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crn_comp.cpp
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1317 lines (1135 loc) · 48.9 KB
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// File: crn_comp.cpp
// See Copyright Notice and license at the end of inc/crnlib.h
#include "crn_core.h"
#include "crn_console.h"
#include "crn_comp.h"
#include "crn_checksum.h"
#define CRNLIB_CREATE_DEBUG_IMAGES 0
#define CRNLIB_ENABLE_DEBUG_MESSAGES 0
namespace crnlib {
crn_comp::crn_comp()
: m_pParams(NULL) {
}
crn_comp::~crn_comp() {
}
bool crn_comp::pack_color_endpoints(crnlib::vector<uint8>& packed_data, const crnlib::vector<uint16>& remapping) {
crnlib::vector<uint> remapped_endpoints(m_color_endpoints.size());
for (uint i = 0; i < m_color_endpoints.size(); i++)
remapped_endpoints[remapping[i]] = m_color_endpoints[i];
const uint component_limits[6] = {31, 63, 31, 31, 63, 31};
symbol_histogram hist[2];
hist[0].resize(32);
hist[1].resize(64);
crnlib::vector<uint> residual_syms;
residual_syms.reserve(m_color_endpoints.size() * 2 * 3);
color_quad_u8 prev[2];
prev[0].clear();
prev[1].clear();
for (uint endpoint_index = 0; endpoint_index < m_color_endpoints.size(); endpoint_index++) {
const uint endpoint = remapped_endpoints[endpoint_index];
color_quad_u8 cur[2];
cur[0] = dxt1_block::unpack_color((uint16)(endpoint & 0xFFFF), false);
cur[1] = dxt1_block::unpack_color((uint16)((endpoint >> 16) & 0xFFFF), false);
for (uint j = 0; j < 2; j++) {
for (uint k = 0; k < 3; k++) {
int delta = cur[j][k] - prev[j][k];
int sym = delta & component_limits[j * 3 + k];
int table = (k == 1) ? 1 : 0;
hist[table].inc_freq(sym);
residual_syms.push_back(sym);
}
}
prev[0] = cur[0];
prev[1] = cur[1];
}
static_huffman_data_model residual_dm[2];
symbol_codec codec;
codec.start_encoding(1024 * 1024);
// Transmit residuals
for (uint i = 0; i < 2; i++) {
if (!residual_dm[i].init(true, hist[i], 15))
return false;
if (!codec.encode_transmit_static_huffman_data_model(residual_dm[i], false))
return false;
}
for (uint i = 0; i < residual_syms.size(); i++) {
const uint sym = residual_syms[i];
const uint table = ((i % 3) == 1) ? 1 : 0;
codec.encode(sym, residual_dm[table]);
}
codec.stop_encoding(false);
packed_data.swap(codec.get_encoding_buf());
return true;
}
bool crn_comp::pack_color_endpoints_etc(crnlib::vector<uint8>& packed_data, const crnlib::vector<uint16>& remapping) {
crnlib::vector<uint32> remapped_endpoints(m_color_endpoints.size());
for (uint i = 0; i < m_color_endpoints.size(); i++)
remapped_endpoints[remapping[i]] = (m_color_endpoints[i] & 0x07000000) | (m_color_endpoints[i] >> 3 & 0x001F1F1F);
symbol_histogram hist(32);
for (uint32 prev_endpoint = 0, p = 0; p < remapped_endpoints.size(); p++) {
for (uint32 _e = prev_endpoint, e = prev_endpoint = remapped_endpoints[p], c = 0; c < 4; c++, _e >>= 8, e >>= 8)
hist.inc_freq((e - _e) & 0x1F);
}
static_huffman_data_model dm;
dm.init(true, hist, 15);
symbol_codec codec;
codec.start_encoding(1024 * 1024);
codec.encode_transmit_static_huffman_data_model(dm, false);
for (uint32 prev_endpoint = 0, p = 0; p < remapped_endpoints.size(); p++) {
for (uint32 _e = prev_endpoint, e = prev_endpoint = remapped_endpoints[p], c = 0; c < 4; c++, _e >>= 8, e >>= 8)
codec.encode((e - _e) & 0x1F, dm);
}
codec.stop_encoding(false);
packed_data.swap(codec.get_encoding_buf());
return true;
}
bool crn_comp::pack_alpha_endpoints(crnlib::vector<uint8>& packed_data, const crnlib::vector<uint16>& remapping) {
crnlib::vector<uint> remapped_endpoints(m_alpha_endpoints.size());
for (uint i = 0; i < m_alpha_endpoints.size(); i++)
remapped_endpoints[remapping[i]] = m_alpha_endpoints[i];
symbol_histogram hist;
hist.resize(256);
crnlib::vector<uint> residual_syms;
residual_syms.reserve(m_alpha_endpoints.size() * 2 * 3);
uint prev[2];
utils::zero_object(prev);
for (uint endpoint_index = 0; endpoint_index < m_alpha_endpoints.size(); endpoint_index++) {
const uint endpoint = remapped_endpoints[endpoint_index];
uint cur[2];
cur[0] = dxt5_block::unpack_endpoint(endpoint, 0);
cur[1] = dxt5_block::unpack_endpoint(endpoint, 1);
for (uint j = 0; j < 2; j++) {
int delta = cur[j] - prev[j];
int sym = delta & 255;
hist.inc_freq(sym);
residual_syms.push_back(sym);
}
prev[0] = cur[0];
prev[1] = cur[1];
}
static_huffman_data_model residual_dm;
symbol_codec codec;
codec.start_encoding(1024 * 1024);
