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// Copyright (c) the JPEG XL Project Authors. All rights reserved.
//
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.
#include "lib/jxl/enc_aux_out.h"
#include <inttypes.h>
#include <stddef.h>
#include <stdint.h>
#include <stdio.h>
#include <algorithm>
#include <numeric> // accumulate
#include <sstream>
#include "lib/jxl/base/printf_macros.h"
#include "lib/jxl/base/status.h"
#include "lib/jxl/color_encoding_internal.h"
#include "lib/jxl/dec_xyb.h"
#include "lib/jxl/image_ops.h"
namespace jxl {
const char* LayerName(size_t layer) {
switch (layer) {
case kLayerHeader:
return "Headers";
case kLayerTOC:
return "TOC";
case kLayerDictionary:
return "Patches";
case kLayerSplines:
return "Splines";
case kLayerNoise:
return "Noise";
case kLayerQuant:
return "Quantizer";
case kLayerModularTree:
return "ModularTree";
case kLayerModularGlobal:
return "ModularGlobal";
case kLayerDC:
return "DC";
case kLayerModularDcGroup:
return "ModularDcGroup";
case kLayerControlFields:
return "ControlFields";
case kLayerOrder:
return "CoeffOrder";
case kLayerAC:
return "ACHistograms";
case kLayerACTokens:
return "ACTokens";
case kLayerModularAcGroup:
return "ModularAcGroup";
default:
JXL_ABORT("Invalid layer %d\n", static_cast<int>(layer));
}
}
void AuxOut::LayerTotals::Print(size_t num_inputs) const {
printf("%10" PRId64, static_cast<int64_t>(total_bits));
if (histogram_bits != 0) {
printf(" [c/i:%6.2f | hst:%8" PRId64 " | ex:%8" PRId64 " | h+c+e:%12.3f",
num_clustered_histograms * 1.0 / num_inputs,
static_cast<int64_t>(histogram_bits >> 3),
static_cast<int64_t>(extra_bits >> 3),
(histogram_bits + clustered_entropy + extra_bits) / 8.0);
printf("]");
}
printf("\n");
}
void AuxOut::Assimilate(const AuxOut& victim) {
for (size_t i = 0; i < layers.size(); ++i) {
layers[i].Assimilate(victim.layers[i]);
}
num_blocks += victim.num_blocks;
num_small_blocks += victim.num_small_blocks;
num_dct4x8_blocks += victim.num_dct4x8_blocks;
num_afv_blocks += victim.num_afv_blocks;
num_dct8_blocks += victim.num_dct8_blocks;
num_dct8x16_blocks += victim.num_dct8x16_blocks;
num_dct8x32_blocks += victim.num_dct8x32_blocks;
num_dct16_blocks += victim.num_dct16_blocks;
num_dct16x32_blocks += victim.num_dct16x32_blocks;
num_dct32_blocks += victim.num_dct32_blocks;
num_dct32x64_blocks += victim.num_dct32x64_blocks;
num_dct64_blocks += victim.num_dct64_blocks;
num_butteraugli_iters += victim.num_butteraugli_iters;
for (size_t i = 0; i < dc_pred_usage.size(); ++i) {
dc_pred_usage[i] += victim.dc_pred_usage[i];
dc_pred_usage_xb[i] += victim.dc_pred_usage_xb[i];
}
max_quant_rescale = std::max(max_quant_rescale, victim.max_quant_rescale);
min_quant_rescale = std::min(min_quant_rescale, victim.min_quant_rescale);
max_bitrate_error = std::max(max_bitrate_error, victim.max_bitrate_error);
min_bitrate_error = std::min(min_bitrate_error, victim.min_bitrate_error);
}
void AuxOut::Print(size_t num_inputs) const {
if (num_inputs == 0) return;
LayerTotals all_layers;
for (size_t i = 0; i < layers.size(); ++i) {
all_layers.Assimilate(layers[i]);
}
printf("Average butteraugli iters: %10.2f\n",
num_butteraugli_iters * 1.0 / num_inputs);
