// SPDX-License-Identifier: Apache-2.0
// ----------------------------------------------------------------------------
// Copyright 2011-2021 Arm Limited
//
// 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.
// ----------------------------------------------------------------------------
#if !defined(ASTCENC_DECOMPRESS_ONLY)
/**
* @brief Functions to compress a symbolic block.
*/
#include "astcenc_internal.h"
#include "astcenc_diagnostic_trace.h"
#include <cassert>
/**
* @brief Merge two planes of endpoints into a single vector.
*
* @param ep_plane1 The endpoints for plane 1.
* @param ep_plane2 The endpoints for plane 2.
* @param component_plane2 The color component for plane 2.
* @param[out] result The merged output.
*/
static void merge_endpoints(
const endpoints& ep_plane1,
const endpoints& ep_plane2,
unsigned int component_plane2,
endpoints& result
) {
unsigned int partition_count = ep_plane1.partition_count;
vmask4 sep_mask = vint4::lane_id() == vint4(component_plane2);
result.partition_count = partition_count;
promise(partition_count > 0);
for (unsigned int i = 0; i < partition_count; i++)
{
result.endpt0[i] = select(ep_plane1.endpt0[i], ep_plane2.endpt0[i], sep_mask);
result.endpt1[i] = select(ep_plane1.endpt1[i], ep_plane2.endpt1[i], sep_mask);
}
}
/**
* @brief Attempt to improve weights given a chosen configuration.
*
* Given a fixed weight grid decimation and weight value quantization, iterate over all weights (per
* partition and per plane) and attempt to improve image quality by moving each weight up by one or
* down by one quantization step.
*
* @param decode_mode The decode mode (LDR, HDR).
* @param bsd The block size information.
* @param blk The image block color data to compress.
* @param ewb The image block weighted error data.
* @param[out] scb The symbolic compressed block output.
* @param[out] dec_weights_quant_pvalue_plane1 The weights for plane 1.
* @param[out] dec_weights_quant_pvalue_plane2 The weights for plane 2, or @c nullptr if 1 plane.
*/
static bool realign_weights(
astcenc_profile decode_mode,
const block_size_descriptor& bsd,
const image_block& blk,
const error_weight_block& ewb,
symbolic_compressed_block& scb,
uint8_t* dec_weights_quant_pvalue_plane1,
uint8_t* dec_weights_quant_pvalue_plane2
) {
// Get the partition descriptor
unsigned int partition_count = scb.partition_count;
const auto& pi = bsd.get_partition_info(partition_count, scb.partition_index);
// Get the quantization table
const block_mode& bm = bsd.get_block_mode(scb.block_mode);
unsigned int weight_quant_level = bm.quant_mode;
const quantization_and_transfer_table *qat = &(quant_and_xfer_tables[weight_quant_level]);
// Get the decimation table
const decimation_info& di = bsd.get_decimation_info(bm.decimation_mode);
unsigned int weight_count = di.weight_count;
unsigned int max_plane = bm.is_dual_plane;
int plane2_component = bm.is_dual_plane ? scb.plane2_component : -1;
vmask4 plane_mask = vint4::lane_id() == vint4(plane2_component);
// Decode the color endpoints
bool rgb_hdr;
bool alpha_hdr;
vint4 endpnt0[BLOCK_MAX_PARTITIONS];
vint4 endpnt1[BLOCK_MAX_PARTITIONS];
vfloat4 endpnt0f[BLOCK_MAX_PARTITIONS];
vfloat4 offset[BLOCK_MAX_PARTITIONS];
promise(partition_count > 0);
promise(weight_count > 0);
for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
{
unpack_color_endpoints(decode_mode,
scb.color_formats[pa_idx],
scb.get_color_quant_mode(),
scb.color_values[pa_idx],
rgb_hdr, alpha_hdr,
endpnt0[pa_idx],
endpnt1[pa_idx]);
}
uint8_t uq_pl_weights[BLOCK_MAX_WEIGHTS];
uint8_t* dec_weights_quant_pvalue = dec_weights_quant_pvalue_plane1;
bool adjustments = false;
// For each plane and partition ...
for (unsigned int pl_idx = 0; pl_idx <= max_plane; pl_idx++)
{
for (unsigned int pa_idx = 0; pa_idx < partition_count; pa_idx++)
{
// Compute the endpoint delta for all components in current plane
vint4 epd = endpnt1[pa_idx] - endpnt0[pa_idx];
epd = select(epd, vint4::zero(), plane_mask);
endpnt0f[pa_idx] = int_to_float(endpnt0[pa_idx]);
offset[pa_idx] = int_to_float(epd) * (1.0f / 64.0f);
}
// Create an unquantized weight grid for this decimation level
for (unsigned int we_idx = 0; we_idx < weight_count; we_idx++)
{
uq_pl_weights[we_idx] = qat->unquantized_value[dec_weights_quant_pvalue[we_idx]];
}
// For each weight compute previous, current, and next errors
for (unsigned int we_idx = 0; we_idx < weight_count; we_idx++)
{
unsigned int uqw = uq_pl_weights[we_idx];
uint32_t prev_and_next = qat->prev_next_values[uqw];
unsigned int prev_wt_uq = prev_and_next & 0xFF;
unsigned int next_wt_uq = (prev_and_next >> 8) & 0xFF;
int uqw_next_dif = next_wt_uq - uqw;
int uqw_prev_dif = prev_wt_uq - uqw;
float current_error = 0.0f;
float up_error = 0.0f;
float down_error = 0.0f;
// Interpolate the colors to create the diffs
unsigned int texels_to_evaluate = di.weight_texel_count[we_idx];
promise(texels_to_evaluate > 0);
for (unsigned int te_idx = 0; te_idx < texels_to_evaluate; te_idx++)
{
unsigned int texel = di.weight_texel[te_idx][we_idx];
const uint8_t *texel_weights = di.texel_weights_texel[we_idx][te_idx];
const float *texel_weights_float = di.texel_weights_float_texel[we_idx][te_idx];
float twf0 = texel_weights_float[0];
float weight_base = static_cast<float>(uqw) * twf0;
// Don't interpolate filtered weights for a 1:1 weight grid
if (weight_count != bsd.texel_count)
{
weight_base =
(( weight_base
+ static_cast<float>(uq_pl_weights[texel_weights[1]]) * texel_weights_float[1])
+ (static_cast<float>(uq_pl_weights[texel_weights[2]]) * texel_weights_float[2]
+ static_cast<float>(uq_pl_weights[texel_weights[3]]) * texel_weights_float[3]));
}
unsigned int partition = pi.partition_of_texel[texel];
weight_base = weight_base + 0.5f;
float plane_weight = astc::flt_rd(weight_base);
float plane_up_weight = astc::flt_rd(weight_base + static_cast<float>(uqw_next_dif) * twf0) - plane_weight;
float plane_down_weight = astc::flt_rd(weight_base + static_cast<float>(uqw_prev_dif) * twf0) - plane_weight;
vfloat4 color_offset = offset[partition];
vfloat4 color_base = endpnt0f[partition];
vfloat4 color = color_base + color_offset * plane_weight;
vfloat4 origcolor = blk.texel(texel);
vfloat4 error_weight = ewb.error_weights[texel];
vfloat4 colordiff = color - origcolor;
vfloat4 color_up_diff = colordiff + color_offset * plane_up_weight;
vfloat4 color_down_diff = colordiff + color_offset * plane_down_weight;
current_error += dot_s(colordiff * colordiff, error_weight);
up_error += dot_s(color_up_diff * color_up_diff, error_weight);
down_error += dot_s(color_down_diff * color_down_diff, error_weight);
}
// Check if the prev or next error is better, and if so use it
if ((up_error < current_error) && (up_error < down_error))
{
uq_pl_weights[we_idx] = static_cast<uint8_t>(next_wt_uq);
dec_weights_quant_pvalue[we_idx] = (uint8_t)((prev_and_next >> 24) & 0xFF);
adjustments = true;
}
else if (down_error < current_error)
{
uq_pl_weights[we_idx] = static_cast<uint8_t>(prev_wt_uq);
dec_weights_quant_pvalue[we_idx] = (uint8_t)((prev_and_next >> 16) & 0xFF);
adjustments = true;
}
}
// Prepare iteration for plane 2
dec_weights_quant_pvalue = dec_weights_quant_pvalue_plane2;
plane_mask = ~plane_mask;
}
return adjustments;
}
/**
* @brief Compress a block using a chosen partitioning and 1 plane of weights.