// Transmit residuals
if (!residual_dm.init(true, hist, 15))
return false;
if (!codec.encode_transmit_static_huffman_data_model(residual_dm, false))
return false;
for (uint i = 0; i < residual_syms.size(); i++) {
const uint sym = residual_syms[i];
codec.encode(sym, residual_dm);
}
codec.stop_encoding(false);
packed_data.swap(codec.get_encoding_buf());
return true;
}
bool crn_comp::pack_color_selectors(crnlib::vector<uint8>& packed_data, const crnlib::vector<uint16>& remapping) {
crnlib::vector<uint32> remapped_selectors(m_color_selectors.size());
for (uint i = 0; i < m_color_selectors.size(); i++)
remapped_selectors[remapping[i]] = m_color_selectors[i];
symbol_histogram hist(16);
for (uint32 c, selector, prev_selector = 0, i = 0; i < remapped_selectors.size(); i++) {
for (selector = prev_selector ^ remapped_selectors[i], prev_selector ^= selector, c = 8; c; c--, selector >>= 4)
hist.inc_freq(selector & 0xF);
}
static_huffman_data_model dm;
dm.init(true, hist, 15);
symbol_codec codec;
codec.start_encoding(1024 * 1024);
codec.encode_transmit_static_huffman_data_model(dm, false);
for (uint32 c, selector, prev_selector = 0, i = 0; i < remapped_selectors.size(); i++) {
for (selector = prev_selector ^ remapped_selectors[i], prev_selector ^= selector, c = 8; c; c--, selector >>= 4)
codec.encode(selector & 0xF, dm);
}
codec.stop_encoding(false);
packed_data.swap(codec.get_encoding_buf());
return true;
}
bool crn_comp::pack_alpha_selectors(crnlib::vector<uint8>& packed_data, const crnlib::vector<uint16>& remapping) {
crnlib::vector<uint64> remapped_selectors(m_alpha_selectors.size());
for (uint i = 0; i < m_alpha_selectors.size(); i++)
remapped_selectors[remapping[i]] = m_alpha_selectors[i];
symbol_histogram hist(64);
for (uint64 c, selector, prev_selector = 0, i = 0; i < remapped_selectors.size(); i++) {
for (selector = prev_selector ^ remapped_selectors[i], prev_selector ^= selector, c = 8; c; c--, selector >>= 6)
hist.inc_freq(selector & 0x3F);
}
static_huffman_data_model dm;
dm.init(true, hist, 15);
symbol_codec codec;
codec.start_encoding(1024 * 1024);
codec.encode_transmit_static_huffman_data_model(dm, false);
for (uint64 c, selector, prev_selector = 0, i = 0; i < remapped_selectors.size(); i++) {
for (selector = prev_selector ^ remapped_selectors[i], prev_selector ^= selector, c = 8; c; c--, selector >>= 6)
codec.encode(selector & 0x3F, dm);
}
codec.stop_encoding(false);
packed_data.swap(codec.get_encoding_buf());
return true;
}
bool crn_comp::pack_blocks(
uint group,
bool clear_histograms,
symbol_codec* pCodec,
const crnlib::vector<uint16>* pColor_endpoint_remap,
const crnlib::vector<uint16>* pColor_selector_remap,
const crnlib::vector<uint16>* pAlpha_endpoint_remap,
const crnlib::vector<uint16>* pAlpha_selector_remap
) {
if (!pCodec) {
m_reference_hist.resize(256);
if (clear_histograms)
m_reference_hist.set_all(0);
if (pColor_endpoint_remap) {
m_endpoint_index_hist[0].resize(pColor_endpoint_remap->size());
if (clear_histograms)
m_endpoint_index_hist[0].set_all(0);
}
if (pColor_selector_remap) {
m_selector_index_hist[0].resize(pColor_selector_remap->size());
if (clear_histograms)
m_selector_index_hist[0].set_all(0);
}
if (pAlpha_endpoint_remap) {
m_endpoint_index_hist[1].resize(pAlpha_endpoint_remap->size());
if (clear_histograms)
m_endpoint_index_hist[1].set_all(0);
}
if (pAlpha_selector_remap) {
m_selector_index_hist[1].resize(pAlpha_selector_remap->size());
if (clear_histograms)
m_selector_index_hist[1].set_all(0);
}
}
uint endpoint_index[cNumComps] = {};
const crnlib::vector<uint16>* endpoint_remap[cNumComps] = {};
const crnlib::vector<uint16>* selector_remap[cNumComps] = {};
for (uint c = 0; c < cNumComps; c++) {
if (m_has_comp[c]) {
endpoint_remap[c] = c ? pAlpha_endpoint_remap : pColor_endpoint_remap;
selector_remap[c] = c ? pAlpha_selector_remap : pColor_selector_remap;
}
}
uint block_width = m_levels[group].block_width;
for (uint by = 0, b = m_levels[group].first_block, bEnd = b + m_levels[group].num_blocks; b < bEnd; by++) {
for (uint bx = 0; bx < block_width; bx++, b++) {
const bool secondary_etc_subblock = m_has_subblocks && bx & 1;
if (!(by & 1) && !(bx & 1)) {
uint8 reference_group = m_endpoint_indices[b].reference | m_endpoint_indices[b + block_width].reference << 2 |
m_endpoint_indices[b + 1].reference << 4 | m_endpoint_indices[b + block_width + 1].reference << 6;
if (pCodec)
