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Diffstat (limited to '')
-rw-r--r-- | third_party/jpeg-xl/lib/jxl/modular/transform/palette.cc | 176 |
1 files changed, 176 insertions, 0 deletions
diff --git a/third_party/jpeg-xl/lib/jxl/modular/transform/palette.cc b/third_party/jpeg-xl/lib/jxl/modular/transform/palette.cc new file mode 100644 index 0000000000..46129f19f0 --- /dev/null +++ b/third_party/jpeg-xl/lib/jxl/modular/transform/palette.cc @@ -0,0 +1,176 @@ +// 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/modular/transform/palette.h" + +namespace jxl { + +Status InvPalette(Image &input, uint32_t begin_c, uint32_t nb_colors, + uint32_t nb_deltas, Predictor predictor, + const weighted::Header &wp_header, ThreadPool *pool) { + if (input.nb_meta_channels < 1) { + return JXL_FAILURE("Error: Palette transform without palette."); + } + std::atomic<int> num_errors{0}; + int nb = input.channel[0].h; + uint32_t c0 = begin_c + 1; + if (c0 >= input.channel.size()) { + return JXL_FAILURE("Channel is out of range."); + } + size_t w = input.channel[c0].w; + size_t h = input.channel[c0].h; + if (nb < 1) return JXL_FAILURE("Corrupted transforms"); + for (int i = 1; i < nb; i++) { + input.channel.insert( + input.channel.begin() + c0 + 1, + Channel(w, h, input.channel[c0].hshift, input.channel[c0].vshift)); + } + const Channel &palette = input.channel[0]; + const pixel_type *JXL_RESTRICT p_palette = input.channel[0].Row(0); + intptr_t onerow = input.channel[0].plane.PixelsPerRow(); + intptr_t onerow_image = input.channel[c0].plane.PixelsPerRow(); + const int bit_depth = std::min(input.bitdepth, 24); + + if (w == 0) { + // Nothing to do. + // Avoid touching "empty" channels with non-zero height. + } else if (nb_deltas == 0 && predictor == Predictor::Zero) { + if (nb == 1) { + JXL_RETURN_IF_ERROR(RunOnPool( + pool, 0, h, ThreadPool::NoInit, + [&](const uint32_t task, size_t /* thread */) { + const size_t y = task; + pixel_type *p = input.channel[c0].Row(y); + for (size_t x = 0; x < w; x++) { + const int index = Clamp1<int>(p[x], 0, (pixel_type)palette.w - 1); + p[x] = palette_internal::GetPaletteValue( + p_palette, index, /*c=*/0, + /*palette_size=*/palette.w, + /*onerow=*/onerow, /*bit_depth=*/bit_depth); + } + }, + "UndoChannelPalette")); + } else { + JXL_RETURN_IF_ERROR(RunOnPool( + pool, 0, h, ThreadPool::NoInit, + [&](const uint32_t task, size_t /* thread */) { + const size_t y = task; + std::vector<pixel_type *> p_out(nb); + const pixel_type *p_index = input.channel[c0].Row(y); + for (int c = 0; c < nb; c++) + p_out[c] = input.channel[c0 + c].Row(y); + for (size_t x = 0; x < w; x++) { + const int index = p_index[x]; + for (int c = 0; c < nb; c++) { + p_out[c][x] = palette_internal::GetPaletteValue( + p_palette, index, /*c=*/c, + /*palette_size=*/palette.w, + /*onerow=*/onerow, /*bit_depth=*/bit_depth); + } + } + }, + "UndoPalette")); + } + } else { + // Parallelized per channel. + ImageI indices = CopyImage(input.channel[c0].plane); + if (predictor == Predictor::Weighted) { + JXL_RETURN_IF_ERROR(RunOnPool( + pool, 0, nb, ThreadPool::NoInit, + [&](const uint32_t c, size_t /* thread */) { + Channel &channel = input.channel[c0 + c]; + weighted::State wp_state(wp_header, channel.w, channel.h); + for (size_t y = 0; y < channel.h; y++) { + pixel_type *JXL_RESTRICT p = channel.Row(y); + const pixel_type *JXL_RESTRICT idx = indices.Row(y); + for (size_t x = 0; x < channel.w; x++) { + int index = idx[x]; + pixel_type_w val = 0; + const pixel_type palette_entry = + palette_internal::GetPaletteValue( + p_palette, index, /*c=*/c, + /*palette_size=*/palette.w, /*onerow=*/onerow, + /*bit_depth=*/bit_depth); + if (index < static_cast<int32_t>(nb_deltas)) { + PredictionResult pred = + PredictNoTreeWP(channel.w, p + x, onerow_image, x, y, + predictor, &wp_state); + val = pred.guess + palette_entry; + } else { + val = palette_entry; + } + p[x] = val; + wp_state.UpdateErrors(p[x], x, y, channel.w); + } + } + }, + "UndoDeltaPaletteWP")); + } else { + JXL_RETURN_IF_ERROR(RunOnPool( + pool, 0, nb, ThreadPool::NoInit, + [&](const uint32_t c, size_t /* thread */) { + Channel &channel = input.channel[c0 + c]; + for (size_t y = 0; y < channel.h; y++) { + pixel_type *JXL_RESTRICT p = channel.Row(y); + const pixel_type *JXL_RESTRICT idx = indices.Row(y); + for (size_t x = 0; x < channel.w; x++) { + int index = idx[x]; + pixel_type_w val = 0; + const pixel_type palette_entry = + palette_internal::GetPaletteValue( + p_palette, index, /*c=*/c, + /*palette_size=*/palette.w, + /*onerow=*/onerow, /*bit_depth=*/bit_depth); + if (index < static_cast<int32_t>(nb_deltas)) { + PredictionResult pred = PredictNoTreeNoWP( + channel.w, p + x, onerow_image, x, y, predictor); + val = pred.guess + palette_entry; + } else { + val = palette_entry; + } + p[x] = val; + } + } + }, + "UndoDeltaPaletteNoWP")); + } + } + if (c0 >= input.nb_meta_channels) { + // Palette was done on normal channels + input.nb_meta_channels--; + } else { + // Palette was done on metachannels + JXL_ASSERT(static_cast<int>(input.nb_meta_channels) >= 2 - nb); + input.nb_meta_channels -= 2 - nb; + JXL_ASSERT(begin_c + nb - 1 < input.nb_meta_channels); + } + input.channel.erase(input.channel.begin(), input.channel.begin() + 1); + return num_errors.load(std::memory_order_relaxed) == 0; +} + +Status MetaPalette(Image &input, uint32_t begin_c, uint32_t end_c, + uint32_t nb_colors, uint32_t nb_deltas, bool lossy) { + JXL_RETURN_IF_ERROR(CheckEqualChannels(input, begin_c, end_c)); + + size_t nb = end_c - begin_c + 1; + if (begin_c >= input.nb_meta_channels) { + // Palette was done on normal channels + input.nb_meta_channels++; + } else { + // Palette was done on metachannels + JXL_ASSERT(end_c < input.nb_meta_channels); + // we remove nb-1 metachannels and add one + input.nb_meta_channels += 2 - nb; + } + input.channel.erase(input.channel.begin() + begin_c + 1, + input.channel.begin() + end_c + 1); + Channel pch(nb_colors + nb_deltas, nb); + pch.hshift = -1; + pch.vshift = -1; + input.channel.insert(input.channel.begin(), std::move(pch)); + return true; +} + +} // namespace jxl |