*
* @param config The compressor configuration.
* @param bsd The block size information.
* @param blk The image block color data to compress.
* @param ewb The image block weighted error data.
* @param only_always True if we only use "always" percentile block modes.
* @param tune_errorval_threshold The error value threshold.
* @param partition_count The partition count.
* @param partition_index The partition index if @c partition_count is 2-4.
* @param[out] scb The symbolic compressed block output.
* @param[out] tmpbuf The quantized weights for plane 1.
*/
static float compress_symbolic_block_for_partition_1plane(
const astcenc_config& config,
const block_size_descriptor& bsd,
const image_block& blk,
const error_weight_block& ewb,
bool only_always,
float tune_errorval_threshold,
unsigned int partition_count,
unsigned int partition_index,
symbolic_compressed_block& scb,
compression_working_buffers& tmpbuf
) {
promise(partition_count > 0);
promise(config.tune_candidate_limit > 0);
promise(config.tune_refinement_limit > 0);
promise(bsd.decimation_mode_count > 0);
static const int free_bits_for_partition_count[5] {
0, 115 - 4, 111 - 4 - PARTITION_INDEX_BITS, 108 - 4 - PARTITION_INDEX_BITS, 105 - 4 - PARTITION_INDEX_BITS
};
const auto& pi = bsd.get_partition_info(partition_count, partition_index);
// Compute ideal weights and endpoint colors, with no quantization or decimation
endpoints_and_weights& ei = tmpbuf.ei1;
endpoints_and_weights *eix = tmpbuf.eix1;
compute_ideal_colors_and_weights_1plane(bsd, blk, ewb, pi, ei);
// Compute ideal weights and endpoint colors for every decimation
float *dec_weights_ideal_value = tmpbuf.dec_weights_ideal_value;
float *dec_weights_ideal_sig = tmpbuf.dec_weights_ideal_sig;
float *dec_weights_quant_uvalue = tmpbuf.dec_weights_quant_uvalue;
uint8_t *dec_weights_quant_pvalue = tmpbuf.dec_weights_quant_pvalue;
// For each decimation mode, compute an ideal set of weights with no quantization
unsigned int max_decimation_modes = only_always ? bsd.always_decimation_mode_count
: bsd.decimation_mode_count;
promise(max_decimation_modes > 0);
for (unsigned int i = 0; i < max_decimation_modes; i++)
{
const auto& dm = bsd.get_decimation_mode(i);
if (dm.maxprec_1plane < 0 || !dm.percentile_hit)
{
continue;
}
const auto& di = bsd.get_decimation_info(i);
compute_ideal_weights_for_decimation(
ei,
eix[i],
di,
dec_weights_ideal_value + i * BLOCK_MAX_WEIGHTS,
dec_weights_ideal_sig + i * BLOCK_MAX_WEIGHTS);
}
// Compute maximum colors for the endpoints and ideal weights, then for each endpoint and ideal
// weight pair, compute the smallest weight that will result in a color value greater than 1
vfloat4 min_ep(10.0f);
for (unsigned int i = 0; i < partition_count; i++)
{
vfloat4 ep = (vfloat4(1.0f) - ei.ep.endpt0[i]) / (ei.ep.endpt1[i] - ei.ep.endpt0[i]);
vmask4 use_ep = (ep > vfloat4(0.5f)) & (ep < min_ep);
min_ep = select(min_ep, ep, use_ep);
}
float min_wt_cutoff = hmin_s(min_ep);
// For each mode, use the angular method to compute a shift
float weight_low_value[WEIGHTS_MAX_BLOCK_MODES];
float weight_high_value[WEIGHTS_MAX_BLOCK_MODES];
compute_angular_endpoints_1plane(
config.tune_low_weight_count_limit,
only_always, bsd,
dec_weights_ideal_value, dec_weights_ideal_sig,
weight_low_value, weight_high_value);
// For each mode (which specifies a decimation and a quantization):
// * Compute number of bits needed for the quantized weights
// * Generate an optimized set of quantized weights
// * Compute quantization errors for the mode
int qwt_bitcounts[WEIGHTS_MAX_BLOCK_MODES];
float qwt_errors[WEIGHTS_MAX_BLOCK_MODES];
for (unsigned int i = 0; i < bsd.block_mode_count; ++i)
{
qwt_errors[i] = 1e38f;
}
unsigned int max_block_modes = only_always ? bsd.always_block_mode_count
: bsd.block_mode_count;
promise(max_block_modes > 0);
for (unsigned int i = 0; i < max_block_modes; ++i)
{
const block_mode& bm = bsd.block_modes[i];
if (bm.is_dual_plane || !bm.percentile_hit)
{
continue;
}
if (weight_high_value[i] > 1.02f * min_wt_cutoff)
{
weight_high_value[i] = 1.0f;
}
int decimation_mode = bm.decimation_mode;
const auto& di = bsd.get_decimation_info(decimation_mode);
// Compute weight bitcount for the mode
unsigned int bits_used_by_weights = get_ise_sequence_bitcount(
di.weight_count,
bm.get_weight_quant_mode());
int bitcount = free_bits_for_partition_count[partition_count] - bits_used_by_weights;
if (bitcount <= 0)
{
continue;
}
qwt_bitcounts[i] = bitcount;
// Generate the optimized set of weights for the weight mode
compute_quantized_weights_for_decimation(
di,
weight_low_value[i], weight_high_value[i],
dec_weights_ideal_value + BLOCK_MAX_WEIGHTS * decimation_mode,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i,
dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * i,
bm.get_weight_quant_mode());
// Compute weight quantization errors for the block mode
qwt_errors[i] = compute_error_of_weight_set_1plane(
eix[decimation_mode],
di,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i);
}
// Decide the optimal combination of color endpoint encodings and weight encodings
int partition_format_specifiers[TUNE_MAX_TRIAL_CANDIDATES][BLOCK_MAX_PARTITIONS];
int block_mode_index[TUNE_MAX_TRIAL_CANDIDATES];
quant_method color_quant_level[TUNE_MAX_TRIAL_CANDIDATES];
quant_method color_quant_level_mod[TUNE_MAX_TRIAL_CANDIDATES];
unsigned int candidate_count = compute_ideal_endpoint_formats(
bsd, pi, blk, ewb, ei.ep, qwt_bitcounts, qwt_errors,
config.tune_candidate_limit, partition_format_specifiers, block_mode_index,
color_quant_level, color_quant_level_mod);
// Iterate over the N believed-to-be-best modes to find out which one is actually best
float best_errorval_in_mode = ERROR_CALC_DEFAULT;
float best_errorval_in_scb = scb.errorval;
for (unsigned int i = 0; i < candidate_count; i++)
{
TRACE_NODE(node0, "candidate");