pCodec->encode(reference_group, m_reference_dm);
else
m_reference_hist.inc_freq(reference_group);
}
for (uint c = 0, cEnd = secondary_etc_subblock ? cAlpha0 : cNumComps; c < cEnd; c++) {
if (endpoint_remap[c]) {
uint index = (*endpoint_remap[c])[m_endpoint_indices[b].component[c]];
if (secondary_etc_subblock ? m_endpoint_indices[b].reference : !m_endpoint_indices[b].reference) {
int sym = index - endpoint_index[c];
if (sym < 0)
sym += endpoint_remap[c]->size();
if (!pCodec)
m_endpoint_index_hist[c ? 1 : 0].inc_freq(sym);
else
pCodec->encode(sym, m_endpoint_index_dm[c ? 1 : 0]);
}
endpoint_index[c] = index;
}
}
for (uint c = 0, cEnd = secondary_etc_subblock ? 0 : cNumComps; c < cEnd; c++) {
if (selector_remap[c]) {
uint index = (*selector_remap[c])[m_selector_indices[b].component[c]];
if (!pCodec)
m_selector_index_hist[c ? 1 : 0].inc_freq(index);
else
pCodec->encode(index, m_selector_index_dm[c ? 1 : 0]);
}
}
}
}
return true;
}
bool crn_comp::alias_images() {
for (uint face_index = 0; face_index < m_pParams->m_faces; face_index++) {
for (uint level_index = 0; level_index < m_pParams->m_levels; level_index++) {
const uint width = math::maximum(1U, m_pParams->m_width >> level_index);
const uint height = math::maximum(1U, m_pParams->m_height >> level_index);
if (!m_pParams->m_pImages[face_index][level_index])
return false;
m_images[face_index][level_index].alias((color_quad_u8*)m_pParams->m_pImages[face_index][level_index], width, height);
}
}
image_utils::conversion_type conv_type = image_utils::get_image_conversion_type_from_crn_format((crn_format)m_pParams->m_format);
if (conv_type != image_utils::cConversion_Invalid) {
for (uint face_index = 0; face_index < m_pParams->m_faces; face_index++) {
for (uint level_index = 0; level_index < m_pParams->m_levels; level_index++) {
image_u8 cooked_image(m_images[face_index][level_index]);
image_utils::convert_image(cooked_image, conv_type);
m_images[face_index][level_index].swap(cooked_image);
}
}
}
m_levels.resize(m_pParams->m_levels);
m_total_blocks = 0;
for (uint level = 0; level < m_pParams->m_levels; level++) {
uint blockHeight = ((math::maximum(1U, m_pParams->m_height >> level) + 7) & ~7) >> 2;
m_levels[level].block_width = ((math::maximum(1U, m_pParams->m_width >> level) + 7) & ~7) >> (m_has_subblocks ? 1 : 2);
m_levels[level].first_block = m_total_blocks;
m_levels[level].num_blocks = m_pParams->m_faces * m_levels[level].block_width * blockHeight;
m_total_blocks += m_levels[level].num_blocks;
}
return true;
}
void crn_comp::clear() {
m_pParams = NULL;
for (uint f = 0; f < cCRNMaxFaces; f++)
for (uint l = 0; l < cCRNMaxLevels; l++)
m_images[f][l].clear();
utils::zero_object(m_has_comp);
m_has_etc_color_blocks = false;
m_has_subblocks = false;
m_levels.clear();
m_total_blocks = 0;
m_color_endpoints.clear();
m_alpha_endpoints.clear();
m_color_selectors.clear();
m_alpha_selectors.clear();
m_endpoint_indices.clear();
m_selector_indices.clear();
utils::zero_object(m_crn_header);
m_comp_data.clear();
m_hvq.clear();
m_reference_hist.clear();
m_reference_dm.clear();
for (uint i = 0; i < 2; i++) {
m_endpoint_remaping[i].clear();
m_endpoint_index_hist[i].clear();
m_endpoint_index_dm[i].clear();
m_selector_remaping[i].clear();
m_selector_index_hist[i].clear();
m_selector_index_dm[i].clear();
}
for (uint i = 0; i < cCRNMaxLevels; i++)
m_packed_blocks[i].clear();
m_packed_data_models.clear();
m_packed_color_endpoints.clear();
m_packed_color_selectors.clear();
m_packed_alpha_endpoints.clear();
m_packed_alpha_selectors.clear();
}
bool crn_comp::quantize_images() {
dxt_hc::params params;
params.m_adaptive_tile_alpha_psnr_derating = m_pParams->m_crn_adaptive_tile_alpha_psnr_derating;
params.m_adaptive_tile_color_psnr_derating = m_pParams->m_crn_adaptive_tile_color_psnr_derating;
if (m_pParams->m_flags & cCRNCompFlagManualPaletteSizes) {
params.m_color_endpoint_codebook_size = math::clamp<int>(m_pParams->m_crn_color_endpoint_palette_size, cCRNMinPaletteSize, cCRNMaxPaletteSize);
params.m_color_selector_codebook_size = math::clamp<int>(m_pParams->m_crn_color_selector_palette_size, cCRNMinPaletteSize, cCRNMaxPaletteSize);
params.m_alpha_endpoint_codebook_size = math::clamp<int>(m_pParams->m_crn_alpha_endpoint_palette_size, cCRNMinPaletteSize, cCRNMaxPaletteSize);
params.m_alpha_selector_codebook_size = math::clamp<int>(m_pParams->m_crn_alpha_selector_palette_size, cCRNMinPaletteSize, cCRNMaxPaletteSize);