if (min_quant_rescale != 1.0 || max_quant_rescale != 1.0) {
printf("quant rescale range: %f .. %f\n", min_quant_rescale,
max_quant_rescale);
printf("bitrate error range: %.3f%% .. %.3f%%\n",
100.0f * min_bitrate_error, 100.0f * max_bitrate_error);
}
for (size_t i = 0; i < layers.size(); ++i) {
if (layers[i].total_bits != 0) {
printf("Total layer bits %-10s\t", LayerName(i));
printf("%10f%%", 100.0 * layers[i].total_bits / all_layers.total_bits);
layers[i].Print(num_inputs);
}
}
printf("Total image size ");
all_layers.Print(num_inputs);
const uint32_t dc_pred_total =
std::accumulate(dc_pred_usage.begin(), dc_pred_usage.end(), 0u);
const uint32_t dc_pred_total_xb =
std::accumulate(dc_pred_usage_xb.begin(), dc_pred_usage_xb.end(), 0u);
if (dc_pred_total + dc_pred_total_xb != 0) {
printf("\nDC pred Y XB:\n");
for (size_t i = 0; i < dc_pred_usage.size(); ++i) {
printf(" %6u (%5.2f%%) %6u (%5.2f%%)\n", dc_pred_usage[i],
100.0 * dc_pred_usage[i] / dc_pred_total, dc_pred_usage_xb[i],
100.0 * dc_pred_usage_xb[i] / dc_pred_total_xb);
}
}
size_t total_blocks = 0;
size_t total_positions = 0;
if (total_blocks != 0 && total_positions != 0) {
printf("\n\t\t Blocks\t\tPositions\t\t\tBlocks/Position\n");
printf(" Total:\t\t %7" PRIuS "\t\t %7" PRIuS " \t\t\t%10f%%\n\n",
total_blocks, total_positions,
100.0 * total_blocks / total_positions);
}
}
template <typename T>
void AuxOut::DumpImage(const char* label, const Image3<T>& image) const {
if (!dump_image) return;
if (debug_prefix.empty()) return;
std::ostringstream pathname;
pathname << debug_prefix << label << ".png";
(void)dump_image(ConvertToFloat(image), ColorEncoding::SRGB(),
pathname.str());
}
template void AuxOut::DumpImage(const char* label,
const Image3<float>& image) const;
template void AuxOut::DumpImage(const char* label,
const Image3<uint8_t>& image) const;
template <typename T>
void AuxOut::DumpPlaneNormalized(const char* label,
const Plane<T>& image) const {
T min;
T max;
ImageMinMax(image, &min, &max);
Image3B normalized(image.xsize(), image.ysize());
for (size_t c = 0; c < 3; ++c) {
float mul = min == max ? 0 : (255.0f / (max - min));
for (size_t y = 0; y < image.ysize(); ++y) {
const T* JXL_RESTRICT row_in = image.ConstRow(y);
uint8_t* JXL_RESTRICT row_out = normalized.PlaneRow(c, y);
for (size_t x = 0; x < image.xsize(); ++x) {
row_out[x] = static_cast<uint8_t>((row_in[x] - min) * mul);
}
}
}
DumpImage(label, normalized);
}
template void AuxOut::DumpPlaneNormalized(const char* label,
const Plane<float>& image) const;
template void AuxOut::DumpPlaneNormalized(const char* label,
const Plane<uint8_t>& image) const;
void AuxOut::DumpXybImage(const char* label, const Image3F& image) const {
if (!dump_image) return;
if (debug_prefix.empty()) return;
std::ostringstream pathname;
pathname << debug_prefix << label << ".png";
Image3F linear(image.xsize(), image.ysize());
OpsinParams opsin_params;
opsin_params.Init(kDefaultIntensityTarget);
OpsinToLinear(image, Rect(linear), nullptr, &linear, opsin_params);
(void)dump_image(std::move(linear), ColorEncoding::LinearSRGB(),
pathname.str());
}
} // namespace jxl
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