const int bm_packed_index = block_mode_index[i];
assert(bm_packed_index >= 0 && bm_packed_index < (int)bsd.block_mode_count);
const block_mode& qw_bm = bsd.block_modes[bm_packed_index];
int decimation_mode = qw_bm.decimation_mode;
int weight_quant_mode = qw_bm.quant_mode;
const auto& di = bsd.get_decimation_info(decimation_mode);
promise(di.weight_count > 0);
trace_add_data("weight_x", di.weight_x);
trace_add_data("weight_y", di.weight_y);
trace_add_data("weight_z", di.weight_z);
trace_add_data("weight_quant", weight_quant_mode);
// Recompute the ideal color endpoints before storing them
vfloat4 rgbs_colors[BLOCK_MAX_PARTITIONS];
vfloat4 rgbo_colors[BLOCK_MAX_PARTITIONS];
symbolic_compressed_block workscb;
uint8_t* u8_weight_src = dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * bm_packed_index;
for (unsigned int j = 0; j < di.weight_count; j++)
{
workscb.weights[j] = u8_weight_src[j];
}
for (unsigned int l = 0; l < config.tune_refinement_limit; l++)
{
recompute_ideal_colors_1plane(
blk, ewb, pi, di,
weight_quant_mode, workscb.weights,
eix[decimation_mode].ep, rgbs_colors, rgbo_colors);
// Quantize the chosen color
for (unsigned int j = 0; j < partition_count; j++)
{
workscb.color_formats[j] = pack_color_endpoints(
eix[decimation_mode].ep.endpt0[j],
eix[decimation_mode].ep.endpt1[j],
rgbs_colors[j],
rgbo_colors[j],
partition_format_specifiers[i][j],
workscb.color_values[j],
(quant_method)color_quant_level[i]);
}
// If all the color endpoint modes are the same, we get a few more bits to store colors;
// let's see if we can take advantage of this: requantize all the colors and see if the
// endpoint modes remain the same.
workscb.color_formats_matched = 0;
if ((partition_count >= 2 && workscb.color_formats[0] == workscb.color_formats[1]
&& color_quant_level[i] != color_quant_level_mod[i])
&& (partition_count == 2 || (workscb.color_formats[0] == workscb.color_formats[2]
&& (partition_count == 3 || (workscb.color_formats[0] == workscb.color_formats[3])))))
{
uint8_t colorvals[BLOCK_MAX_PARTITIONS][12];
uint8_t color_formats_mod[BLOCK_MAX_PARTITIONS] { 0 };
for (unsigned int j = 0; j < partition_count; j++)
{
color_formats_mod[j] = pack_color_endpoints(
eix[decimation_mode].ep.endpt0[j],
eix[decimation_mode].ep.endpt1[j],
rgbs_colors[j],
rgbo_colors[j],
partition_format_specifiers[i][j],
colorvals[j],
(quant_method)color_quant_level_mod[i]);
}
if (color_formats_mod[0] == color_formats_mod[1]
&& (partition_count == 2 || (color_formats_mod[0] == color_formats_mod[2]
&& (partition_count == 3 || (color_formats_mod[0] == color_formats_mod[3])))))
{
workscb.color_formats_matched = 1;
for (unsigned int j = 0; j < BLOCK_MAX_PARTITIONS; j++)
{
for (unsigned int k = 0; k < 8; k++)
{
workscb.color_values[j][k] = colorvals[j][k];
}
workscb.color_formats[j] = color_formats_mod[j];
}
}
}
// Store header fields
workscb.partition_count = static_cast<uint8_t>(partition_count);
workscb.partition_index = static_cast<uint16_t>(partition_index);
workscb.plane2_component = -1;
workscb.quant_mode = workscb.color_formats_matched ? color_quant_level_mod[i] : color_quant_level[i];
workscb.block_mode = qw_bm.mode_index;
workscb.block_type = SYM_BTYPE_NONCONST;
if (workscb.quant_mode < QUANT_6)
{
workscb.block_type = SYM_BTYPE_ERROR;
}
// Pre-realign test
if (l == 0)
{
float errorval = compute_symbolic_block_difference(config, bsd, workscb, blk, ewb);
if (errorval == -ERROR_CALC_DEFAULT)
{
errorval = -errorval;
workscb.block_type = SYM_BTYPE_ERROR;
}
trace_add_data("error_prerealign", errorval);
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
// Average refinement improvement is 3.5% per iteration (allow 5%), but the first
// iteration can help more so we give it a extra 10% leeway. Use this knowledge to
// drive a heuristic to skip blocks that are unlikely to catch up with the best
// block we have already.
unsigned int iters_remaining = config.tune_refinement_limit - l;
float threshold = (0.05f * static_cast<float>(iters_remaining)) + 1.1f;
if (errorval > (threshold * best_errorval_in_scb))
{
break;
}
if (errorval < best_errorval_in_scb)
{
best_errorval_in_scb = errorval;
workscb.errorval = errorval;
scb = workscb;
if (errorval < tune_errorval_threshold)
{
// Skip remaining candidates - this is "good enough"
i = candidate_count;
break;
}
}
}
// Perform a final pass over the weights to try to improve them.
bool adjustments = realign_weights(
config.profile, bsd, blk, ewb, workscb,
workscb.weights, nullptr);
// Post-realign test
float errorval = compute_symbolic_block_difference(config, bsd, workscb, blk, ewb);
if (errorval == -ERROR_CALC_DEFAULT)
{
errorval = -errorval;
workscb.block_type = SYM_BTYPE_ERROR;
}
trace_add_data("error_postrealign", errorval);
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
// Average refinement improvement is 3.5% per iteration, so skip blocks that are
// unlikely to catch up with the best block we have already. Assume a 5% per step to
// give benefit of the doubt ...
unsigned int iters_remaining = config.tune_refinement_limit - 1 - l;
float threshold = (0.05f * static_cast<float>(iters_remaining)) + 1.0f;
if (errorval > (threshold * best_errorval_in_scb))
{
break;
}
if (errorval < best_errorval_in_scb)
{
best_errorval_in_scb = errorval;
workscb.errorval = errorval;
scb = workscb;
if (errorval < tune_errorval_threshold)
{
// Skip remaining candidates - this is "good enough"
i = candidate_count;
break;
}
}
if (!adjustments)
{
break;
}
}
}
return best_errorval_in_mode;
}
/**
* @brief Compress a block using a chosen partitioning and 2 planes of weights.
*
* @param config The compressor configuration.
* @param bsd The block size information.
* @param blk The image block color data to compress.
* @param ewb The image block weighted error data.
* @param tune_errorval_threshold The error value threshold.