} else {
uint max_codebook_entries = ((m_pParams->m_width + 3) / 4) * ((m_pParams->m_height + 3) / 4);
max_codebook_entries = math::clamp<uint>(max_codebook_entries, cCRNMinPaletteSize, cCRNMaxPaletteSize);
float quality = math::clamp<float>((float)m_pParams->m_quality_level / cCRNMaxQualityLevel, 0.0f, 1.0f);
float color_quality_power_mul = 1.0f;
float alpha_quality_power_mul = 1.0f;
if (m_has_etc_color_blocks) {
color_quality_power_mul = m_has_subblocks ? 1.31f : 0.7f;
params.m_adaptive_tile_color_psnr_derating = m_has_subblocks ? 5.0f : 2.0f;
}
if (m_pParams->m_format == cCRNFmtDXT5_CCxY) {
color_quality_power_mul = 3.5f;
alpha_quality_power_mul = .35f;
params.m_adaptive_tile_color_psnr_derating = 5.0f;
} else if (m_pParams->m_format == cCRNFmtDXT5) {
color_quality_power_mul = .75f;
} else if (m_pParams->m_format == cCRNFmtETC2A) {
alpha_quality_power_mul = .9f;
}
float color_endpoint_quality = powf(quality, 1.8f * color_quality_power_mul);
float color_selector_quality = powf(quality, 1.65f * color_quality_power_mul);
params.m_color_endpoint_codebook_size = math::clamp<uint>(math::float_to_uint(.5f + math::lerp<float>(math::maximum<float>(64, cCRNMinPaletteSize), (float)max_codebook_entries, color_endpoint_quality)), cCRNMinPaletteSize, cCRNMaxPaletteSize);
params.m_color_selector_codebook_size = math::clamp<uint>(math::float_to_uint(.5f + math::lerp<float>(math::maximum<float>(96, cCRNMinPaletteSize), (float)max_codebook_entries, color_selector_quality)), cCRNMinPaletteSize, cCRNMaxPaletteSize);
float alpha_endpoint_quality = powf(quality, 2.1f * alpha_quality_power_mul);
float alpha_selector_quality = powf(quality, 1.65f * alpha_quality_power_mul);
params.m_alpha_endpoint_codebook_size = math::clamp<uint>(math::float_to_uint(.5f + math::lerp<float>(math::maximum<float>(24, cCRNMinPaletteSize), (float)max_codebook_entries, alpha_endpoint_quality)), cCRNMinPaletteSize, cCRNMaxPaletteSize);
params.m_alpha_selector_codebook_size = math::clamp<uint>(math::float_to_uint(.5f + math::lerp<float>(math::maximum<float>(48, cCRNMinPaletteSize), (float)max_codebook_entries, alpha_selector_quality)), cCRNMinPaletteSize, cCRNMaxPaletteSize);
}
if (m_pParams->m_flags & cCRNCompFlagDebugging) {
console::debug("Color endpoints: %u", params.m_color_endpoint_codebook_size);
console::debug("Color selectors: %u", params.m_color_selector_codebook_size);
console::debug("Alpha endpoints: %u", params.m_alpha_endpoint_codebook_size);
console::debug("Alpha selectors: %u", params.m_alpha_selector_codebook_size);
}
params.m_hierarchical = (m_pParams->m_flags & cCRNCompFlagHierarchical) != 0;
params.m_perceptual = (m_pParams->m_flags & cCRNCompFlagPerceptual) != 0;
params.m_pProgress_func = m_pParams->m_pProgress_func;
params.m_pProgress_func_data = m_pParams->m_pProgress_func_data;
switch (m_pParams->m_format) {
case cCRNFmtDXT1: {
params.m_format = cDXT1;
m_has_comp[cColor] = true;
break;
}
case cCRNFmtDXT3: {
m_has_comp[cAlpha0] = true;
return false;
}
case cCRNFmtDXT5: {
params.m_format = cDXT5;
params.m_alpha_component_indices[0] = m_pParams->m_alpha_component;
m_has_comp[cColor] = true;
m_has_comp[cAlpha0] = true;
break;
}
case cCRNFmtDXT5_CCxY: {
params.m_format = cDXT5;
params.m_alpha_component_indices[0] = 3;
m_has_comp[cColor] = true;
m_has_comp[cAlpha0] = true;
params.m_perceptual = false;
//params.m_adaptive_tile_color_alpha_weighting_ratio = 1.0f;
params.m_adaptive_tile_color_alpha_weighting_ratio = 1.5f;
break;
}
case cCRNFmtDXT5_xGBR:
case cCRNFmtDXT5_AGBR:
case cCRNFmtDXT5_xGxR: {
params.m_format = cDXT5;
params.m_alpha_component_indices[0] = 3;
m_has_comp[cColor] = true;
m_has_comp[cAlpha0] = true;
params.m_perceptual = false;
break;
}
case cCRNFmtDXN_XY: {
params.m_format = cDXN_XY;
params.m_alpha_component_indices[0] = 0;
params.m_alpha_component_indices[1] = 1;
m_has_comp[cAlpha0] = true;
m_has_comp[cAlpha1] = true;
params.m_perceptual = false;
break;
}
case cCRNFmtDXN_YX: {
params.m_format = cDXN_YX;
params.m_alpha_component_indices[0] = 1;
params.m_alpha_component_indices[1] = 0;
m_has_comp[cAlpha0] = true;
m_has_comp[cAlpha1] = true;
params.m_perceptual = false;
break;
}
case cCRNFmtDXT5A: {
params.m_format = cDXT5A;
params.m_alpha_component_indices[0] = m_pParams->m_alpha_component;
m_has_comp[cAlpha0] = true;
params.m_perceptual = false;
