options.h (3457B)
1 // Copyright (c) the JPEG XL Project Authors. All rights reserved. 2 // 3 // Use of this source code is governed by a BSD-style 4 // license that can be found in the LICENSE file. 5 6 #ifndef LIB_JXL_MODULAR_OPTIONS_H_ 7 #define LIB_JXL_MODULAR_OPTIONS_H_ 8 9 #include <array> 10 #include <cstddef> 11 #include <cstdint> 12 #include <vector> 13 14 #include "lib/jxl/enc_ans_params.h" 15 16 namespace jxl { 17 18 using PropertyVal = int32_t; 19 using Properties = std::vector<PropertyVal>; 20 21 enum class Predictor : uint32_t { 22 Zero = 0, 23 Left = 1, 24 Top = 2, 25 Average0 = 3, 26 Select = 4, 27 Gradient = 5, 28 Weighted = 6, 29 TopRight = 7, 30 TopLeft = 8, 31 LeftLeft = 9, 32 Average1 = 10, 33 Average2 = 11, 34 Average3 = 12, 35 Average4 = 13, 36 // The following predictors are encoder-only. 37 Best = 14, // Best of Gradient and Weighted 38 Variable = 39 15, // Find the best decision tree for predictors/predictor per row 40 }; 41 42 constexpr Predictor kUndefinedPredictor = static_cast<Predictor>(~0u); 43 44 constexpr size_t kNumModularPredictors = 45 static_cast<size_t>(Predictor::Average4) + 1; 46 constexpr size_t kNumModularEncoderPredictors = 47 static_cast<size_t>(Predictor::Variable) + 1; 48 49 static constexpr ssize_t kNumStaticProperties = 2; // channel, group_id. 50 51 using StaticPropRange = 52 std::array<std::array<uint32_t, 2>, kNumStaticProperties>; 53 54 struct ModularMultiplierInfo { 55 StaticPropRange range; 56 uint32_t multiplier; 57 }; 58 59 struct ModularOptions { 60 /// Used in both encode and decode: 61 62 // Stop encoding/decoding when reaching a (non-meta) channel that has a 63 // dimension bigger than max_chan_size. 64 size_t max_chan_size = 0xFFFFFF; 65 66 // Used during decoding for validation of transforms (sqeeezing) scheme. 67 size_t group_dim = 0x1FFFFFFF; 68 69 /// Encode options: 70 // Fraction of pixels to look at to learn a MA tree 71 // Number of iterations to do to learn a MA tree 72 // (if zero there is no MA context model) 73 float nb_repeats = .5f; 74 75 // Maximum number of (previous channel) properties to use in the MA trees 76 int max_properties = 0; // no previous channels 77 78 // Alternative heuristic tweaks. 79 // Properties default to channel, group, weighted, gradient residual, W-NW, 80 // NW-N, N-NE, N-NN 81 std::vector<uint32_t> splitting_heuristics_properties = {0, 1, 15, 9, 82 10, 11, 12, 13}; 83 float splitting_heuristics_node_threshold = 96; 84 size_t max_property_values = 32; 85 86 // Predictor to use for each channel. 87 Predictor predictor = kUndefinedPredictor; 88 89 int wp_mode = 0; 90 91 float fast_decode_multiplier = 1.01f; 92 93 // Forces the encoder to produce a tree that is compatible with the WP-only 94 // decode path (or with the no-wp path, or the gradient-only path). 95 enum class TreeMode { kGradientOnly, kWPOnly, kNoWP, kDefault }; 96 TreeMode wp_tree_mode = TreeMode::kDefault; 97 98 // Skip fast paths in the encoder. 99 bool skip_encoder_fast_path = false; 100 101 // Kind of tree to use. 102 // TODO(veluca): add tree kinds for JPEG recompression with CfL enabled, 103 // general AC metadata, different DC qualities, and others. 104 enum class TreeKind { 105 kTrivialTreeNoPredictor, 106 kLearn, 107 kJpegTranscodeACMeta, 108 kFalconACMeta, 109 kACMeta, 110 kWPFixedDC, 111 kGradientFixedDC, 112 }; 113 TreeKind tree_kind = TreeKind::kLearn; 114 115 HistogramParams histogram_params; 116 117 // Ignore the image and just pretend all tokens are zeroes 118 bool zero_tokens = false; 119 }; 120 121 } // namespace jxl 122 123 #endif // LIB_JXL_MODULAR_OPTIONS_H_