* @param plane2_component The component index for the second plane of weights.
* @param[out] scb The symbolic compressed block output.
* @param[out] tmpbuf The quantized weights for plane 1.
*/
static float compress_symbolic_block_for_partition_2planes(
const astcenc_config& config,
const block_size_descriptor& bsd,
const image_block& blk,
const error_weight_block& ewb,
float tune_errorval_threshold,
unsigned int plane2_component,
symbolic_compressed_block& scb,
compression_working_buffers& tmpbuf
) {
promise(config.tune_candidate_limit > 0);
promise(config.tune_refinement_limit > 0);
promise(bsd.decimation_mode_count > 0);
// Compute ideal weights and endpoint colors, with no quantization or decimation
endpoints_and_weights& ei1 = tmpbuf.ei1;
endpoints_and_weights& ei2 = tmpbuf.ei2;
endpoints_and_weights* eix1 = tmpbuf.eix1;
endpoints_and_weights* eix2 = tmpbuf.eix2;
compute_ideal_colors_and_weights_2planes(bsd, blk, ewb, plane2_component, ei1, ei2);
// Compute ideal weights and endpoint colors for every decimation
float *dec_weights_ideal_value = tmpbuf.dec_weights_ideal_value;
float *dec_weights_ideal_sig = tmpbuf.dec_weights_ideal_sig;
float *dec_weights_quant_uvalue = tmpbuf.dec_weights_quant_uvalue;
uint8_t *dec_weights_quant_pvalue = tmpbuf.dec_weights_quant_pvalue;
// For each decimation mode, compute an ideal set of weights with no quantization
for (unsigned int i = 0; i < bsd.decimation_mode_count; i++)
{
const auto& dm = bsd.get_decimation_mode(i);
if (dm.maxprec_2planes < 0 || !dm.percentile_hit)
{
continue;
}
const auto& di = bsd.get_decimation_info(i);
compute_ideal_weights_for_decimation(
ei1,
eix1[i],
di,
dec_weights_ideal_value + i * BLOCK_MAX_WEIGHTS,
dec_weights_ideal_sig + i * BLOCK_MAX_WEIGHTS);
compute_ideal_weights_for_decimation(
ei2,
eix2[i],
di,
dec_weights_ideal_value + i * BLOCK_MAX_WEIGHTS + WEIGHTS_PLANE2_OFFSET,
dec_weights_ideal_sig + i * BLOCK_MAX_WEIGHTS + WEIGHTS_PLANE2_OFFSET);
}
// Compute maximum colors for the endpoints and ideal weights, then for each endpoint and ideal
// weight pair, compute the smallest weight that will result in a color value greater than 1
vfloat4 min_ep1(10.0f);
vfloat4 min_ep2(10.0f);
vfloat4 ep1 = (vfloat4(1.0f) - ei1.ep.endpt0[0]) / (ei1.ep.endpt1[0] - ei1.ep.endpt0[0]);
vmask4 use_ep1 = (ep1 > vfloat4(0.5f)) & (ep1 < min_ep1);
min_ep1 = select(min_ep1, ep1, use_ep1);
vfloat4 ep2 = (vfloat4(1.0f) - ei2.ep.endpt0[0]) / (ei2.ep.endpt1[0] - ei2.ep.endpt0[0]);
vmask4 use_ep2 = (ep2 > vfloat4(0.5f)) & (ep2 < min_ep2);
min_ep2 = select(min_ep2, ep2, use_ep2);
vfloat4 err_max(ERROR_CALC_DEFAULT);
vmask4 err_mask = vint4::lane_id() == vint4(plane2_component);
// Set the plane2 component to max error in ep1
min_ep1 = select(min_ep1, err_max, err_mask);
float min_wt_cutoff1 = hmin_s(min_ep1);
// Set the minwt2 to the plane2 component min in ep2
float min_wt_cutoff2 = hmin_s(select(err_max, min_ep2, err_mask));
float weight_low_value1[WEIGHTS_MAX_BLOCK_MODES];
float weight_high_value1[WEIGHTS_MAX_BLOCK_MODES];
float weight_low_value2[WEIGHTS_MAX_BLOCK_MODES];
float weight_high_value2[WEIGHTS_MAX_BLOCK_MODES];
compute_angular_endpoints_2planes(
config.tune_low_weight_count_limit,
bsd, dec_weights_ideal_value, dec_weights_ideal_sig,
weight_low_value1, weight_high_value1,
weight_low_value2, weight_high_value2);
// For each mode (which specifies a decimation and a quantization):
// * Compute number of bits needed for the quantized weights
// * Generate an optimized set of quantized weights
// * Compute quantization errors for the mode
int qwt_bitcounts[WEIGHTS_MAX_BLOCK_MODES];
float qwt_errors[WEIGHTS_MAX_BLOCK_MODES];
for (unsigned int i = 0; i < bsd.block_mode_count; ++i)
{
const block_mode& bm = bsd.block_modes[i];
if (!bm.is_dual_plane || !bm.percentile_hit)
{
qwt_errors[i] = 1e38f;
continue;
}
unsigned int decimation_mode = bm.decimation_mode;
const auto& di = bsd.get_decimation_info(decimation_mode);
if (weight_high_value1[i] > 1.02f * min_wt_cutoff1)
{
weight_high_value1[i] = 1.0f;
}
if (weight_high_value2[i] > 1.02f * min_wt_cutoff2)
{
weight_high_value2[i] = 1.0f;
}
// Compute weight bitcount for the mode
unsigned int bits_used_by_weights = get_ise_sequence_bitcount(
2 * di.weight_count,
bm.get_weight_quant_mode());
int bitcount = 113 - 4 - bits_used_by_weights;
if (bitcount <= 0)
{
continue;
}
qwt_bitcounts[i] = bitcount;
// Generate the optimized set of weights for the mode
compute_quantized_weights_for_decimation(
di,
weight_low_value1[i],
weight_high_value1[i],
dec_weights_ideal_value + BLOCK_MAX_WEIGHTS * decimation_mode,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i,
dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * i,
bm.get_weight_quant_mode());
compute_quantized_weights_for_decimation(
di,
weight_low_value2[i],
weight_high_value2[i],
dec_weights_ideal_value + BLOCK_MAX_WEIGHTS * decimation_mode + WEIGHTS_PLANE2_OFFSET,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i + WEIGHTS_PLANE2_OFFSET,
dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * i + WEIGHTS_PLANE2_OFFSET,
bm.get_weight_quant_mode());
// Compute weight quantization errors for the block mode
qwt_errors[i] = compute_error_of_weight_set_2planes(
eix1[decimation_mode],
eix2[decimation_mode],
di,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i,
dec_weights_quant_uvalue + BLOCK_MAX_WEIGHTS * i + WEIGHTS_PLANE2_OFFSET);
}
// Decide the optimal combination of color endpoint encodings and weight encodings
int partition_format_specifiers[TUNE_MAX_TRIAL_CANDIDATES][BLOCK_MAX_PARTITIONS];
int block_mode_index[TUNE_MAX_TRIAL_CANDIDATES];
quant_method color_quant_level[TUNE_MAX_TRIAL_CANDIDATES];
quant_method color_quant_level_mod[TUNE_MAX_TRIAL_CANDIDATES];
endpoints epm;
merge_endpoints(ei1.ep, ei2.ep, plane2_component, epm);
const auto& pi = bsd.get_partition_info(1, 0);
unsigned int candidate_count = compute_ideal_endpoint_formats(
bsd, pi, blk, ewb, epm, qwt_bitcounts, qwt_errors,
config.tune_candidate_limit, partition_format_specifiers, block_mode_index,
color_quant_level, color_quant_level_mod);
// Iterate over the N believed-to-be-best modes to find out which one is actually best
float best_errorval_in_mode = ERROR_CALC_DEFAULT;
float best_errorval_in_scb = scb.errorval;
for (unsigned int i = 0; i < candidate_count; i++)
{
TRACE_NODE(node0, "candidate");
const int bm_packed_index = block_mode_index[i];
assert(bm_packed_index >= 0 && bm_packed_index < (int)bsd.block_mode_count);
const block_mode& qw_bm = bsd.block_modes[bm_packed_index];
int decimation_mode = qw_bm.decimation_mode;
int weight_quant_mode = qw_bm.quant_mode;
const auto& di = bsd.get_decimation_info(decimation_mode);
promise(di.weight_count > 0);
trace_add_data("weight_x", di.weight_x);
trace_add_data("weight_y", di.weight_y);
trace_add_data("weight_z", di.weight_z);
trace_add_data("weight_quant", weight_quant_mode);
// Recompute the ideal color endpoints before storing them.
