);
|
|
vfloat4 color_rdet2 = 1.0f / color_det2;
|
|
|
|
vfloat4 color_mss2 = (left2_sum * left2_sum)
|
|
+ (2.0f * middle2_sum * middle2_sum)
|
|
+ (right2_sum * right2_sum);
|
|
|
|
vfloat4 ep0 = (right2_sum * color_vec_x - middle2_sum * color_vec_y) * color_rdet2;
|
|
vfloat4 ep1 = (left2_sum * color_vec_y - middle2_sum * color_vec_x) * color_rdet2;
|
|
|
|
vmask4 det_mask = abs(color_det2) > (color_mss2 * 1e-4f);
|
|
vmask4 notnan_mask = (ep0 == ep0) & (ep1 == ep1);
|
|
vmask4 full_mask = p2_mask & det_mask & notnan_mask;
|
|
|
|
ep.endpt0[0] = select(ep.endpt0[0], ep0, full_mask);
|
|
ep.endpt1[0] = select(ep.endpt1[0], ep1, full_mask);
|
|
}
|
|
|
|
// Calculations specific to mode #7, the HDR RGB-scale mode - skip if known LDR
|
|
if (blk.rgb_lns[0] || blk.alpha_lns[0])
|
|
{
|
|
weight_weight_sum = weight_weight_sum * color_weight;
|
|
float psum = dot3_s(select(right1_sum, right2_sum, p2_mask), color_weight);
|
|
|
|
vfloat4 rgbq_sum = color_vec_x + color_vec_y;
|
|
rgbq_sum.set_lane<3>(hadd_rgb_s(color_vec_y));
|
|
|
|
rgbo_vector = compute_rgbo_vector(rgba_weight_sum, weight_weight_sum, rgbq_sum, psum);
|
|
|
|
// We can get a failure due to the use of a singular (non-invertible) matrix
|
|
// If it failed, compute rgbo_vectors[] with a different method ...
|
|
if (astc::isnan(dot_s(rgbo_vector, rgbo_vector)))
|
|
{
|
|
vfloat4 v0 = ep.endpt0[0];
|
|
vfloat4 v1 = ep.endpt1[0];
|
|
|
|
float avgdif = hadd_rgb_s(v1 - v0) * (1.0f / 3.0f);
|
|
avgdif = astc::max(avgdif, 0.0f);
|
|
|
|
vfloat4 avg = (v0 + v1) * 0.5f;
|
|
vfloat4 ep0 = avg - vfloat4(avgdif) * 0.5f;
|
|
|
|
rgbo_vector = vfloat4(ep0.lane<0>(), ep0.lane<1>(), ep0.lane<2>(), avgdif);
|
|
}
|
|
}
|
|
}
|
|
|
|
#endif
|