break;
}
case cCRNFmtETC1: {
params.m_format = cETC1;
m_has_comp[cColor] = true;
break;
}
case cCRNFmtETC2: {
params.m_format = cETC2;
m_has_comp[cColor] = true;
break;
}
case cCRNFmtETC2A: {
params.m_format = cETC2A;
params.m_alpha_component_indices[0] = m_pParams->m_alpha_component;
m_has_comp[cColor] = true;
m_has_comp[cAlpha0] = true;
break;
}
case cCRNFmtETC1S: {
params.m_format = cETC1S;
m_has_comp[cColor] = true;
break;
}
case cCRNFmtETC2AS: {
params.m_format = cETC2AS;
params.m_alpha_component_indices[0] = m_pParams->m_alpha_component;
m_has_comp[cColor] = true;
m_has_comp[cAlpha0] = true;
break;
}
default: {
return false;
}
}
params.m_debugging = (m_pParams->m_flags & cCRNCompFlagDebugging) != 0;
params.m_pTask_pool = &m_task_pool;
params.m_num_levels = m_pParams->m_levels;
for (uint i = 0; i < m_pParams->m_levels; i++) {
params.m_levels[i].m_first_block = m_levels[i].first_block;
params.m_levels[i].m_num_blocks = m_levels[i].num_blocks;
params.m_levels[i].m_block_width = m_levels[i].block_width;
params.m_levels[i].m_weight = math::minimum(12.0f, powf(1.3f, (float)i));
}
params.m_num_faces = m_pParams->m_faces;
params.m_num_blocks = m_total_blocks;
color_quad_u8 (*blocks)[16] = (color_quad_u8(*)[16])crnlib_malloc(params.m_num_blocks * 16 * sizeof(color_quad_u8));
for (uint b = 0, level = 0; level < m_pParams->m_levels; level++) {
for (uint face = 0; face < m_pParams->m_faces; face++) {
image_u8& image = m_images[face][level];
uint width = image.get_width();
uint height = image.get_height();
uint blockWidth = ((width + 7) & ~7) >> 2;
uint blockHeight = ((height + 7) & ~7) >> 2;
for (uint by = 0; by < blockHeight; by++) {
for (uint y0 = by << 2, bx = 0; bx < blockWidth; bx++, b++) {
for (uint t = 0, x0 = bx << 2, dy = 0; dy < 4; dy++) {
for (uint y = math::minimum<uint>(y0 + dy, height - 1), dx = 0; dx < 4; dx++, t++)
blocks[b][t] = image(math::minimum<uint>(x0 + dx, width - 1), y);
}
}
}
}
}
bool result = m_hvq.compress(blocks, m_endpoint_indices, m_selector_indices, m_color_endpoints, m_alpha_endpoints, m_color_selectors, m_alpha_selectors, params);
crnlib_free(blocks);
return result;
}
struct optimize_color_params {
struct unpacked_endpoint {
color_quad_u8 low, high;
};
const unpacked_endpoint* unpacked_endpoints;
const uint* hist;
uint16 n;
uint16 selected;
float weight;
struct result {
crnlib::vector<uint16> endpoint_remapping;
crnlib::vector<uint8> packed_endpoints;
uint total_bits;
} *pResult;
};
static void sort_color_endpoints(crnlib::vector<uint16>& remapping, const optimize_color_params::unpacked_endpoint* unpacked_endpoints, uint16 n) {
remapping.resize(n);
crnlib::vector<optimize_color_params::unpacked_endpoint> endpoints(n);
crnlib::vector<uint16> indices(n);
for (uint16 i = 0; i < n; i++) {
endpoints[i] = unpacked_endpoints[i];
indices[i] = i;
}
optimize_color_params::unpacked_endpoint selected_endpoint = {color_quad_u8(0), color_quad_u8(0)};
for (uint16 left = n; left;) {
uint16 selected_index = 0;
uint min_error = cUINT32_MAX;
for (uint16 i = 0; i < left; i++) {
optimize_color_params::unpacked_endpoint& endpoint = endpoints[i];
uint error = color::elucidian_distance(endpoint.low, selected_endpoint.low, false) + color::elucidian_distance(endpoint.high, selected_endpoint.high, false);
if (error < min_error) {
min_error = error;
selected_index = i;
}
}
selected_endpoint = endpoints[selected_index];
remapping[indices[selected_index]] = n - left;
left--;
endpoints[selected_index] = endpoints[left];
indices[selected_index] = indices[left];
}
}
static void remap_color_endpoints(uint16* remapping, const optimize_color_params::unpacked_endpoint* unpacked_endpoints, const uint* hist, uint16 n, uint16 selected, float weight) {
struct Node {
uint index, frequency, front_similarity, back_similarity;
optimize_color_params::unpacked_endpoint e;
Node() { utils::zero_object(*this); }
};
crnlib::vector<Node> remaining(n);
for (uint16 i = 0; i < n; i++) {
remaining[i].index = i;
remaining[i].e = unpacked_endpoints[i];
}
crnlib::vector<uint16> chosen(n << 1);
uint16 remaining_count = n, chosen_front = n, chosen_back = chosen_front;
chosen[chosen_front] = selected;
optimize_color_params::unpacked_endpoint front_e = remaining[selected].e, back_e = front_e;
bool front_updated = true, back_updated = true;
remaining[selected] = remaining[--remaining_count];