merge_endpoints(eix1[decimation_mode].ep, eix2[decimation_mode].ep, plane2_component, epm);
vfloat4 rgbs_color;
vfloat4 rgbo_color;
symbolic_compressed_block workscb;
uint8_t* u8_weight1_src = dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * bm_packed_index;
uint8_t* u8_weight2_src = dec_weights_quant_pvalue + BLOCK_MAX_WEIGHTS * bm_packed_index + WEIGHTS_PLANE2_OFFSET;
for (int j = 0; j < di.weight_count; j++)
{
workscb.weights[j] = u8_weight1_src[j];
workscb.weights[j + WEIGHTS_PLANE2_OFFSET] = u8_weight2_src[j];
}
for (unsigned int l = 0; l < config.tune_refinement_limit; l++)
{
recompute_ideal_colors_2planes(
blk, ewb, bsd, di,
weight_quant_mode, workscb.weights, workscb.weights + WEIGHTS_PLANE2_OFFSET,
epm, rgbs_color, rgbo_color, plane2_component);
// Quantize the chosen color
workscb.color_formats[0] = pack_color_endpoints(
epm.endpt0[0],
epm.endpt1[0],
rgbs_color, rgbo_color,
partition_format_specifiers[i][0],
workscb.color_values[0],
(quant_method)color_quant_level[i]);
// Store header fields
workscb.partition_count = 1;
workscb.partition_index = 0;
workscb.quant_mode = color_quant_level[i];
workscb.color_formats_matched = 0;
workscb.block_mode = qw_bm.mode_index;
workscb.plane2_component = static_cast<int8_t>(plane2_component);
workscb.block_type = SYM_BTYPE_NONCONST;
if (workscb.quant_mode < 4)
{
workscb.block_type = SYM_BTYPE_ERROR;
}
// Pre-realign test
if (l == 0)
{
float errorval = compute_symbolic_block_difference(config, bsd, workscb, blk, ewb);
if (errorval == -ERROR_CALC_DEFAULT)
{
errorval = -errorval;
workscb.block_type = SYM_BTYPE_ERROR;
}
trace_add_data("error_prerealign", errorval);
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
// Average refinement improvement is 3.5% per iteration (allow 5%), but the first
// iteration can help more so we give it a extra 10% leeway. Use this knowledge to
// drive a heuristic to skip blocks that are unlikely to catch up with the best
// block we have already.
unsigned int iters_remaining = config.tune_refinement_limit - l;
float threshold = (0.05f * static_cast<float>(iters_remaining)) + 1.1f;
if (errorval > (threshold * best_errorval_in_scb))
{
break;
}
if (errorval < best_errorval_in_scb)
{
best_errorval_in_scb = errorval;
workscb.errorval = errorval;
scb = workscb;
if (errorval < tune_errorval_threshold)
{
// Skip remaining candidates - this is "good enough"
i = candidate_count;
break;
}
}
}
// Perform a final pass over the weights to try to improve them
bool adjustments = realign_weights(
config.profile, bsd, blk, ewb, workscb,
workscb.weights, workscb.weights + WEIGHTS_PLANE2_OFFSET);
// Post-realign test
float errorval = compute_symbolic_block_difference(config, bsd, workscb, blk, ewb);
if (errorval == -ERROR_CALC_DEFAULT)
{
errorval = -errorval;
workscb.block_type = SYM_BTYPE_ERROR;
}
trace_add_data("error_postrealign", errorval);
best_errorval_in_mode = astc::min(errorval, best_errorval_in_mode);
// Average refinement improvement is 3.5% per iteration, so skip blocks that are
// unlikely to catch up with the best block we have already. Assume a 5% per step to
// give benefit of the doubt ...
unsigned int iters_remaining = config.tune_refinement_limit - 1 - l;
float threshold = (0.05f * static_cast<float>(iters_remaining)) + 1.0f;
if (errorval > (threshold * best_errorval_in_scb))
{
break;
}
if (errorval < best_errorval_in_scb)
{
best_errorval_in_scb = errorval;
workscb.errorval = errorval;
scb = workscb;
if (errorval < tune_errorval_threshold)
{
// Skip remaining candidates - this is "good enough"
i = candidate_count;
break;
}
}
if (!adjustments)
{
break;
}
}
}
return best_errorval_in_mode;
}
/**
* @brief Create a per-texel expansion of the error weights for deblocking.
*
* Deblockign works by assigning a higher error weight to blocks the closer they are the edge of the
* block. The encourages the compressor to keep the periphery colors more accurate, which can help
* reduce block artifacts when compressing gradients.
*
* @param[in,out] ctx The context containing both deblog memory and config.
*/
void expand_deblock_weights(
astcenc_context& ctx
) {
unsigned int xdim = ctx.config.block_x;
unsigned int ydim = ctx.config.block_y;
unsigned int zdim = ctx.config.block_z;
float centerpos_x = static_cast<float>(xdim - 1) * 0.5f;
float centerpos_y = static_cast<float>(ydim - 1) * 0.5f;
float centerpos_z = static_cast<float>(zdim - 1) * 0.5f;
float *bef = ctx.deblock_weights;
for (unsigned int z = 0; z < zdim; z++)
{
for (unsigned int y = 0; y < ydim; y++)
{
for (unsigned int x = 0; x < xdim; x++)
{
float xdif = (static_cast<float>(x) - centerpos_x) / static_cast<float>(xdim);
float ydif = (static_cast<float>(y) - centerpos_y) / static_cast<float>(ydim);
float zdif = (static_cast<float>(z) - centerpos_z) / static_cast<float>(zdim);
float wdif = 0.36f;
float dist = astc::sqrt(xdif * xdif + ydif * ydif + zdif * zdif + wdif * wdif);
*bef = astc::pow(dist, ctx.config.b_deblock_weight);
bef++;
}
}
}
}
/**
* @brief Create a per-texel and per-channel expansion of the error weights.
