// 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" #include #include "lib/jxl/modular/transform/transform.h" // CheckEqualChannels 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 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++) { StatusOr channel_or = Channel::Create( w, h, input.channel[c0].hshift, input.channel[c0].vshift); JXL_RETURN_IF_ERROR(channel_or.status()); input.channel.insert(input.channel.begin() + c0 + 1, std::move(channel_or).value()); } 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(p[x], 0, static_cast(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 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; ImageI &plane = input.channel[c0].plane; JXL_ASSIGN_OR_RETURN(indices, ImageI::Create(plane.xsize(), plane.ysize())); plane.Swap(indices); 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(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(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(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); JXL_ASSIGN_OR_RETURN(Channel pch, Channel::Create(nb_colors + nb_deltas, nb)); pch.hshift = -1; pch.vshift = -1; input.channel.insert(input.channel.begin(), std::move(pch)); return true; } } // namespace jxl