const uint* frequency = hist + selected * n;
for (uint similarity_base = (uint)(4000 * (1.0f + weight)), frequency_normalizer = 0; remaining_count;) {
uint64 best_value = 0;
uint best_index = 0;
for (uint i = 0; i < remaining_count; i++) {
Node& node = remaining[i];
node.frequency += frequency[node.index];
if (front_updated)
node.front_similarity = similarity_base - math::minimum<uint>(4000, color::elucidian_distance(node.e.low, front_e.low, false) + color::elucidian_distance(node.e.high, front_e.high, false));
if (back_updated)
node.back_similarity = similarity_base - math::minimum<uint>(4000, color::elucidian_distance(node.e.low, back_e.low, false) + color::elucidian_distance(node.e.high, back_e.high, false));
uint64 value = math::maximum(node.front_similarity, node.back_similarity) * (node.frequency + frequency_normalizer) + 1;
if (value > best_value || (value == best_value && node.index < selected)) {
best_value = value;
best_index = i;
selected = node.index;
}
}
frequency = hist + selected * n;
uint frequency_front = 0, frequency_back = 0;
for (int front = chosen_front, back = chosen_back, scale = back - front; scale > 0; front++, back--, scale -= 2) {
frequency_front += scale * frequency[chosen[front]];
frequency_back += scale * frequency[chosen[back]];
}
front_updated = back_updated = false;
Node& best_node = remaining[best_index];
frequency_normalizer = best_node.frequency << 3;
if ((uint64)best_node.front_similarity * frequency_front > (uint64)best_node.back_similarity * frequency_back) {
chosen[--chosen_front] = selected;
front_e = best_node.e;
front_updated = true;
} else {
chosen[++chosen_back] = selected;
back_e = best_node.e;
back_updated = true;
}
best_node = remaining[--remaining_count];
}
for (uint16 i = chosen_front; i <= chosen_back; i++)
remapping[chosen[i]] = i - chosen_front;
}
void crn_comp::optimize_color_endpoints_task(uint64 data, void* pData_ptr) {
optimize_color_params* pParams = reinterpret_cast<optimize_color_params*>(pData_ptr);
crnlib::vector<uint16>& remapping = pParams->pResult->endpoint_remapping;
uint16 n = pParams->n;
remapping.resize(n);
if (data) {
remap_color_endpoints(remapping.get_ptr(), pParams->unpacked_endpoints, pParams->hist, n, pParams->selected, pParams->weight);
} else {
sort_color_endpoints(remapping, pParams->unpacked_endpoints, n);
optimize_color_selectors();
}
m_has_etc_color_blocks ? pack_color_endpoints_etc(pParams->pResult->packed_endpoints, remapping) : pack_color_endpoints(pParams->pResult->packed_endpoints, remapping);
uint total_bits = pParams->pResult->packed_endpoints.size() << 3;
crnlib::vector<uint> hist(n);
for (uint level = 0; level < m_levels.size(); level++) {
for (uint endpoint_index = 0, b = m_levels[level].first_block, bEnd = b + m_levels[level].num_blocks; b < bEnd; b++) {
uint index = remapping[m_endpoint_indices[b].component[cColor]];
if (m_has_subblocks && b & 1 ? m_endpoint_indices[b].reference : !m_endpoint_indices[b].reference) {
int sym = index - endpoint_index;
hist[sym < 0 ? sym + n : sym]++;
}
endpoint_index = index;
}
}
static_huffman_data_model dm;
dm.init(true, n, hist.get_ptr(), 16);
const uint8* code_sizes = dm.get_code_sizes();
for (uint16 s = 0; s < n; s++)
total_bits += hist[s] * code_sizes[s];
symbol_codec codec;
codec.start_encoding(64 * 1024);
codec.encode_enable_simulation(true);
codec.encode_transmit_static_huffman_data_model(dm, false);
codec.stop_encoding(false);
total_bits += codec.encode_get_total_bits_written();
pParams->pResult->total_bits = total_bits;
crnlib_delete(pParams);
}
void crn_comp::optimize_color_selectors() {
crnlib::vector<uint16>& remapping = m_selector_remaping[cColor];
uint16 n = m_color_selectors.size();
remapping.resize(n);
uint8 d[] = {0, 5, 14, 10};
uint8 D4[0x100];
for (uint16 i = 0; i < 0x100; i++)
D4[i] = d[(i ^ i >> 4) & 3] + d[(i >> 2 ^ i >> 6) & 3];
uint8 D8[0x10000];
for (uint32 i = 0; i < 0x10000; i++)
D8[i] = D4[(i >> 8 & 0xF0) | (i >> 4 & 0xF)] + D4[(i >> 4 & 0xF0) | (i & 0xF)];
crnlib::vector<uint32> selectors(n);
crnlib::vector<uint16> indices(n);
for (uint16 i = 0; i < n; i++) {
selectors[i] = m_color_selectors[i];
indices[i] = i;
}
uint32 selected_selector = 0;
for (uint16 left = n; left;) {
uint16 selected_index = 0;
uint min_error = cUINT32_MAX;
for (uint16 i = 0; i < left; i++) {
uint32 selector = selectors[i];
uint8 d0 = D8[(selector >> 16 & 0xFF00) | (selected_selector >> 24 & 0xFF)];