*
* This approach creates relatively large error block tables, but it allows a very flexible level of
* control over how specific texels and channels are prioritized by the compressor.
*
* @param ctx The compressor context and configuration.
* @param image The input image information.
* @param bsd The block size information.
* @param blk The image block color data to compress.
* @param[out] ewb The image block weighted error data.
*
* @return Return the total error weight sum for all texels and channels.
*/
static float prepare_error_weight_block(
const astcenc_context& ctx,
const astcenc_image& image,
const block_size_descriptor& bsd,
const image_block& blk,
error_weight_block& ewb
) {
unsigned int idx = 0;
bool any_mean_stdev_weight =
ctx.config.v_rgb_mean != 0.0f || ctx.config.v_rgb_stdev != 0.0f || \
ctx.config.v_a_mean != 0.0f || ctx.config.v_a_stdev != 0.0f;
vfloat4 color_weights(ctx.config.cw_r_weight,
ctx.config.cw_g_weight,
ctx.config.cw_b_weight,
ctx.config.cw_a_weight);
// This works because HDR is imposed globally at compression time
unsigned int rgb_lns = blk.rgb_lns[0];
unsigned int a_lns = blk.alpha_lns[0];
vint4 use_lns(rgb_lns, rgb_lns, rgb_lns, a_lns);
vmask4 lns_mask = use_lns != vint4::zero();
promise(bsd.xdim > 0);
promise(bsd.ydim > 0);
promise(bsd.zdim > 0);
for (unsigned int z = 0; z < bsd.zdim; z++)
{
for (unsigned int y = 0; y < bsd.ydim; y++)
{
for (unsigned int x = 0; x < bsd.xdim; x++)
{
unsigned int xpos = x + blk.xpos;
unsigned int ypos = y + blk.ypos;
unsigned int zpos = z + blk.zpos;
if (xpos >= image.dim_x || ypos >= image.dim_y || zpos >= image.dim_z)
{
ewb.error_weights[idx] = vfloat4(1e-11f);
}
else
{
vfloat4 derv(65535.0f);
// Compute derivative if we have any use of LNS
if (any(lns_mask))
{
vfloat4 data = blk.texel(idx);
vint4 datai = lns_to_sf16(float_to_int(data));
vfloat4 dataf = float16_to_float(datai);
dataf = max(dataf, 6e-5f);
vfloat4 data_lns1 = dataf * 1.05f;
data_lns1 = float_to_lns(data_lns1);
vfloat4 data_lns2 = dataf;
data_lns2 = float_to_lns(data_lns2);
vfloat4 divisor_lns = dataf * 0.05f;
// Clamp derivatives between 1/32 and 2^25
float lo = 1.0f / 32.0f;
float hi = 33554432.0f;
vfloat4 derv_lns = clamp(lo, hi, (data_lns1 - data_lns2) / divisor_lns);
derv = select(derv, derv_lns, lns_mask);
}
// Compute error weight
vfloat4 error_weight(ctx.config.v_rgb_base,
ctx.config.v_rgb_base,
ctx.config.v_rgb_base,
ctx.config.v_a_base);
unsigned int ydt = image.dim_x;
unsigned int zdt = image.dim_x * image.dim_y;
if (any_mean_stdev_weight)
{
vfloat4 avg = ctx.input_averages[zpos * zdt + ypos * ydt + xpos];
avg = max(avg, 6e-5f);
avg = avg * avg;
vfloat4 variance = ctx.input_variances[zpos * zdt + ypos * ydt + xpos];
variance = variance * variance;
float favg = hadd_rgb_s(avg) * (1.0f / 3.0f);
float fvar = hadd_rgb_s(variance) * (1.0f / 3.0f);
float mixing = ctx.config.v_rgba_mean_stdev_mix;
avg.set_lane<0>(favg * mixing + avg.lane<0>() * (1.0f - mixing));
avg.set_lane<1>(favg * mixing + avg.lane<1>() * (1.0f - mixing));
avg.set_lane<2>(favg * mixing + avg.lane<2>() * (1.0f - mixing));
variance.set_lane<0>(fvar * mixing + variance.lane<0>() * (1.0f - mixing));
variance.set_lane<1>(fvar * mixing + variance.lane<1>() * (1.0f - mixing));
variance.set_lane<2>(fvar * mixing + variance.lane<2>() * (1.0f - mixing));
vfloat4 stdev = sqrt(max(variance, 0.0f));
vfloat4 scalea(ctx.config.v_rgb_mean, ctx.config.v_rgb_mean, ctx.config.v_rgb_mean, ctx.config.v_a_mean);
avg = avg * scalea;
vfloat4 scales(ctx.config.v_rgb_stdev, ctx.config.v_rgb_stdev, ctx.config.v_rgb_stdev, ctx.config.v_a_stdev);
stdev = stdev * scales;
error_weight = error_weight + avg + stdev;
error_weight = 1.0f / error_weight;
}
if (ctx.config.flags & ASTCENC_FLG_MAP_NORMAL)
{
// Convert from 0 to 1 to -1 to +1 range.
float xN = ((blk.data_r[idx] * (1.0f / 65535.0f)) - 0.5f) * 2.0f;
float yN = ((blk.data_a[idx] * (1.0f / 65535.0f)) - 0.5f) * 2.0f;
float denom = 1.0f - xN * xN - yN * yN;
denom = astc::max(denom, 0.1f);
denom = 1.0f / denom;
error_weight.set_lane<0>(error_weight.lane<0>() * (1.0f + xN * xN * denom));
error_weight.set_lane<3>(error_weight.lane<3>() * (1.0f + yN * yN * denom));
}
if (ctx.config.flags & ASTCENC_FLG_USE_ALPHA_WEIGHT)
{
float alpha_scale;
if (ctx.config.a_scale_radius != 0)
{
alpha_scale = ctx.input_alpha_averages[zpos * zdt + ypos * ydt + xpos];
}
else
{
alpha_scale = blk.data_a[idx] * (1.0f / 65535.0f);
}
alpha_scale = astc::max(alpha_scale, 0.0001f);
alpha_scale *= alpha_scale;
error_weight.set_lane<0>(error_weight.lane<0>() * alpha_scale);
error_weight.set_lane<1>(error_weight.lane<1>() * alpha_scale);
error_weight.set_lane<2>(error_weight.lane<2>() * alpha_scale);
}
error_weight = error_weight * color_weights;
error_weight = error_weight * ctx.deblock_weights[idx];
// When we loaded the block to begin with, we applied a transfer function and
// computed the derivative of the transfer function. However, the error-weight
// computation so far is based on the original color values, not the
// transfer-function values. As such, we must multiply the error weights by the
// derivative of the inverse of the transfer function, which is equivalent to
// dividing by the derivative of the transfer function.