uint8 d1 = D8[(selector >> 8 & 0xFF00) | (selected_selector >> 16 & 0xFF)];
uint8 d2 = D8[(selector & 0xFF00) | (selected_selector >> 8 & 0xFF)];
uint8 d3 = D8[(selector << 8 & 0xFF00) | (selected_selector & 0xFF)];
uint error = d0 + d1 + d2 + d3;
if (error < min_error) {
min_error = error;
selected_index = i;
}
}
selected_selector = selectors[selected_index];
remapping[indices[selected_index]] = n - left;
left--;
selectors[selected_index] = selectors[left];
indices[selected_index] = indices[left];
}
pack_color_selectors(m_packed_color_selectors, remapping);
}
void crn_comp::optimize_color() {
uint16 n = m_color_endpoints.size();
crnlib::vector<uint> hist(n * n);
crnlib::vector<uint> sum(n);
for (uint i, i_prev = 0, b = 0; b < m_endpoint_indices.size(); b++, i_prev = i) {
i = m_endpoint_indices[b].color;
if ((m_has_subblocks && b & 1 ? m_endpoint_indices[b].reference : !m_endpoint_indices[b].reference) && i != i_prev) {
hist[i * n + i_prev]++;
hist[i_prev * n + i]++;
sum[i]++;
sum[i_prev]++;
}
}
uint16 selected = 0;
uint best_sum = 0;
for (uint16 i = 0; i < n; i++) {
if (best_sum < sum[i]) {
best_sum = sum[i];
selected = i;
}
}
crnlib::vector<optimize_color_params::unpacked_endpoint> unpacked_endpoints(n);
for (uint16 i = 0; i < n; i++) {
unpacked_endpoints[i].low.m_u32 = m_has_etc_color_blocks ? m_color_endpoints[i] & 0xFFFFFF : dxt1_block::unpack_color(m_color_endpoints[i] & 0xFFFF, true).m_u32;
unpacked_endpoints[i].high.m_u32 = m_has_etc_color_blocks ? m_color_endpoints[i] >> 24 : dxt1_block::unpack_color(m_color_endpoints[i] >> 16, true).m_u32;
}
optimize_color_params::result remapping_trial[4];
float weights[4] = {0, 0, 1.0f / 6.0f, 0.5f};
for (uint i = 0; i < 4; i++) {
optimize_color_params* pParams = crnlib_new<optimize_color_params>();
pParams->unpacked_endpoints = unpacked_endpoints.get_ptr();
pParams->hist = hist.get_ptr();
pParams->n = n;
pParams->selected = selected;
pParams->weight = weights[i];
pParams->pResult = remapping_trial + i;
m_task_pool.queue_object_task(this, &crn_comp::optimize_color_endpoints_task, i, pParams);
}
m_task_pool.join();
for (uint best_bits = cUINT32_MAX, i = 0; i < 4; i++) {
if (remapping_trial[i].total_bits < best_bits) {
m_packed_color_endpoints.swap(remapping_trial[i].packed_endpoints);
m_endpoint_remaping[cColor].swap(remapping_trial[i].endpoint_remapping);
best_bits = remapping_trial[i].total_bits;
}
}
}
struct optimize_alpha_params {
struct unpacked_endpoint {
uint8 low, high;
};
const unpacked_endpoint* unpacked_endpoints;
const uint* hist;
uint16 n;
uint16 selected;
float weight;
struct result {
crnlib::vector<uint16> endpoint_remapping;
crnlib::vector<uint8> packed_endpoints;
uint total_bits;
} *pResult;
};
static void sort_alpha_endpoints(crnlib::vector<uint16>& remapping, const optimize_alpha_params::unpacked_endpoint* unpacked_endpoints, uint16 n) {
remapping.resize(n);
crnlib::vector<optimize_alpha_params::unpacked_endpoint> endpoints(n);
crnlib::vector<uint16> indices(n);
for (uint16 i = 0; i < n; i++) {
endpoints[i] = unpacked_endpoints[i];
indices[i] = i;
}
optimize_alpha_params::unpacked_endpoint selected_endpoint = {0, 0};
for (uint16 left = n; left;) {
uint16 selected_index = 0;
uint min_error = cUINT32_MAX;
for (uint16 i = 0; i < left; i++) {
optimize_alpha_params::unpacked_endpoint& endpoint = endpoints[i];
uint error = math::square(endpoint.low - selected_endpoint.low) + math::square(endpoint.high - selected_endpoint.high);
if (error < min_error) {
min_error = error;
selected_index = i;
}
}
selected_endpoint = endpoints[selected_index];
remapping[indices[selected_index]] = n - left;
left--;
endpoints[selected_index] = endpoints[left];
indices[selected_index] = indices[left];
}
}
static void remap_alpha_endpoints(uint16* remapping, const optimize_alpha_params::unpacked_endpoint* unpacked_endpoints, const uint* hist, uint16 n, uint16 selected, float weight) {
const uint* frequency = hist + selected * n;
crnlib::vector<uint16> chosen, remaining;
crnlib::vector<uint> total_frequency(n);
chosen.push_back(selected);
for (uint16 i = 0; i < n; i++) {
if (i != selected) {
remaining.push_back(i);
total_frequency[i] = frequency[i];
}
}
for (uint similarity_base = (uint)(1000 * (1.0f + weight)), total_frequency_normalizer = 0; remaining.size();) {
const optimize_alpha_params::unpacked_endpoint& e_front = unpacked_endpoints[chosen.front()];
const optimize_alpha_params::unpacked_endpoint& e_back = unpacked_endpoints[chosen.back()];
uint16 selected_index = 0;
uint64 best_value = 0, selected_similarity_front = 0, selected_similarity_back = 0;
for (size_t i = 0; i < remaining.size(); i++) {
uint remaining_index = remaining[i];
const optimize_alpha_params::unpacked_endpoint& e_remaining = unpacked_endpoints[remaining_index];
uint error_front = math::square(e_remaining.low - e_front.low) + math::square(e_remaining.high - e_front.high);
uint error_back = math::square(e_remaining.low - e_back.low) + math::square(e_remaining.high - e_back.high);
uint64 similarity_front = similarity_base - math::minimum<uint>(error_front, 1000);
uint64 similarity_back = similarity_base - math::minimum<uint>(error_back, 1000);
uint64 value = math::maximum(similarity_front, similarity_back) * (total_frequency[remaining_index] + total_frequency_normalizer) + 1;
if (value > best_value) {
best_value = value;
selected_index = i;
selected_similarity_front = similarity_front;
selected_similarity_back = similarity_back;
}
}
selected = remaining[selected_index];
frequency = hist + selected * n;
total_frequency_normalizer = total_frequency[selected];
uint frequency_front = 0, frequency_back = 0;
for (int front = 0, back = chosen.size() - 1, scale = back; scale > 0; front++, back--, scale -= 2) {
frequency_front += scale * frequency[chosen[front]];
frequency_back += scale * frequency[chosen[back]];
}
if (selected_similarity_front * frequency_front > selected_similarity_back * frequency_back) {
chosen.push_front(selected);
} else {
chosen.push_back(selected);
}
remaining.erase(remaining.begin() + selected_index);
for (size_t i = 0; i < remaining.size(); i++)
total_frequency[remaining[i]] += frequency[remaining[i]];
}
for (uint16 i = 0; i < n; i++)
remapping[chosen[i]] = i;
}
void crn_comp::optimize_alpha_endpoints_task(uint64 data, void* pData_ptr) {
optimize_alpha_params* pParams = reinterpret_cast<optimize_alpha_params*>(pData_ptr);
crnlib::vector<uint16>& remapping = pParams->pResult->endpoint_remapping;
uint16 n = pParams->n;
remapping.resize(n);
if (data) {
remap_alpha_endpoints(remapping.get_ptr(), pParams->unpacked_endpoints, pParams->hist, n, pParams->selected, pParams->weight);
} else {
sort_alpha_endpoints(remapping, pParams->unpacked_endpoints, n);
optimize_alpha_selectors();
}
pack_alpha_endpoints(pParams->pResult->packed_endpoints, remapping);
uint total_bits = pParams->pResult->packed_endpoints.size() << 3;
crnlib::vector<uint> hist(n);
bool hasAlpha0 = m_has_comp[cAlpha0], hasAlpha1 = m_has_comp[cAlpha1];
for (uint level = 0; level < m_levels.size(); level++) {
for (uint alpha0_index = 0, alpha1_index = 0, b = m_levels[level].first_block, bEnd = b + m_levels[level].num_blocks; b < bEnd; b++) {
if (hasAlpha0) {
uint index = remapping[m_endpoint_indices[b].component[cAlpha0]];
if (!m_endpoint_indices[b].reference) {
int sym = index - alpha0_index;
hist[sym < 0 ? sym + n : sym]++;
}
alpha0_index = index;
}
if (hasAlpha1) {
uint index = remapping[m_endpoint_indices[b].component[cAlpha1]];
if (!m_endpoint_indices[b].reference) {
int sym = index - alpha1_index;
hist[sym < 0 ? sym + n : sym]++;
}
alpha1_index = index;
}
}
}
static_huffman_data_model dm;
dm.init(true, n, hist.get_ptr(), 16);
const uint8* code_sizes = dm.get_code_sizes();
for (uint16 s = 0; s < n; s++)
total_bits += hist[s] * code_sizes[s];
symbol_codec codec;
codec.start_encoding(64 * 1024);
codec.encode_enable_simulation(true);
codec.encode_transmit_static_huffman_data_model(dm, false);
codec.stop_encoding(false);
total_bits += codec.encode_get_total_bits_written();
pParams->pResult->total_bits = total_bits;
crnlib_delete(pParams);
}
void crn_comp::optimize_alpha_selectors() {
crnlib::vector<uint16>& remapping = m_selector_remaping[cAlpha0];
uint16 n = m_alpha_selectors.size();
remapping.resize(n);
uint8 d[] = {0, 2, 3, 3, 5, 5, 4, 4};
uint8 D6[0x1000];
for (uint16 i = 0; i < 0x1000; i++)
D6[i] = d[(i ^ i >> 6) & 7] + d[(i >> 3 ^ i >> 9) & 7];
crnlib::vector<uint64> selectors(n);
crnlib::vector<uint16> indices(n);
for (uint16 i = 0; i < n; i++) {
selectors[i] = m_alpha_selectors[i];
indices[i] = i;
}
uint64 selected_selector = 0;
for (uint16 left = n; left;) {
uint16 selected_index = 0;
uint min_error = cUINT32_MAX;
for (uint16 i = 0; i < left; i++) {