error_weight = error_weight / (derv * derv * 1e-10f);
ewb.error_weights[idx] = error_weight;
}
idx++;
}
}
}
// Small bias to avoid divide by zeros and NaN propagation later
vfloat4 texel_weight_sum(1e-17f);
vfloat4 error_weight_sum(1e-17f);
int texels_per_block = bsd.texel_count;
for (int i = 0; i < texels_per_block; i++)
{
texel_weight_sum += ewb.error_weights[i] * blk.texel(i);
error_weight_sum += ewb.error_weights[i];
float wr = ewb.error_weights[i].lane<0>();
float wg = ewb.error_weights[i].lane<1>();
float wb = ewb.error_weights[i].lane<2>();
float wa = ewb.error_weights[i].lane<3>();
ewb.texel_weight_r[i] = wr;
ewb.texel_weight_g[i] = wg;
ewb.texel_weight_b[i] = wb;
ewb.texel_weight_a[i] = wa;
ewb.texel_weight_rg[i] = (wr + wg) * 0.5f;
ewb.texel_weight_rb[i] = (wr + wb) * 0.5f;
ewb.texel_weight_gb[i] = (wg + wb) * 0.5f;
ewb.texel_weight_gba[i] = (wg + wb + wa) * 0.333333f;
ewb.texel_weight_rba[i] = (wr + wb + wa) * 0.333333f;
ewb.texel_weight_rga[i] = (wr + wg + wa) * 0.333333f;
ewb.texel_weight_rgb[i] = (wr + wg + wb) * 0.333333f;
ewb.texel_weight[i] = (wr + wg + wb + wa) * 0.25f;
}
ewb.block_error_weighted_rgba_sum = texel_weight_sum;
ewb.block_error_weight_sum = error_weight_sum;
return hadd_s(error_weight_sum);
}
/**
* @brief Determine the lowest cross-channel correlation factor.
*
* @param texels_per_block The number of texels in a block.
* @param blk The image block color data to compress.
* @param ewb The image block weighted error data.
*
* @return Return the lowest correlation factor.
*/
static float prepare_block_statistics(
int texels_per_block,
const image_block& blk,
const error_weight_block& ewb
) {
// Compute covariance matrix, as a collection of 10 scalars that form the upper-triangular row
// of the matrix. The matrix is symmetric, so this is all we need for this use case.
float rs = 0.0f;
float gs = 0.0f;
float bs = 0.0f;
float as = 0.0f;
float rr_var = 0.0f;
float gg_var = 0.0f;
float bb_var = 0.0f;
float aa_var = 0.0f;
float rg_cov = 0.0f;
float rb_cov = 0.0f;
float ra_cov = 0.0f;
float gb_cov = 0.0f;
float ga_cov = 0.0f;
float ba_cov = 0.0f;
float weight_sum = 0.0f;
promise(texels_per_block > 0);
for (int i = 0; i < texels_per_block; i++)
{
float weight = ewb.texel_weight[i];
assert(weight >= 0.0f);
weight_sum += weight;
float r = blk.data_r[i];
float g = blk.data_g[i];
float b = blk.data_b[i];
float a = blk.data_a[i];
float rw = r * weight;
rs += rw;
rr_var += r * rw;
rg_cov += g * rw;
rb_cov += b * rw;
ra_cov += a * rw;
float gw = g * weight;
gs += gw;
gg_var += g * gw;
gb_cov += b * gw;
ga_cov += a * gw;
float bw = b * weight;
bs += bw;
bb_var += b * bw;
ba_cov += a * bw;
float aw = a * weight;
as += aw;
aa_var += a * aw;
}
float rpt = 1.0f / astc::max(weight_sum, 1e-7f);
rr_var -= rs * (rs * rpt);
rg_cov -= gs * (rs * rpt);
rb_cov -= bs * (rs * rpt);
ra_cov -= as * (rs * rpt);
gg_var -= gs * (gs * rpt);
gb_cov -= bs * (gs * rpt);
ga_cov -= as * (gs * rpt);
bb_var -= bs * (bs * rpt);
ba_cov -= as * (bs * rpt);
aa_var -= as * (as * rpt);
rg_cov *= astc::rsqrt(astc::max(rr_var * gg_var, 1e-30f));
rb_cov *= astc::rsqrt(astc::max(rr_var * bb_var, 1e-30f));
ra_cov *= astc::rsqrt(astc::max(rr_var * aa_var, 1e-30f));
gb_cov *= astc::rsqrt(astc::max(gg_var * bb_var, 1e-30f));
ga_cov *= astc::rsqrt(astc::max(gg_var * aa_var, 1e-30f));
ba_cov *= astc::rsqrt(astc::max(bb_var * aa_var, 1e-30f));
if (astc::isnan(rg_cov)) rg_cov = 1.0f;
if (astc::isnan(rb_cov)) rb_cov = 1.0f;
if (astc::isnan(ra_cov)) ra_cov = 1.0f;
if (astc::isnan(gb_cov)) gb_cov = 1.0f;
if (astc::isnan(ga_cov)) ga_cov = 1.0f;
if (astc::isnan(ba_cov)) ba_cov = 1.0f;
float lowest_correlation = astc::min(fabsf(rg_cov), fabsf(rb_cov));
lowest_correlation = astc::min(lowest_correlation, fabsf(ra_cov));
lowest_correlation = astc::min(lowest_correlation, fabsf(gb_cov));
lowest_correlation = astc::min(lowest_correlation, fabsf(ga_cov));
lowest_correlation = astc::min(lowest_correlation, fabsf(ba_cov));
// Diagnostic trace points
trace_add_data("min_r", blk.data_min.lane<0>());
trace_add_data("max_r", blk.data_max.lane<0>());
trace_add_data("min_g", blk.data_min.lane<1>());
trace_add_data("max_g", blk.data_max.lane<1>());
trace_add_data("min_b", blk.data_min.lane<2>());
trace_add_data("max_b", blk.data_max.lane<2>());
trace_add_data("min_a", blk.data_min.lane<3>());
trace_add_data("max_a", blk.data_max.lane<3>());
trace_add_data("cov_rg", fabsf(rg_cov));
trace_add_data("cov_rb", fabsf(rb_cov));
trace_add_data("cov_ra", fabsf(ra_cov));
trace_add_data("cov_gb", fabsf(gb_cov));
trace_add_data("cov_ga", fabsf(ga_cov));
trace_add_data("cov_ba", fabsf(ba_cov));
return lowest_correlation;
}
/* See header for documentation. */
void compress_block(
const astcenc_context& ctx,
const astcenc_image& input_image,
const image_block& blk,
physical_compressed_block& pcb,
compression_working_buffers& tmpbuf)
{
astcenc_profile decode_mode = ctx.config.profile;
symbolic_compressed_block scb;
error_weight_block& ewb = tmpbuf.ewb;
const block_size_descriptor* bsd = ctx.bsd;
float lowest_correl;
TRACE_NODE(node0, "block");
trace_add_data("pos_x", blk.xpos);
trace_add_data("pos_y", blk.ypos);
trace_add_data("pos_z", blk.zpos);
// Set stricter block targets for luminance data as we have more bits to play with
bool block_is_l = blk.is_luminance();
float block_is_l_scale = block_is_l ? 1.0f / 1.5f : 1.0f;
// Set slightly stricter block targets for lumalpha data as we have more bits to play with
bool block_is_la = blk.is_luminancealpha();
float block_is_la_scale = block_is_la ? 1.0f / 1.05f : 1.0f;
bool block_skip_two_plane = false;
// Default max partition, but +1 if only have 1 or 2 active components
int max_partitions = ctx.config.tune_partition_count_limit;
if (block_is_l || block_is_la)
{
max_partitions = astc::min(max_partitions + 1, 4);
}
#if defined(ASTCENC_DIAGNOSTICS)
// Do this early in diagnostic builds so we can dump uniform metrics
// for every block. Do it later in release builds to avoid redundant work!
float error_weight_sum = prepare_error_weight_block(ctx, input_image, *bsd, blk, ewb);
float error_threshold = ctx.config.tune_db_limit
* error_weight_sum
* block_is_l_scale
* block_is_la_scale;
lowest_correl = prepare_block_statistics(bsd->texel_count, blk, ewb);
trace_add_data("lowest_correl", lowest_correl);
trace_add_data("tune_error_threshold", error_threshold);
#endif
// Detected a constant-color block
if (all(blk.data_min == blk.data_max))
{
TRACE_NODE(node1, "pass");
trace_add_data("partition_count", 0);
trace_add_data("plane_count", 1);
scb.partition_count = 0;
// Encode as FP16 if using HDR
if ((decode_mode == ASTCENC_PRF_HDR) ||
(decode_mode == ASTCENC_PRF_HDR_RGB_LDR_A))
{
scb.block_type = SYM_BTYPE_CONST_F16;
vint4 color_f16 = float_to_float16(blk.origin_texel);
store(color_f16, scb.constant_color);
}
// Encode as UNORM16 if NOT using HDR
else
{
scb.block_type = SYM_BTYPE_CONST_U16;
vfloat4 color_f32 = clamp(0.0f, 1.0f, blk.origin_texel) * 65535.0f;
vint4 color_u16 = float_to_int_rtn(color_f32);
store(color_u16, scb.constant_color);
}
trace_add_data("exit", "quality hit");
symbolic_to_physical(*bsd, scb, pcb);
return;
}
#if !defined(ASTCENC_DIAGNOSTICS)
float error_weight_sum = prepare_error_weight_block(ctx, input_image, *bsd, blk, ewb);
float error_threshold = ctx.config.tune_db_limit
* error_weight_sum
* block_is_l_scale
* block_is_la_scale;
#endif
// Set SCB and mode errors to a very high error value
scb.errorval = ERROR_CALC_DEFAULT;
scb.block_type = SYM_BTYPE_ERROR;
float best_errorvals_for_pcount[BLOCK_MAX_PARTITIONS] {
ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT, ERROR_CALC_DEFAULT
};
float exit_thresholds_for_pcount[BLOCK_MAX_PARTITIONS] {
0.0f,
ctx.config.tune_2_partition_early_out_limit_factor,
ctx.config.tune_3_partition_early_out_limit_factor,
0.0f
};
// Trial using 1 plane of weights and 1 partition.
// Most of the time we test it twice, first with a mode cutoff of 0 and then with the specified
// mode cutoff. This causes an early-out that speeds up encoding of easy blocks. However, this
// optimization is disabled for 4x4 and 5x4 blocks where it nearly always slows down the
// compression and slightly reduces image quality.
float errorval_mult[2] {
1.0f / ctx.config.tune_mode0_mse_overshoot,
1.0f
};
static const float errorval_overshoot = 1.0f / ctx.config.tune_refinement_mse_overshoot;
// Only enable MODE0 fast path (trial 0) if 2D and more than 25 texels
int start_trial = 1;
if ((bsd->texel_count >= TUNE_MIN_TEXELS_MODE0_FASTPATH) && (bsd->zdim == 1))
{
start_trial = 0;
}
for (int i = start_trial; i < 2; i++)
{
TRACE_NODE(node1, "pass");
trace_add_data("partition_count", 1);
trace_add_data("plane_count", 1);
trace_add_data("search_mode", i);
float errorval = compress_symbolic_block_for_partition_1plane(
ctx.config, *bsd, blk, ewb, i == 0,
error_threshold * errorval_mult[i] * errorval_overshoot,
1, 0, scb, tmpbuf);
best_errorvals_for_pcount[0] = astc::min(best_errorvals_for_pcount[0], errorval);
if (errorval < (error_threshold * errorval_mult[i]))
{
trace_add_data("exit", "quality hit");
goto END_OF_TESTS;
}
}
#if !defined(ASTCENC_DIAGNOSTICS)
lowest_correl = prepare_block_statistics(bsd->texel_count, blk, ewb);
#endif
block_skip_two_plane = lowest_correl > ctx.config.tune_2_plane_early_out_limit_correlation;
// Test the four possible 1-partition, 2-planes modes. Do this in reverse, as
// alpha is the most likely to be non-correlated if it is present in the data.
for (int i = BLOCK_MAX_COMPONENTS - 1; i >= 0; i--)
{
TRACE_NODE(node1, "pass");
trace_add_data("partition_count", 1);
trace_add_data("plane_count", 2);
trace_add_data("plane_component", i);
if (block_skip_two_plane)
{
trace_add_data("skip", "tune_2_plane_early_out_limit_correlation");
continue;
}
if (blk.grayscale && i != 3)
{
trace_add_data("skip", "grayscale block");
continue;
}
if (blk.is_constant_channel(i))
{
trace_add_data("skip", "constant component");
continue;
}
float errorval = compress_symbolic_block_for_partition_2planes(
ctx.config, *bsd, blk, ewb,
error_threshold * errorval_overshoot,
i, scb, tmpbuf);
// If attempting two planes is much worse than the best one plane result
// then further two plane searches are unlikely to help so move on ...
if (errorval > (best_errorvals_for_pcount[0] * 2.0f))
{
break;
}
if (errorval < error_threshold)
{
trace_add_data("exit", "quality hit");
goto END_OF_TESTS;
}
}
// Find best blocks for 2, 3 and 4 partitions
for (int partition_count = 2; partition_count <= max_partitions; partition_count++)
{
unsigned int partition_indices_1plane[2] { 0, 0 };
find_best_partition_candidates(*bsd, blk, ewb, partition_count,
ctx.config.tune_partition_index_limit,
partition_indices_1plane[0],
partition_indices_1plane[1]);
for (int i = 0; i < 2; i++)
{
TRACE_NODE(node1, "pass");
trace_add_data("partition_count", partition_count);
trace_add_data("partition_index", partition_indices_1plane[i]);
trace_add_data("plane_count", 1);
trace_add_data("search_mode", i);
float errorval = compress_symbolic_block_for_partition_1plane(
ctx.config, *bsd, blk, ewb, false,
error_threshold * errorval_overshoot,
partition_count, partition_indices_1plane[i],
scb, tmpbuf);
best_errorvals_for_pcount[partition_count - 1] = astc::min(best_errorvals_for_pcount[partition_count - 1], errorval);
if (errorval < error_threshold)
{
trace_add_data("exit", "quality hit");
goto END_OF_TESTS;
}
}
// If using N partitions doesn't improve much over using N-1 partitions then skip trying N+1
float best_error = best_errorvals_for_pcount[partition_count - 1];
float best_error_in_prev = best_errorvals_for_pcount[partition_count - 2];
float best_error_scale = exit_thresholds_for_pcount[partition_count - 1];
if (best_error > (best_error_in_prev * best_error_scale))
{
trace_add_data("skip", "tune_partition_early_out_limit_factor");
goto END_OF_TESTS;
}
}
trace_add_data("exit", "quality not hit");
END_OF_TESTS:
// Compress to a physical block
symbolic_to_physical(*bsd, scb, pcb);
}
#endif